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Team explains how artemisinin kills malaria parasite
infecting a red blood cell
Photo courtesy of St. Jude
Children’s Research Hospital
Researchers say they have gained a better understanding of how the antimalarial drug artemisinin kills the Plasmodium falciparum parasite.
A chemical proteomics analysis revealed more than 120 protein targets of artemisinin and the mechanism that activates its killing effect.
Given the emergence of artemisinin resistance, the team believes their findings could aid the design of new treatments against drug-resistant parasites.
They reported the findings in Nature Communications.
Previously, only 2 targets of artemisinin had been identified, and their correlation with the parasite-killing effect of the drug had been questioned.
Lin Qingsong, PhD, of the National University of Singapore, and his colleagues identified 124 protein targets of artemisinin in P falciparum. Many of these newly identified protein targets are involved in essential biological processes in the parasite, thus explaining artemisinin’s potent killing effect.
The research suggests that, through its promiscuous targeting mechanism, artemisinin targets the blood-eating nature of the malaria parasite, binding to a broad spectrum of targets simultaneously and fatally disrupting the biochemistry of the parasite.
The study also showed that the main activator of artemisinin is heme, an iron-containing compound that is either biosynthesized by the parasite at its early developmental ring stage or derived from hemoglobin digestion in the later stages.
The drug activation level was found to be much lower in ring-stage parasites, given that artemisinin activation requires heme, which is of much lower abundance and is biosynthesized by the parasite.
In comparison, during the late stages of its life cycle, the parasite actively digests the hemoglobin in infected blood cells as its primary energy source. This releases large amounts of heme, and the drug is able to specifically respond to parasite-infected cells and effectively attack the disease-causing parasites.
“The current findings not only provide a more complete picture of how artemisinin and its derivatives work but also suggest new ways of using the drug,” Dr Lin said. “For instance, to improve drug activation at ring stage, we can explore enhancing the level of heme biosynthesis in the parasite.”
“By understanding that hemoglobin digestion releases huge amounts of heme, which brings about the effective killing mechanism in the later stages, we can also consider prolonging the treatment time to ensure that the drug can effectively kill the parasite through multiple cycles.”
In addition, the researchers are planning to develop novel artemisinin analogues with more specific targeting properties.
infecting a red blood cell
Photo courtesy of St. Jude
Children’s Research Hospital
Researchers say they have gained a better understanding of how the antimalarial drug artemisinin kills the Plasmodium falciparum parasite.
A chemical proteomics analysis revealed more than 120 protein targets of artemisinin and the mechanism that activates its killing effect.
Given the emergence of artemisinin resistance, the team believes their findings could aid the design of new treatments against drug-resistant parasites.
They reported the findings in Nature Communications.
Previously, only 2 targets of artemisinin had been identified, and their correlation with the parasite-killing effect of the drug had been questioned.
Lin Qingsong, PhD, of the National University of Singapore, and his colleagues identified 124 protein targets of artemisinin in P falciparum. Many of these newly identified protein targets are involved in essential biological processes in the parasite, thus explaining artemisinin’s potent killing effect.
The research suggests that, through its promiscuous targeting mechanism, artemisinin targets the blood-eating nature of the malaria parasite, binding to a broad spectrum of targets simultaneously and fatally disrupting the biochemistry of the parasite.
The study also showed that the main activator of artemisinin is heme, an iron-containing compound that is either biosynthesized by the parasite at its early developmental ring stage or derived from hemoglobin digestion in the later stages.
The drug activation level was found to be much lower in ring-stage parasites, given that artemisinin activation requires heme, which is of much lower abundance and is biosynthesized by the parasite.
In comparison, during the late stages of its life cycle, the parasite actively digests the hemoglobin in infected blood cells as its primary energy source. This releases large amounts of heme, and the drug is able to specifically respond to parasite-infected cells and effectively attack the disease-causing parasites.
“The current findings not only provide a more complete picture of how artemisinin and its derivatives work but also suggest new ways of using the drug,” Dr Lin said. “For instance, to improve drug activation at ring stage, we can explore enhancing the level of heme biosynthesis in the parasite.”
“By understanding that hemoglobin digestion releases huge amounts of heme, which brings about the effective killing mechanism in the later stages, we can also consider prolonging the treatment time to ensure that the drug can effectively kill the parasite through multiple cycles.”
In addition, the researchers are planning to develop novel artemisinin analogues with more specific targeting properties.
infecting a red blood cell
Photo courtesy of St. Jude
Children’s Research Hospital
Researchers say they have gained a better understanding of how the antimalarial drug artemisinin kills the Plasmodium falciparum parasite.
A chemical proteomics analysis revealed more than 120 protein targets of artemisinin and the mechanism that activates its killing effect.
Given the emergence of artemisinin resistance, the team believes their findings could aid the design of new treatments against drug-resistant parasites.
They reported the findings in Nature Communications.
Previously, only 2 targets of artemisinin had been identified, and their correlation with the parasite-killing effect of the drug had been questioned.
Lin Qingsong, PhD, of the National University of Singapore, and his colleagues identified 124 protein targets of artemisinin in P falciparum. Many of these newly identified protein targets are involved in essential biological processes in the parasite, thus explaining artemisinin’s potent killing effect.
The research suggests that, through its promiscuous targeting mechanism, artemisinin targets the blood-eating nature of the malaria parasite, binding to a broad spectrum of targets simultaneously and fatally disrupting the biochemistry of the parasite.
The study also showed that the main activator of artemisinin is heme, an iron-containing compound that is either biosynthesized by the parasite at its early developmental ring stage or derived from hemoglobin digestion in the later stages.
The drug activation level was found to be much lower in ring-stage parasites, given that artemisinin activation requires heme, which is of much lower abundance and is biosynthesized by the parasite.
In comparison, during the late stages of its life cycle, the parasite actively digests the hemoglobin in infected blood cells as its primary energy source. This releases large amounts of heme, and the drug is able to specifically respond to parasite-infected cells and effectively attack the disease-causing parasites.
“The current findings not only provide a more complete picture of how artemisinin and its derivatives work but also suggest new ways of using the drug,” Dr Lin said. “For instance, to improve drug activation at ring stage, we can explore enhancing the level of heme biosynthesis in the parasite.”
“By understanding that hemoglobin digestion releases huge amounts of heme, which brings about the effective killing mechanism in the later stages, we can also consider prolonging the treatment time to ensure that the drug can effectively kill the parasite through multiple cycles.”
In addition, the researchers are planning to develop novel artemisinin analogues with more specific targeting properties.
Length of Different‐Hospital Readmissions
Readmissions within a relatively short time after discharge are receiving considerable attention as an area of quality improvement,[1, 2] with increasing emphasis on the relatively large share of readmissions to different hospitals, accounting for 20% to 30% of all readmissions.[3, 4, 5, 6] Returning to a different hospital may affect patient and healthcare outcomes due to breaches in continuity. When information from the previous recent hospitalization is not transferred efficiently and accurately to the next admitting hospital, omissions and duplications can occur, resulting in delayed care and potentially worse outcomes (compared to same hospital readmissions [SHRs]), such as longer length of readmission stay (LORS) and increased costs.[7]
Electronic health records (EHRs) and health information exchange (HIE) systems are increasingly used for storage and retrieval of patient information from various sources, such as laboratories and previous physician visits and hospitalizations, enabling informational continuity by providing vital historical medical information for decision‐making. Whereas EHRs collect, store, and present information that is locally created within a specific clinic or hospital, HIEs connect EHR systems between multiple institutions, allowing providers to share clinical data and achieve interorganizational continuity. Such integrative systems are increasingly being implemented across healthcare systems worldwide.[8, 9, 10] Yet, technical difficulties, costs, competitive concerns, data privacy, and workflow implementation challenges have been described as hindering HIE participation.[11, 12, 13, 14] Moreover, major concerns exist regarding the poor usability of EHRs, their limited ability to support multidisciplinary care, and major difficulties in achieving interoperability with HIEs, which undermine efforts to deliver integrated patient‐centered care.[15] Nonetheless, previous research has demonstrated that HIEs can positively affect healthcare resource use and outcomes, including reduced rates of repeated diagnostic imaging in the emergency evaluation of back pain,[16] reduction in admissions via the emergency department (ED),[17] and reduced rates of readmissions within 7 days.[18] However, it is not known whether HIEs can contribute to positive outcomes when patients are readmitted to a different hospital than the hospital from which they were recently (within the previous 30 days) discharged, potentially bridging the transitional‐care information divide.
In Israel, an innovative HIE system, OFEK (literally horizon), was implemented in 2005 at the largest not‐for‐profit insurer and provider of services, Clalit Health Services (Clalit). Clalit operates as an integrated healthcare delivery system, serving more than 50% of the Israeli population, as part of the country's national health insurance system. OFEK links information on all Clalit enrollees from all hospitals, primary care, and specialty care clinics, laboratories, and diagnostic services into a single, virtual, patient file, enabling providers to obtain complete, real‐time information needed for healthcare decision making at the point of care. Like similar HIE systems, OFEK includes information on previous medical encounters and hospitalizations, previous diagnoses, chronically prescribed medications, previous lab and imaging tests, known allergies, and some demographic information.[19] At the time of this study, OFEK was available in all Clalit hospitals as well as in 2 non‐Clalit (government‐owned and operated) large tertiary‐care centers, resulting in 40% coverage of all hospitalizations through the OFEK HIE system. As part of a large organization‐wide readmission reduction program recently implemented by Clalit for all its members admitted to any hospital in Israel, aimed at early detection and intervention,[20] OFEK was viewed as an important mechanism to help maintain continuity and improve transitions.
To inform current knowledge on different‐hospital readmissions (DHRs) and HIEs, we examined whether having HIE systems can contribute to information continuity and prevent delays in care and the need for more expensive, lengthy readmission stays when patients are readmitted to a different hospital. More specifically, we tested whether there is a difference in the LORS between SHRs and DHRs, and whether DHRs the LORS differ by the availability of an HIE (whether index and readmitting hospital are or are not connected through HIE systems).
METHODS
Study Design and Setting
We conducted a retrospective cohort study based on data of hospitalized Clalit members. Clalit has a centralized data warehouse with a comprehensive EHR containing data on all patients' medical encounters, administrative data, and clinical data compiled from laboratories, imaging centers, and hospitals. At the time of the study, OFEK was operating in all 8 Clalit hospitals and in 2 large government‐owned and operated hospitals in the central and northern parts of the country. Information is linked in the Clalit system and OFEK‐affiliated hospitals through an individual identity number assigned by the Israeli Interior Ministry to every Israeli resident for general identification purposes.
Population
The study examined all internal medicine and intensive‐care unit (ICU) readmissions of adult Clalit members (aged 18 years and older) previously (within the prior 30 days) discharged from internal medicine departments during January 1, 2010 until December 31, 2010 (ie, index hospitalizations). Only readmissions of index hospitalizations with more than a 24‐hour stay were included. A total of 146,266 index hospitalizations met the inclusion criteria. Index admissions that resulted in a transfer to another hospital, a long‐term care facility, or rehabilitation center were not included (N = 11,831). The final study sample included 27,057 readmissions (20.1% of the 134,435 index admissions), which could have resulted in any type of discharge (to patient's home, a long‐term care or rehabilitation facility, or due to death). The study was approved by Clalit's institutional review board.
Outcome Variable
We defined the LORS as the number of days from admission to discharge during readmission.
Main Independent Variable
We assessed information continuity as a categorical variable in which 0 = no information continuity (DHRs with either no HIE at either hospital or an HIE in only 1 of the hospitals), 1 = information continuity through an HIE (DHRs with both hospitals having an HIE), and 2 = full information continuity (readmission to the same hospital).
Covariates
We examined the following known correlates of length of stay (LOS): age, gender, residency in a nursing home, socioeconomic status (SES) based on an indicator of social security entitlement received by low‐income members,[21] and the occurrence of common chronic conditions registered in Clalit's EHR registries[22]: congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), chronic renal failure (CRF), malignancy, diabetes, hypertension, ischemic heart disease, atrial fibrillation, asthma, and disability (indication of a functional limitation). To provide comorbidity adjustment we used the Charlson Comorbidity Index.[23] Additionally, we assessed LOS of the index hospitalization. We included an indicator for the size of the index hospital: small, fewer than 100 beds; medium, 100 to 200 beds; and large, more than 200 beds. Finally, to account for a well‐known correlate of length of hospital stay,[24] we included an indicator for an ICU stay during the readmission.
Statistical Analysis
We first examined the study populations' characteristics and calculated the average LORS for each SHR and DHR category. Due to the skewed distribution of LORS, we also calculated the median and interquartile range (IQR) of LORS and evaluated the difference between categories using the Kruskall‐Wallis test.[25] Sample‐size calculations showed that we would need a sample of >3000 admissions to have 80% power to detect a difference of 0.8 hospitalization days given the 1:3 ratio between the DHR groups. To examine the association between LORS and information continuity, we employed a univariate marginal Cox model.[26] Variables that were significantly (P < 0.05) associated with LORS in the univariate model were entered into a multivariate marginal Cox model, clustering by patient and using a robust sandwich covariance matrix estimate. Additionally, we performed a sensitivity analysis using hierarchichal modeling to account for potential variations due to hospital level factors. A low hazard ratio (<1) represented an association of the covariate with decreased likelihood of discharge, that is, longer LORS. All analyses were conducted with SPSS version 20 (IBM, Armonk, NY) and SAS version 9.3 (SAS Institute Inc., Cary, NC).
RESULTS
The study included a total of 27,057 readmissions, of which 23,927 (88.4%) were SHRs and 3130 (11.6%) were DHRs. Of all DHRs, in 792 (2.9%) of the cases, both hospitals had HIEs (partial information continuity), and in 2338 (8.6%), either 1 or both did not have an HIE system (thus meaning there was no information continuity). Characteristics of the study population are shown in Table 1. Most (75%) of the readmissions were of patients over the age of 65 years, though only 7% were nursing home residents. More than half the study's population consisted of patients with low SES. The most common chronic conditions were hypertension (77%), ischemic heart disease (52%), and diabetes (48%). Other chronic conditions were arrhythmia (38%), CHF (35%), disability (31%), COPD (28%), malignancy (28%), and asthma (16%). In more than 55% of the index hospitalizations, the LOS was 4 days or less, and most index admissions (64%) were in large hospitals. Table 1 also displays the study population by the type of readmission: SHR, DHR with HIE, and DHR without HIE. As compared to patients readmitted to the same hospital, patients with DHRs were younger (P < 0.001), less likely to be nursing home residents (P < 0.001), and had longer LOS during the index admission (P < 0.001). Additionally, patients with SHRs were more likely to have their index admission at a large hospital (P < 0.001), had a higher comorbidity score (P < 0.043), and were less likely be treated in the ICU during their readmission (P < 0.001) compared to their DHR counterparts. Patients with DHRs without an HIE were similar in most characteristics to those with an HIE, except for having an ICU stay during their readmission (6.4% compared with 9.2%, respectively).
Characteristics | All Readmissions, n = 27,057 | SHR, n = 23,927 | DHR With HIE, n = 792 | DHR Without HIE, n = 2,338 | P Value |
---|---|---|---|---|---|
| |||||
All personal characteristics | |||||
Age, n (%) | <0.001 | ||||
1844 years | 1,328 (4.9) | 1,095 (4.6) | 58 (7.3) | 175 (7.5) | |
4564 years | 5,370 (19.8) | 4,597 (19.2) | 197 (24.9) | 576 (24.6) | |
6584 years | 14,059 (52.0) | 12,500 (52.2) | 402 (50.8) | 1,157 (49.5) | |
85+ years | 6,300 (23.3) | 5,735 (24.0) | 135 (17.0) | 430 (18.4) | |
Female sex, n (%) | 13,742 (50.8) | 12,040 (50.3) | 418 (52.8) | 1,284 (54.9) | <0.001 |
Low socioeconomic status, n (%) | 15,473 (57.2) | 13,670 (57.1) | 453 (57.2) | 1,350 (57.7) | |
Residency in a nursing home, n (%) | 1,857 (6.9) | 1,743 (7.3) | 27 (3.4) | 87 (3.7) | <0.001 |
Common chronic conditions, n (%) | |||||
Hypertension | 20,797 (76.9) | 18,484 (77.3) | 588 (74.2) | 1,725 (73.8) | <0.001 |
Ischemic heart disease | 14,150 (52.3) | 12,577 (52.6) | 397 (50.1) | 1,176 (50.3) | 0.052 |
Diabetes | 13,052 (48.2) | 11,589 (48.4) | 345 (43.6) | 1,118 (47.8) | 0.024 |
Arrhythmia | 10,306 (38.1) | 9,197 (38.4) | 292 (36.9) | 817 (34.9) | 0.003 |
Chronic renal failure | 9,486 (35.1) | 8,454 (35.3) | 262 (33.1) | 770 (32.9) | 0.034 |
Congestive heart failure | 9,216 (34.1) | 8,232 (34.4) | 270 (34.1) | 714 (30.5) | 0.001 |
Disability | 8,362 (30.9) | 7,600 (31.8) | 165 (20.8) | 597 (25.5) | <0.001 |
Chronic obstructive pulmonary disease | 7,671 (28.4) | 6,888 (28.8) | 201 (25.4) | 582 (24.9) | <0.001 |
Malignancy | 7,642 (28.2) | 6,763 (28.3) | 220 (27.8) | 659 (28.2) | 0.954 |
Asthma | 4,491 (16.6) | 4,040 (16.9) | 109 (13.8) | 342 (14.6) | 0.002 |
Charlson score, mean [SD] | 4.54 [3.15] | 4.58 [3.14] | 4.14 [3.08] | 4.25 [3.24] | 0.043 |
Index hospitalization characteristics (LOS during index hospitalization), n (%) | <0.001 | ||||
24 days | 14,961 (55.3) | 13,310 (55.6) | 428 (54.0) | 1,223 (52.3) | |
57 days | 6,366 (23.5) | 5,654 (23.6) | 174 (22.0) | 538 (23.0) | |
8 days and more | 5,730 (21.2) | 4,963 (20.7) | 190 (24.0) | 577 (24.7) | |
Hospital size in index hospitalization (no. of hospitals in each category), n (%) | <0.001 | ||||
Small, <100 beds (8) | 1,498 (5.5) | 1,166 (4.9) | 23 (2.9) | 309 (13.2) | |
Medium, 100200 beds (9) | 8,129 (30.0) | 7,113 (29.7) | 316 (39.9) | 700 (29.9) | |
Large, >200 beds (10) | 17,430 (64.4) | 15,648 (65.4) | 453 (57.2) | 1,329 (56.8) | |
Intensive care unit during readmission, n (%) | 869 (3.2) | 647 (2.7) | 73 (9.2) | 149 (6.4) | <0.001 |
The mean LORS in SHRs was shorter by 1 day than the mean LORS for DHRs: 6.3 (95% confidence interval [CI]: 6.2‐6.4) versus 7.3 (95% CI: 7.0‐7.6), respectively. Mean LORS in DHRs with or without HIE was 7.6 (95% CI: 7.0‐8.3) and 7.2 (95% CI: 6.8‐7.6), respectively. Although median LORS was similar (4 days), the IQR differed, resulting in significant differences between the SHR and DHR groups (Table 2).
Information Continuity | No. of Readmissions | Mean LORS (95% CI) | Median (Q1Q3) | Kruskal‐Wallis P Value |
---|---|---|---|---|
| ||||
SHRs | 23,927 (88.4) | 6.3 (6.26.4) | 4 (27) | |
DHRs | 3,130 (11.6) | 7.3 (7.07.6) | 4 (28) | |
DHRs with HIE | 792 (2.9) | 7.6 (7.08.3) | 4 (29) | |
DHRs without HIE | 2,338 (8.7) | 7.2 (6.87.6) | 4 (28) | |
Total | 27,057 | 6.4 (6.36.5) | 4 (27) | <0.001 |
In the multivariate model, partial continuity (DHRs with an HIE) was associated with decreased likelihood of discharge on any given day compared with full continuity (SHR) (hazard ratio [HR] = 0.85, 95% CI: 0.79‐0.91). Similar results were obtained for no continuity (DHRs without an HIE) (HR = 0.90, 95% CI: 0.86‐0.94). The difference between DHRs with and without an HIE was not significant (overlapping confidence intervals). Other factors associated with a lower HR for discharge during each day of the readmission were older age, residency in a nursing home, CHF, CRF, disability, malignancy, and long LOS (8+ days) during the index hospitalization. Patients with asthma or ischemic heart disease had a higher HR for discharge during each readmission day (Table 3). We performed a sensitivity analysis using hierarchical modeling (patients nested within hospitals), which resulted in similar findings in terms of directionality and magnitude of the relationships and significance levels.
Characteristics | Univariate Model | Multivariate Model | ||
---|---|---|---|---|
Hazard Ratio (95% CI) | P Value | Hazard Ratio (95% CI) | P Value | |
| ||||
Information continuity | ||||
SHR | Reference | Reference | ||
DHR with HIE | 0.87 (0.810.93) | <0.001 | 0.86 (0.800.93) | <0.001 |
DHR without HIE | 0.91 (0.870.94) | <0.001 | 0.90 (0.870.94) | <0.001 |
Age | ||||
844 years | 1.22 (1.181.26) | <0.001 | 1.14 (1.071.22) | <0.001 |
4564 years | 1.16 (1.141.18) | <0.001 | 1.11 (1.061.1) | <0.001 |
6584 years | 1.01 (0.991.02) | 0.53 | 0.99 (0.961.02) | 0.60 |
85+ years | Reference | Reference | ||
Sex | ||||
Male | 0.97 (0.950.99) | 0.008 | 0.98 (0.961.01) | 0.19 |
Female | Reference | Reference | ||
Socioeconomic status | ||||
Low | 0.98 (0.970.99) | 0.11 | ||
Other | Reference | |||
Residency in a nursing home | ||||
Nursing home | 0.90 (0.880.92) | <0.001 | 0.90 (0.860.95) | <0.001 |
All others | Reference | Reference | ||
Common chronic conditions (reference: without condition) | ||||
Hypertension | 0.94 (0.930.96) | <0.001 | 1.01 (0.971.04) | 0.69 |
Ischemic heart disease | 1.00 (0.991.01) | 0.93 | 1.06 (1.031.09) | <0.001 |
Diabetes | 0.97 (0.950.98) | 0.004 | 0.99 (0.971.02) | 0.64 |
Arrhythmia | 0.96 (0.950.97) | 0.002 | 1.01 (0.981.04) | 0.39 |
Chronic renal failure | 0.92 (0.910.93) | <0.001 | 0.96 (0.930.99) | 0.01 |
Congestive heart failure | 0.93 (0.920.94) | <0.001 | 0.96 (0.930.99) | 0.01 |
Disability | 0.86 (0.850.87) | <0.001 | 0.90 (0.870.92) | <0.001 |
Chronic obstructive pulmonary disease | 0.99 (0.981.01) | 0.66 | ||
Malignancy | 0.97 (0.960.98) | 0.03 | 0.98 (0.961.01) | 0.28 |
Asthma | 1.04 (1.021.06) | 0.03 | 1.04 (1.001.07) | 0.03 |
Charlson score | 0.99 (0.980.99) | <0.001 | 0.99 (0.991.00) | 0.04 |
LOS during index hospitalization | ||||
Days 24 | 1.52 (1.491.54) | <0.001 | 1.49 (1.451.54) | <0.001 |
Days 57 | 1.21 (1.191.23) | <0.001 | 1.20 (1.161.24) | <0.001 |
8 days and more | Reference | Reference | ||
Hospital size in index hospitalization | ||||
Small, <100 beds (8) | 0.94 (0.920.97) | 0.02 | 1.00 (0.951.05) | 0.93 |
Medium, 100200 beds (9) | 1.00 (0.991.02) | 0.78 | 1.01 (0.991.04) | 0.38 |
Large, >200 beds (10) | Reference | Reference | ||
Intensive care unit in readmission | ||||
Yes | 0.75 (0.700.80) | <0.001 | 0.74 (0.690.79) | <0.001 |
No | Reference | Reference |
DISCUSSION
This study shows that readmission to a different hospital results in longer duration of the readmission stay compared with readmission to the same index hospital. Our results also show that having HIE systems in both the index and readmitting hospitals does not protect against these negative outcomes, as there was no difference in the length of the readmission stay based on the availability of HIE systems. Factors that were found to be associated with longer readmission stays are well known indicators of the complexity of the patient's medical condition, such as the presence of disability, comorbidity, and ICU treatment during the readmission.[24, 27]
The shorter LORS in SHRs may be due to the familiarity of physicians and other healthcare providers with the patient and his or her condition, especially as the policy in SHRs in Israel is to readmit to the same unit from which the patient was recently discharged. This same hospital familiarity is especially important as hospital care in Israel follows the hospitalist model, in which responsibility for patient care is transferred from the patient's primary care physician to the hospital's physician, resulting in increased need for integration through HIE systems, especially when patients are readmitted to a different hospital.[28, 29]
Our findings, congruent with previous research on DHRs and poor outcomes,[7] could also be explained by the inefficiency associated with transitions. For example, patients frequently leave the hospital with pending lab tests, often with abnormal results that would change the course of care.[30] Because these pending tests are often omitted from the hospital discharge summaries,[31] if patients are hospitalized in a different hospital, the same tests may be ordered again, or a course of treatment that does not acknowledge the test results could be taken. Such time‐consuming duplication can be prevented in SHRs, where the index‐hospital records may be already more complete.
Our null findings regarding the contribution of HIE systems may be explained by the low levels of HIE actual use. Although we did not directly assess use, previous research reports that actual use of HIE is limited.[12] An Israeli study on the effects of the use of the OFEK system on ED physicians' admission decisions found that the patient's medical history was viewed in only 31.2% of all 281,750 ED referrals.[19] In another Israeli‐based ED study, even lower usage levels were found, with the OFEK system having been accessed in only 16% of all 3,219,910 ED referrals.[32] Low levels of HIE use have also been reported in the United States. An additional study, which tested the implementation of HIE in hospitals and clinics, showed that in only 2.3% of encounters did providers access the HIE record.[33] Another study conducted in 12 ED sites and 2 ambulatory clinics reported rates of 6.8% HIE use.[34] Moreover, the null effect of integrated health information reported here is congruent with findings from a US study on implementation of an electronic discharge instructions form with embedded computerized medication reconciliation, which was not found to be associated with postdischarge outcomes.[35]
A wide range of factors may influence decisions on HIE use: patient‐level factors,[36] perceived medical complexity of the patient,[33, 34] and the number of prior hospitalizations.[33, 34, 36] Healthcare systemlevel factors may include: time constraints, which may be positively[32] or negatively[33] associated with HIE use, and organizational policies or incentives.[33] Use may also be associated with features of the HIE technology itself, such as difficulty to access, difficulty to use once accessed, and the quality of information it contains.[37] Additionally, there is some evidence of the link between tight functional integration and higher proportions of usage.[38] Although comprehensive studies on factors affecting the use of the OFEK system in Israeli internal medicine units are still needed, the lack of its integration within each hospital's EHR system may serve as a major explanatory factor for the low usage levels.
The findings from this study should be interpreted in light of its limitations. First, compared with previously reported DHR rates (20%30%),[3, 5] the rate observed in our population was relatively low (about 12%). Previous research was restricted to heart failure patients[3] or assessed DHR in surgical, as well as internal medicine, patients.[5] Our lower rates may have been affected by the type of population (hospitalized internal medicine patients) and/or by characteristics of the Clalit healthcare system, which serves as an integrated provider network as well as insurer. Generalization from 1 health care system to others should be made with caution. Nonetheless, our results may underestimate the potential effect in other healthcare systems with less structural integration. Additionally, as noted above, information on the actual use of an HIE in the course of medical decision making during readmission was absent. Future studies should examine the potential benefit of an HIE with measures that capture providers' use of HIEs. Also, the LORS may be influenced by other factors not investigated here, and further future studies should examine additional outcomes such as costs, patient well‐being, and satisfaction. Finally, causality could not be determined, and future research in this realm should aim to search for the pathways connecting readmission to a different hospital, with and without HIEs, to readmission LOS and additional outcomes.
To conclude, our findings show that patients readmitted to a different hospital are at risk for prolonged LORS, regardless of the availability of HIE systems. Implementing HIE systems is the focus of substantial efforts by policymakers and is considered a key part of the meaningful use of electronic health information. HIE features in the provisions of the Health Information Technology for Economic and Clinical Health Act[39] because it can furnish providers with complete, timely information at the point of care. Moreover, although there has been substantial growth in the number of healthcare organizations that have operational an HIE, its ability to lead to improved outcomes has yet to be realized.[8, 10] The Israeli experience reported here suggests that provisions are needed that will ensure actual use of HIEs, which might in turn minimize the difference between DHRs and SHRs.
Acknowledgements
The authors acknowledge Chandra Cohen‐Stavi, MPA, and Orly Tonkikh, MA, for their contribution to this study.
Disclosures
The study was supported in part by a grant from the Israel National Institute for Health Policy Research (NIHP) (10/127). The authors report no conflicts of interest.
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Readmissions within a relatively short time after discharge are receiving considerable attention as an area of quality improvement,[1, 2] with increasing emphasis on the relatively large share of readmissions to different hospitals, accounting for 20% to 30% of all readmissions.[3, 4, 5, 6] Returning to a different hospital may affect patient and healthcare outcomes due to breaches in continuity. When information from the previous recent hospitalization is not transferred efficiently and accurately to the next admitting hospital, omissions and duplications can occur, resulting in delayed care and potentially worse outcomes (compared to same hospital readmissions [SHRs]), such as longer length of readmission stay (LORS) and increased costs.[7]
Electronic health records (EHRs) and health information exchange (HIE) systems are increasingly used for storage and retrieval of patient information from various sources, such as laboratories and previous physician visits and hospitalizations, enabling informational continuity by providing vital historical medical information for decision‐making. Whereas EHRs collect, store, and present information that is locally created within a specific clinic or hospital, HIEs connect EHR systems between multiple institutions, allowing providers to share clinical data and achieve interorganizational continuity. Such integrative systems are increasingly being implemented across healthcare systems worldwide.[8, 9, 10] Yet, technical difficulties, costs, competitive concerns, data privacy, and workflow implementation challenges have been described as hindering HIE participation.[11, 12, 13, 14] Moreover, major concerns exist regarding the poor usability of EHRs, their limited ability to support multidisciplinary care, and major difficulties in achieving interoperability with HIEs, which undermine efforts to deliver integrated patient‐centered care.[15] Nonetheless, previous research has demonstrated that HIEs can positively affect healthcare resource use and outcomes, including reduced rates of repeated diagnostic imaging in the emergency evaluation of back pain,[16] reduction in admissions via the emergency department (ED),[17] and reduced rates of readmissions within 7 days.[18] However, it is not known whether HIEs can contribute to positive outcomes when patients are readmitted to a different hospital than the hospital from which they were recently (within the previous 30 days) discharged, potentially bridging the transitional‐care information divide.
In Israel, an innovative HIE system, OFEK (literally horizon), was implemented in 2005 at the largest not‐for‐profit insurer and provider of services, Clalit Health Services (Clalit). Clalit operates as an integrated healthcare delivery system, serving more than 50% of the Israeli population, as part of the country's national health insurance system. OFEK links information on all Clalit enrollees from all hospitals, primary care, and specialty care clinics, laboratories, and diagnostic services into a single, virtual, patient file, enabling providers to obtain complete, real‐time information needed for healthcare decision making at the point of care. Like similar HIE systems, OFEK includes information on previous medical encounters and hospitalizations, previous diagnoses, chronically prescribed medications, previous lab and imaging tests, known allergies, and some demographic information.[19] At the time of this study, OFEK was available in all Clalit hospitals as well as in 2 non‐Clalit (government‐owned and operated) large tertiary‐care centers, resulting in 40% coverage of all hospitalizations through the OFEK HIE system. As part of a large organization‐wide readmission reduction program recently implemented by Clalit for all its members admitted to any hospital in Israel, aimed at early detection and intervention,[20] OFEK was viewed as an important mechanism to help maintain continuity and improve transitions.
To inform current knowledge on different‐hospital readmissions (DHRs) and HIEs, we examined whether having HIE systems can contribute to information continuity and prevent delays in care and the need for more expensive, lengthy readmission stays when patients are readmitted to a different hospital. More specifically, we tested whether there is a difference in the LORS between SHRs and DHRs, and whether DHRs the LORS differ by the availability of an HIE (whether index and readmitting hospital are or are not connected through HIE systems).
METHODS
Study Design and Setting
We conducted a retrospective cohort study based on data of hospitalized Clalit members. Clalit has a centralized data warehouse with a comprehensive EHR containing data on all patients' medical encounters, administrative data, and clinical data compiled from laboratories, imaging centers, and hospitals. At the time of the study, OFEK was operating in all 8 Clalit hospitals and in 2 large government‐owned and operated hospitals in the central and northern parts of the country. Information is linked in the Clalit system and OFEK‐affiliated hospitals through an individual identity number assigned by the Israeli Interior Ministry to every Israeli resident for general identification purposes.
Population
The study examined all internal medicine and intensive‐care unit (ICU) readmissions of adult Clalit members (aged 18 years and older) previously (within the prior 30 days) discharged from internal medicine departments during January 1, 2010 until December 31, 2010 (ie, index hospitalizations). Only readmissions of index hospitalizations with more than a 24‐hour stay were included. A total of 146,266 index hospitalizations met the inclusion criteria. Index admissions that resulted in a transfer to another hospital, a long‐term care facility, or rehabilitation center were not included (N = 11,831). The final study sample included 27,057 readmissions (20.1% of the 134,435 index admissions), which could have resulted in any type of discharge (to patient's home, a long‐term care or rehabilitation facility, or due to death). The study was approved by Clalit's institutional review board.
Outcome Variable
We defined the LORS as the number of days from admission to discharge during readmission.
Main Independent Variable
We assessed information continuity as a categorical variable in which 0 = no information continuity (DHRs with either no HIE at either hospital or an HIE in only 1 of the hospitals), 1 = information continuity through an HIE (DHRs with both hospitals having an HIE), and 2 = full information continuity (readmission to the same hospital).
Covariates
We examined the following known correlates of length of stay (LOS): age, gender, residency in a nursing home, socioeconomic status (SES) based on an indicator of social security entitlement received by low‐income members,[21] and the occurrence of common chronic conditions registered in Clalit's EHR registries[22]: congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), chronic renal failure (CRF), malignancy, diabetes, hypertension, ischemic heart disease, atrial fibrillation, asthma, and disability (indication of a functional limitation). To provide comorbidity adjustment we used the Charlson Comorbidity Index.[23] Additionally, we assessed LOS of the index hospitalization. We included an indicator for the size of the index hospital: small, fewer than 100 beds; medium, 100 to 200 beds; and large, more than 200 beds. Finally, to account for a well‐known correlate of length of hospital stay,[24] we included an indicator for an ICU stay during the readmission.
Statistical Analysis
We first examined the study populations' characteristics and calculated the average LORS for each SHR and DHR category. Due to the skewed distribution of LORS, we also calculated the median and interquartile range (IQR) of LORS and evaluated the difference between categories using the Kruskall‐Wallis test.[25] Sample‐size calculations showed that we would need a sample of >3000 admissions to have 80% power to detect a difference of 0.8 hospitalization days given the 1:3 ratio between the DHR groups. To examine the association between LORS and information continuity, we employed a univariate marginal Cox model.[26] Variables that were significantly (P < 0.05) associated with LORS in the univariate model were entered into a multivariate marginal Cox model, clustering by patient and using a robust sandwich covariance matrix estimate. Additionally, we performed a sensitivity analysis using hierarchichal modeling to account for potential variations due to hospital level factors. A low hazard ratio (<1) represented an association of the covariate with decreased likelihood of discharge, that is, longer LORS. All analyses were conducted with SPSS version 20 (IBM, Armonk, NY) and SAS version 9.3 (SAS Institute Inc., Cary, NC).
RESULTS
The study included a total of 27,057 readmissions, of which 23,927 (88.4%) were SHRs and 3130 (11.6%) were DHRs. Of all DHRs, in 792 (2.9%) of the cases, both hospitals had HIEs (partial information continuity), and in 2338 (8.6%), either 1 or both did not have an HIE system (thus meaning there was no information continuity). Characteristics of the study population are shown in Table 1. Most (75%) of the readmissions were of patients over the age of 65 years, though only 7% were nursing home residents. More than half the study's population consisted of patients with low SES. The most common chronic conditions were hypertension (77%), ischemic heart disease (52%), and diabetes (48%). Other chronic conditions were arrhythmia (38%), CHF (35%), disability (31%), COPD (28%), malignancy (28%), and asthma (16%). In more than 55% of the index hospitalizations, the LOS was 4 days or less, and most index admissions (64%) were in large hospitals. Table 1 also displays the study population by the type of readmission: SHR, DHR with HIE, and DHR without HIE. As compared to patients readmitted to the same hospital, patients with DHRs were younger (P < 0.001), less likely to be nursing home residents (P < 0.001), and had longer LOS during the index admission (P < 0.001). Additionally, patients with SHRs were more likely to have their index admission at a large hospital (P < 0.001), had a higher comorbidity score (P < 0.043), and were less likely be treated in the ICU during their readmission (P < 0.001) compared to their DHR counterparts. Patients with DHRs without an HIE were similar in most characteristics to those with an HIE, except for having an ICU stay during their readmission (6.4% compared with 9.2%, respectively).
Characteristics | All Readmissions, n = 27,057 | SHR, n = 23,927 | DHR With HIE, n = 792 | DHR Without HIE, n = 2,338 | P Value |
---|---|---|---|---|---|
| |||||
All personal characteristics | |||||
Age, n (%) | <0.001 | ||||
1844 years | 1,328 (4.9) | 1,095 (4.6) | 58 (7.3) | 175 (7.5) | |
4564 years | 5,370 (19.8) | 4,597 (19.2) | 197 (24.9) | 576 (24.6) | |
6584 years | 14,059 (52.0) | 12,500 (52.2) | 402 (50.8) | 1,157 (49.5) | |
85+ years | 6,300 (23.3) | 5,735 (24.0) | 135 (17.0) | 430 (18.4) | |
Female sex, n (%) | 13,742 (50.8) | 12,040 (50.3) | 418 (52.8) | 1,284 (54.9) | <0.001 |
Low socioeconomic status, n (%) | 15,473 (57.2) | 13,670 (57.1) | 453 (57.2) | 1,350 (57.7) | |
Residency in a nursing home, n (%) | 1,857 (6.9) | 1,743 (7.3) | 27 (3.4) | 87 (3.7) | <0.001 |
Common chronic conditions, n (%) | |||||
Hypertension | 20,797 (76.9) | 18,484 (77.3) | 588 (74.2) | 1,725 (73.8) | <0.001 |
Ischemic heart disease | 14,150 (52.3) | 12,577 (52.6) | 397 (50.1) | 1,176 (50.3) | 0.052 |
Diabetes | 13,052 (48.2) | 11,589 (48.4) | 345 (43.6) | 1,118 (47.8) | 0.024 |
Arrhythmia | 10,306 (38.1) | 9,197 (38.4) | 292 (36.9) | 817 (34.9) | 0.003 |
Chronic renal failure | 9,486 (35.1) | 8,454 (35.3) | 262 (33.1) | 770 (32.9) | 0.034 |
Congestive heart failure | 9,216 (34.1) | 8,232 (34.4) | 270 (34.1) | 714 (30.5) | 0.001 |
Disability | 8,362 (30.9) | 7,600 (31.8) | 165 (20.8) | 597 (25.5) | <0.001 |
Chronic obstructive pulmonary disease | 7,671 (28.4) | 6,888 (28.8) | 201 (25.4) | 582 (24.9) | <0.001 |
Malignancy | 7,642 (28.2) | 6,763 (28.3) | 220 (27.8) | 659 (28.2) | 0.954 |
Asthma | 4,491 (16.6) | 4,040 (16.9) | 109 (13.8) | 342 (14.6) | 0.002 |
Charlson score, mean [SD] | 4.54 [3.15] | 4.58 [3.14] | 4.14 [3.08] | 4.25 [3.24] | 0.043 |
Index hospitalization characteristics (LOS during index hospitalization), n (%) | <0.001 | ||||
24 days | 14,961 (55.3) | 13,310 (55.6) | 428 (54.0) | 1,223 (52.3) | |
57 days | 6,366 (23.5) | 5,654 (23.6) | 174 (22.0) | 538 (23.0) | |
8 days and more | 5,730 (21.2) | 4,963 (20.7) | 190 (24.0) | 577 (24.7) | |
Hospital size in index hospitalization (no. of hospitals in each category), n (%) | <0.001 | ||||
Small, <100 beds (8) | 1,498 (5.5) | 1,166 (4.9) | 23 (2.9) | 309 (13.2) | |
Medium, 100200 beds (9) | 8,129 (30.0) | 7,113 (29.7) | 316 (39.9) | 700 (29.9) | |
Large, >200 beds (10) | 17,430 (64.4) | 15,648 (65.4) | 453 (57.2) | 1,329 (56.8) | |
Intensive care unit during readmission, n (%) | 869 (3.2) | 647 (2.7) | 73 (9.2) | 149 (6.4) | <0.001 |
The mean LORS in SHRs was shorter by 1 day than the mean LORS for DHRs: 6.3 (95% confidence interval [CI]: 6.2‐6.4) versus 7.3 (95% CI: 7.0‐7.6), respectively. Mean LORS in DHRs with or without HIE was 7.6 (95% CI: 7.0‐8.3) and 7.2 (95% CI: 6.8‐7.6), respectively. Although median LORS was similar (4 days), the IQR differed, resulting in significant differences between the SHR and DHR groups (Table 2).
Information Continuity | No. of Readmissions | Mean LORS (95% CI) | Median (Q1Q3) | Kruskal‐Wallis P Value |
---|---|---|---|---|
| ||||
SHRs | 23,927 (88.4) | 6.3 (6.26.4) | 4 (27) | |
DHRs | 3,130 (11.6) | 7.3 (7.07.6) | 4 (28) | |
DHRs with HIE | 792 (2.9) | 7.6 (7.08.3) | 4 (29) | |
DHRs without HIE | 2,338 (8.7) | 7.2 (6.87.6) | 4 (28) | |
Total | 27,057 | 6.4 (6.36.5) | 4 (27) | <0.001 |
In the multivariate model, partial continuity (DHRs with an HIE) was associated with decreased likelihood of discharge on any given day compared with full continuity (SHR) (hazard ratio [HR] = 0.85, 95% CI: 0.79‐0.91). Similar results were obtained for no continuity (DHRs without an HIE) (HR = 0.90, 95% CI: 0.86‐0.94). The difference between DHRs with and without an HIE was not significant (overlapping confidence intervals). Other factors associated with a lower HR for discharge during each day of the readmission were older age, residency in a nursing home, CHF, CRF, disability, malignancy, and long LOS (8+ days) during the index hospitalization. Patients with asthma or ischemic heart disease had a higher HR for discharge during each readmission day (Table 3). We performed a sensitivity analysis using hierarchical modeling (patients nested within hospitals), which resulted in similar findings in terms of directionality and magnitude of the relationships and significance levels.
Characteristics | Univariate Model | Multivariate Model | ||
---|---|---|---|---|
Hazard Ratio (95% CI) | P Value | Hazard Ratio (95% CI) | P Value | |
| ||||
Information continuity | ||||
SHR | Reference | Reference | ||
DHR with HIE | 0.87 (0.810.93) | <0.001 | 0.86 (0.800.93) | <0.001 |
DHR without HIE | 0.91 (0.870.94) | <0.001 | 0.90 (0.870.94) | <0.001 |
Age | ||||
844 years | 1.22 (1.181.26) | <0.001 | 1.14 (1.071.22) | <0.001 |
4564 years | 1.16 (1.141.18) | <0.001 | 1.11 (1.061.1) | <0.001 |
6584 years | 1.01 (0.991.02) | 0.53 | 0.99 (0.961.02) | 0.60 |
85+ years | Reference | Reference | ||
Sex | ||||
Male | 0.97 (0.950.99) | 0.008 | 0.98 (0.961.01) | 0.19 |
Female | Reference | Reference | ||
Socioeconomic status | ||||
Low | 0.98 (0.970.99) | 0.11 | ||
Other | Reference | |||
Residency in a nursing home | ||||
Nursing home | 0.90 (0.880.92) | <0.001 | 0.90 (0.860.95) | <0.001 |
All others | Reference | Reference | ||
Common chronic conditions (reference: without condition) | ||||
Hypertension | 0.94 (0.930.96) | <0.001 | 1.01 (0.971.04) | 0.69 |
Ischemic heart disease | 1.00 (0.991.01) | 0.93 | 1.06 (1.031.09) | <0.001 |
Diabetes | 0.97 (0.950.98) | 0.004 | 0.99 (0.971.02) | 0.64 |
Arrhythmia | 0.96 (0.950.97) | 0.002 | 1.01 (0.981.04) | 0.39 |
Chronic renal failure | 0.92 (0.910.93) | <0.001 | 0.96 (0.930.99) | 0.01 |
Congestive heart failure | 0.93 (0.920.94) | <0.001 | 0.96 (0.930.99) | 0.01 |
Disability | 0.86 (0.850.87) | <0.001 | 0.90 (0.870.92) | <0.001 |
Chronic obstructive pulmonary disease | 0.99 (0.981.01) | 0.66 | ||
Malignancy | 0.97 (0.960.98) | 0.03 | 0.98 (0.961.01) | 0.28 |
Asthma | 1.04 (1.021.06) | 0.03 | 1.04 (1.001.07) | 0.03 |
Charlson score | 0.99 (0.980.99) | <0.001 | 0.99 (0.991.00) | 0.04 |
LOS during index hospitalization | ||||
Days 24 | 1.52 (1.491.54) | <0.001 | 1.49 (1.451.54) | <0.001 |
Days 57 | 1.21 (1.191.23) | <0.001 | 1.20 (1.161.24) | <0.001 |
8 days and more | Reference | Reference | ||
Hospital size in index hospitalization | ||||
Small, <100 beds (8) | 0.94 (0.920.97) | 0.02 | 1.00 (0.951.05) | 0.93 |
Medium, 100200 beds (9) | 1.00 (0.991.02) | 0.78 | 1.01 (0.991.04) | 0.38 |
Large, >200 beds (10) | Reference | Reference | ||
Intensive care unit in readmission | ||||
Yes | 0.75 (0.700.80) | <0.001 | 0.74 (0.690.79) | <0.001 |
No | Reference | Reference |
DISCUSSION
This study shows that readmission to a different hospital results in longer duration of the readmission stay compared with readmission to the same index hospital. Our results also show that having HIE systems in both the index and readmitting hospitals does not protect against these negative outcomes, as there was no difference in the length of the readmission stay based on the availability of HIE systems. Factors that were found to be associated with longer readmission stays are well known indicators of the complexity of the patient's medical condition, such as the presence of disability, comorbidity, and ICU treatment during the readmission.[24, 27]
The shorter LORS in SHRs may be due to the familiarity of physicians and other healthcare providers with the patient and his or her condition, especially as the policy in SHRs in Israel is to readmit to the same unit from which the patient was recently discharged. This same hospital familiarity is especially important as hospital care in Israel follows the hospitalist model, in which responsibility for patient care is transferred from the patient's primary care physician to the hospital's physician, resulting in increased need for integration through HIE systems, especially when patients are readmitted to a different hospital.[28, 29]
Our findings, congruent with previous research on DHRs and poor outcomes,[7] could also be explained by the inefficiency associated with transitions. For example, patients frequently leave the hospital with pending lab tests, often with abnormal results that would change the course of care.[30] Because these pending tests are often omitted from the hospital discharge summaries,[31] if patients are hospitalized in a different hospital, the same tests may be ordered again, or a course of treatment that does not acknowledge the test results could be taken. Such time‐consuming duplication can be prevented in SHRs, where the index‐hospital records may be already more complete.
Our null findings regarding the contribution of HIE systems may be explained by the low levels of HIE actual use. Although we did not directly assess use, previous research reports that actual use of HIE is limited.[12] An Israeli study on the effects of the use of the OFEK system on ED physicians' admission decisions found that the patient's medical history was viewed in only 31.2% of all 281,750 ED referrals.[19] In another Israeli‐based ED study, even lower usage levels were found, with the OFEK system having been accessed in only 16% of all 3,219,910 ED referrals.[32] Low levels of HIE use have also been reported in the United States. An additional study, which tested the implementation of HIE in hospitals and clinics, showed that in only 2.3% of encounters did providers access the HIE record.[33] Another study conducted in 12 ED sites and 2 ambulatory clinics reported rates of 6.8% HIE use.[34] Moreover, the null effect of integrated health information reported here is congruent with findings from a US study on implementation of an electronic discharge instructions form with embedded computerized medication reconciliation, which was not found to be associated with postdischarge outcomes.[35]
A wide range of factors may influence decisions on HIE use: patient‐level factors,[36] perceived medical complexity of the patient,[33, 34] and the number of prior hospitalizations.[33, 34, 36] Healthcare systemlevel factors may include: time constraints, which may be positively[32] or negatively[33] associated with HIE use, and organizational policies or incentives.[33] Use may also be associated with features of the HIE technology itself, such as difficulty to access, difficulty to use once accessed, and the quality of information it contains.[37] Additionally, there is some evidence of the link between tight functional integration and higher proportions of usage.[38] Although comprehensive studies on factors affecting the use of the OFEK system in Israeli internal medicine units are still needed, the lack of its integration within each hospital's EHR system may serve as a major explanatory factor for the low usage levels.
The findings from this study should be interpreted in light of its limitations. First, compared with previously reported DHR rates (20%30%),[3, 5] the rate observed in our population was relatively low (about 12%). Previous research was restricted to heart failure patients[3] or assessed DHR in surgical, as well as internal medicine, patients.[5] Our lower rates may have been affected by the type of population (hospitalized internal medicine patients) and/or by characteristics of the Clalit healthcare system, which serves as an integrated provider network as well as insurer. Generalization from 1 health care system to others should be made with caution. Nonetheless, our results may underestimate the potential effect in other healthcare systems with less structural integration. Additionally, as noted above, information on the actual use of an HIE in the course of medical decision making during readmission was absent. Future studies should examine the potential benefit of an HIE with measures that capture providers' use of HIEs. Also, the LORS may be influenced by other factors not investigated here, and further future studies should examine additional outcomes such as costs, patient well‐being, and satisfaction. Finally, causality could not be determined, and future research in this realm should aim to search for the pathways connecting readmission to a different hospital, with and without HIEs, to readmission LOS and additional outcomes.
To conclude, our findings show that patients readmitted to a different hospital are at risk for prolonged LORS, regardless of the availability of HIE systems. Implementing HIE systems is the focus of substantial efforts by policymakers and is considered a key part of the meaningful use of electronic health information. HIE features in the provisions of the Health Information Technology for Economic and Clinical Health Act[39] because it can furnish providers with complete, timely information at the point of care. Moreover, although there has been substantial growth in the number of healthcare organizations that have operational an HIE, its ability to lead to improved outcomes has yet to be realized.[8, 10] The Israeli experience reported here suggests that provisions are needed that will ensure actual use of HIEs, which might in turn minimize the difference between DHRs and SHRs.
Acknowledgements
The authors acknowledge Chandra Cohen‐Stavi, MPA, and Orly Tonkikh, MA, for their contribution to this study.
Disclosures
The study was supported in part by a grant from the Israel National Institute for Health Policy Research (NIHP) (10/127). The authors report no conflicts of interest.
Readmissions within a relatively short time after discharge are receiving considerable attention as an area of quality improvement,[1, 2] with increasing emphasis on the relatively large share of readmissions to different hospitals, accounting for 20% to 30% of all readmissions.[3, 4, 5, 6] Returning to a different hospital may affect patient and healthcare outcomes due to breaches in continuity. When information from the previous recent hospitalization is not transferred efficiently and accurately to the next admitting hospital, omissions and duplications can occur, resulting in delayed care and potentially worse outcomes (compared to same hospital readmissions [SHRs]), such as longer length of readmission stay (LORS) and increased costs.[7]
Electronic health records (EHRs) and health information exchange (HIE) systems are increasingly used for storage and retrieval of patient information from various sources, such as laboratories and previous physician visits and hospitalizations, enabling informational continuity by providing vital historical medical information for decision‐making. Whereas EHRs collect, store, and present information that is locally created within a specific clinic or hospital, HIEs connect EHR systems between multiple institutions, allowing providers to share clinical data and achieve interorganizational continuity. Such integrative systems are increasingly being implemented across healthcare systems worldwide.[8, 9, 10] Yet, technical difficulties, costs, competitive concerns, data privacy, and workflow implementation challenges have been described as hindering HIE participation.[11, 12, 13, 14] Moreover, major concerns exist regarding the poor usability of EHRs, their limited ability to support multidisciplinary care, and major difficulties in achieving interoperability with HIEs, which undermine efforts to deliver integrated patient‐centered care.[15] Nonetheless, previous research has demonstrated that HIEs can positively affect healthcare resource use and outcomes, including reduced rates of repeated diagnostic imaging in the emergency evaluation of back pain,[16] reduction in admissions via the emergency department (ED),[17] and reduced rates of readmissions within 7 days.[18] However, it is not known whether HIEs can contribute to positive outcomes when patients are readmitted to a different hospital than the hospital from which they were recently (within the previous 30 days) discharged, potentially bridging the transitional‐care information divide.
In Israel, an innovative HIE system, OFEK (literally horizon), was implemented in 2005 at the largest not‐for‐profit insurer and provider of services, Clalit Health Services (Clalit). Clalit operates as an integrated healthcare delivery system, serving more than 50% of the Israeli population, as part of the country's national health insurance system. OFEK links information on all Clalit enrollees from all hospitals, primary care, and specialty care clinics, laboratories, and diagnostic services into a single, virtual, patient file, enabling providers to obtain complete, real‐time information needed for healthcare decision making at the point of care. Like similar HIE systems, OFEK includes information on previous medical encounters and hospitalizations, previous diagnoses, chronically prescribed medications, previous lab and imaging tests, known allergies, and some demographic information.[19] At the time of this study, OFEK was available in all Clalit hospitals as well as in 2 non‐Clalit (government‐owned and operated) large tertiary‐care centers, resulting in 40% coverage of all hospitalizations through the OFEK HIE system. As part of a large organization‐wide readmission reduction program recently implemented by Clalit for all its members admitted to any hospital in Israel, aimed at early detection and intervention,[20] OFEK was viewed as an important mechanism to help maintain continuity and improve transitions.
To inform current knowledge on different‐hospital readmissions (DHRs) and HIEs, we examined whether having HIE systems can contribute to information continuity and prevent delays in care and the need for more expensive, lengthy readmission stays when patients are readmitted to a different hospital. More specifically, we tested whether there is a difference in the LORS between SHRs and DHRs, and whether DHRs the LORS differ by the availability of an HIE (whether index and readmitting hospital are or are not connected through HIE systems).
METHODS
Study Design and Setting
We conducted a retrospective cohort study based on data of hospitalized Clalit members. Clalit has a centralized data warehouse with a comprehensive EHR containing data on all patients' medical encounters, administrative data, and clinical data compiled from laboratories, imaging centers, and hospitals. At the time of the study, OFEK was operating in all 8 Clalit hospitals and in 2 large government‐owned and operated hospitals in the central and northern parts of the country. Information is linked in the Clalit system and OFEK‐affiliated hospitals through an individual identity number assigned by the Israeli Interior Ministry to every Israeli resident for general identification purposes.
Population
The study examined all internal medicine and intensive‐care unit (ICU) readmissions of adult Clalit members (aged 18 years and older) previously (within the prior 30 days) discharged from internal medicine departments during January 1, 2010 until December 31, 2010 (ie, index hospitalizations). Only readmissions of index hospitalizations with more than a 24‐hour stay were included. A total of 146,266 index hospitalizations met the inclusion criteria. Index admissions that resulted in a transfer to another hospital, a long‐term care facility, or rehabilitation center were not included (N = 11,831). The final study sample included 27,057 readmissions (20.1% of the 134,435 index admissions), which could have resulted in any type of discharge (to patient's home, a long‐term care or rehabilitation facility, or due to death). The study was approved by Clalit's institutional review board.
Outcome Variable
We defined the LORS as the number of days from admission to discharge during readmission.
Main Independent Variable
We assessed information continuity as a categorical variable in which 0 = no information continuity (DHRs with either no HIE at either hospital or an HIE in only 1 of the hospitals), 1 = information continuity through an HIE (DHRs with both hospitals having an HIE), and 2 = full information continuity (readmission to the same hospital).
Covariates
We examined the following known correlates of length of stay (LOS): age, gender, residency in a nursing home, socioeconomic status (SES) based on an indicator of social security entitlement received by low‐income members,[21] and the occurrence of common chronic conditions registered in Clalit's EHR registries[22]: congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), chronic renal failure (CRF), malignancy, diabetes, hypertension, ischemic heart disease, atrial fibrillation, asthma, and disability (indication of a functional limitation). To provide comorbidity adjustment we used the Charlson Comorbidity Index.[23] Additionally, we assessed LOS of the index hospitalization. We included an indicator for the size of the index hospital: small, fewer than 100 beds; medium, 100 to 200 beds; and large, more than 200 beds. Finally, to account for a well‐known correlate of length of hospital stay,[24] we included an indicator for an ICU stay during the readmission.
Statistical Analysis
We first examined the study populations' characteristics and calculated the average LORS for each SHR and DHR category. Due to the skewed distribution of LORS, we also calculated the median and interquartile range (IQR) of LORS and evaluated the difference between categories using the Kruskall‐Wallis test.[25] Sample‐size calculations showed that we would need a sample of >3000 admissions to have 80% power to detect a difference of 0.8 hospitalization days given the 1:3 ratio between the DHR groups. To examine the association between LORS and information continuity, we employed a univariate marginal Cox model.[26] Variables that were significantly (P < 0.05) associated with LORS in the univariate model were entered into a multivariate marginal Cox model, clustering by patient and using a robust sandwich covariance matrix estimate. Additionally, we performed a sensitivity analysis using hierarchichal modeling to account for potential variations due to hospital level factors. A low hazard ratio (<1) represented an association of the covariate with decreased likelihood of discharge, that is, longer LORS. All analyses were conducted with SPSS version 20 (IBM, Armonk, NY) and SAS version 9.3 (SAS Institute Inc., Cary, NC).
RESULTS
The study included a total of 27,057 readmissions, of which 23,927 (88.4%) were SHRs and 3130 (11.6%) were DHRs. Of all DHRs, in 792 (2.9%) of the cases, both hospitals had HIEs (partial information continuity), and in 2338 (8.6%), either 1 or both did not have an HIE system (thus meaning there was no information continuity). Characteristics of the study population are shown in Table 1. Most (75%) of the readmissions were of patients over the age of 65 years, though only 7% were nursing home residents. More than half the study's population consisted of patients with low SES. The most common chronic conditions were hypertension (77%), ischemic heart disease (52%), and diabetes (48%). Other chronic conditions were arrhythmia (38%), CHF (35%), disability (31%), COPD (28%), malignancy (28%), and asthma (16%). In more than 55% of the index hospitalizations, the LOS was 4 days or less, and most index admissions (64%) were in large hospitals. Table 1 also displays the study population by the type of readmission: SHR, DHR with HIE, and DHR without HIE. As compared to patients readmitted to the same hospital, patients with DHRs were younger (P < 0.001), less likely to be nursing home residents (P < 0.001), and had longer LOS during the index admission (P < 0.001). Additionally, patients with SHRs were more likely to have their index admission at a large hospital (P < 0.001), had a higher comorbidity score (P < 0.043), and were less likely be treated in the ICU during their readmission (P < 0.001) compared to their DHR counterparts. Patients with DHRs without an HIE were similar in most characteristics to those with an HIE, except for having an ICU stay during their readmission (6.4% compared with 9.2%, respectively).
Characteristics | All Readmissions, n = 27,057 | SHR, n = 23,927 | DHR With HIE, n = 792 | DHR Without HIE, n = 2,338 | P Value |
---|---|---|---|---|---|
| |||||
All personal characteristics | |||||
Age, n (%) | <0.001 | ||||
1844 years | 1,328 (4.9) | 1,095 (4.6) | 58 (7.3) | 175 (7.5) | |
4564 years | 5,370 (19.8) | 4,597 (19.2) | 197 (24.9) | 576 (24.6) | |
6584 years | 14,059 (52.0) | 12,500 (52.2) | 402 (50.8) | 1,157 (49.5) | |
85+ years | 6,300 (23.3) | 5,735 (24.0) | 135 (17.0) | 430 (18.4) | |
Female sex, n (%) | 13,742 (50.8) | 12,040 (50.3) | 418 (52.8) | 1,284 (54.9) | <0.001 |
Low socioeconomic status, n (%) | 15,473 (57.2) | 13,670 (57.1) | 453 (57.2) | 1,350 (57.7) | |
Residency in a nursing home, n (%) | 1,857 (6.9) | 1,743 (7.3) | 27 (3.4) | 87 (3.7) | <0.001 |
Common chronic conditions, n (%) | |||||
Hypertension | 20,797 (76.9) | 18,484 (77.3) | 588 (74.2) | 1,725 (73.8) | <0.001 |
Ischemic heart disease | 14,150 (52.3) | 12,577 (52.6) | 397 (50.1) | 1,176 (50.3) | 0.052 |
Diabetes | 13,052 (48.2) | 11,589 (48.4) | 345 (43.6) | 1,118 (47.8) | 0.024 |
Arrhythmia | 10,306 (38.1) | 9,197 (38.4) | 292 (36.9) | 817 (34.9) | 0.003 |
Chronic renal failure | 9,486 (35.1) | 8,454 (35.3) | 262 (33.1) | 770 (32.9) | 0.034 |
Congestive heart failure | 9,216 (34.1) | 8,232 (34.4) | 270 (34.1) | 714 (30.5) | 0.001 |
Disability | 8,362 (30.9) | 7,600 (31.8) | 165 (20.8) | 597 (25.5) | <0.001 |
Chronic obstructive pulmonary disease | 7,671 (28.4) | 6,888 (28.8) | 201 (25.4) | 582 (24.9) | <0.001 |
Malignancy | 7,642 (28.2) | 6,763 (28.3) | 220 (27.8) | 659 (28.2) | 0.954 |
Asthma | 4,491 (16.6) | 4,040 (16.9) | 109 (13.8) | 342 (14.6) | 0.002 |
Charlson score, mean [SD] | 4.54 [3.15] | 4.58 [3.14] | 4.14 [3.08] | 4.25 [3.24] | 0.043 |
Index hospitalization characteristics (LOS during index hospitalization), n (%) | <0.001 | ||||
24 days | 14,961 (55.3) | 13,310 (55.6) | 428 (54.0) | 1,223 (52.3) | |
57 days | 6,366 (23.5) | 5,654 (23.6) | 174 (22.0) | 538 (23.0) | |
8 days and more | 5,730 (21.2) | 4,963 (20.7) | 190 (24.0) | 577 (24.7) | |
Hospital size in index hospitalization (no. of hospitals in each category), n (%) | <0.001 | ||||
Small, <100 beds (8) | 1,498 (5.5) | 1,166 (4.9) | 23 (2.9) | 309 (13.2) | |
Medium, 100200 beds (9) | 8,129 (30.0) | 7,113 (29.7) | 316 (39.9) | 700 (29.9) | |
Large, >200 beds (10) | 17,430 (64.4) | 15,648 (65.4) | 453 (57.2) | 1,329 (56.8) | |
Intensive care unit during readmission, n (%) | 869 (3.2) | 647 (2.7) | 73 (9.2) | 149 (6.4) | <0.001 |
The mean LORS in SHRs was shorter by 1 day than the mean LORS for DHRs: 6.3 (95% confidence interval [CI]: 6.2‐6.4) versus 7.3 (95% CI: 7.0‐7.6), respectively. Mean LORS in DHRs with or without HIE was 7.6 (95% CI: 7.0‐8.3) and 7.2 (95% CI: 6.8‐7.6), respectively. Although median LORS was similar (4 days), the IQR differed, resulting in significant differences between the SHR and DHR groups (Table 2).
Information Continuity | No. of Readmissions | Mean LORS (95% CI) | Median (Q1Q3) | Kruskal‐Wallis P Value |
---|---|---|---|---|
| ||||
SHRs | 23,927 (88.4) | 6.3 (6.26.4) | 4 (27) | |
DHRs | 3,130 (11.6) | 7.3 (7.07.6) | 4 (28) | |
DHRs with HIE | 792 (2.9) | 7.6 (7.08.3) | 4 (29) | |
DHRs without HIE | 2,338 (8.7) | 7.2 (6.87.6) | 4 (28) | |
Total | 27,057 | 6.4 (6.36.5) | 4 (27) | <0.001 |
In the multivariate model, partial continuity (DHRs with an HIE) was associated with decreased likelihood of discharge on any given day compared with full continuity (SHR) (hazard ratio [HR] = 0.85, 95% CI: 0.79‐0.91). Similar results were obtained for no continuity (DHRs without an HIE) (HR = 0.90, 95% CI: 0.86‐0.94). The difference between DHRs with and without an HIE was not significant (overlapping confidence intervals). Other factors associated with a lower HR for discharge during each day of the readmission were older age, residency in a nursing home, CHF, CRF, disability, malignancy, and long LOS (8+ days) during the index hospitalization. Patients with asthma or ischemic heart disease had a higher HR for discharge during each readmission day (Table 3). We performed a sensitivity analysis using hierarchical modeling (patients nested within hospitals), which resulted in similar findings in terms of directionality and magnitude of the relationships and significance levels.
Characteristics | Univariate Model | Multivariate Model | ||
---|---|---|---|---|
Hazard Ratio (95% CI) | P Value | Hazard Ratio (95% CI) | P Value | |
| ||||
Information continuity | ||||
SHR | Reference | Reference | ||
DHR with HIE | 0.87 (0.810.93) | <0.001 | 0.86 (0.800.93) | <0.001 |
DHR without HIE | 0.91 (0.870.94) | <0.001 | 0.90 (0.870.94) | <0.001 |
Age | ||||
844 years | 1.22 (1.181.26) | <0.001 | 1.14 (1.071.22) | <0.001 |
4564 years | 1.16 (1.141.18) | <0.001 | 1.11 (1.061.1) | <0.001 |
6584 years | 1.01 (0.991.02) | 0.53 | 0.99 (0.961.02) | 0.60 |
85+ years | Reference | Reference | ||
Sex | ||||
Male | 0.97 (0.950.99) | 0.008 | 0.98 (0.961.01) | 0.19 |
Female | Reference | Reference | ||
Socioeconomic status | ||||
Low | 0.98 (0.970.99) | 0.11 | ||
Other | Reference | |||
Residency in a nursing home | ||||
Nursing home | 0.90 (0.880.92) | <0.001 | 0.90 (0.860.95) | <0.001 |
All others | Reference | Reference | ||
Common chronic conditions (reference: without condition) | ||||
Hypertension | 0.94 (0.930.96) | <0.001 | 1.01 (0.971.04) | 0.69 |
Ischemic heart disease | 1.00 (0.991.01) | 0.93 | 1.06 (1.031.09) | <0.001 |
Diabetes | 0.97 (0.950.98) | 0.004 | 0.99 (0.971.02) | 0.64 |
Arrhythmia | 0.96 (0.950.97) | 0.002 | 1.01 (0.981.04) | 0.39 |
Chronic renal failure | 0.92 (0.910.93) | <0.001 | 0.96 (0.930.99) | 0.01 |
Congestive heart failure | 0.93 (0.920.94) | <0.001 | 0.96 (0.930.99) | 0.01 |
Disability | 0.86 (0.850.87) | <0.001 | 0.90 (0.870.92) | <0.001 |
Chronic obstructive pulmonary disease | 0.99 (0.981.01) | 0.66 | ||
Malignancy | 0.97 (0.960.98) | 0.03 | 0.98 (0.961.01) | 0.28 |
Asthma | 1.04 (1.021.06) | 0.03 | 1.04 (1.001.07) | 0.03 |
Charlson score | 0.99 (0.980.99) | <0.001 | 0.99 (0.991.00) | 0.04 |
LOS during index hospitalization | ||||
Days 24 | 1.52 (1.491.54) | <0.001 | 1.49 (1.451.54) | <0.001 |
Days 57 | 1.21 (1.191.23) | <0.001 | 1.20 (1.161.24) | <0.001 |
8 days and more | Reference | Reference | ||
Hospital size in index hospitalization | ||||
Small, <100 beds (8) | 0.94 (0.920.97) | 0.02 | 1.00 (0.951.05) | 0.93 |
Medium, 100200 beds (9) | 1.00 (0.991.02) | 0.78 | 1.01 (0.991.04) | 0.38 |
Large, >200 beds (10) | Reference | Reference | ||
Intensive care unit in readmission | ||||
Yes | 0.75 (0.700.80) | <0.001 | 0.74 (0.690.79) | <0.001 |
No | Reference | Reference |
DISCUSSION
This study shows that readmission to a different hospital results in longer duration of the readmission stay compared with readmission to the same index hospital. Our results also show that having HIE systems in both the index and readmitting hospitals does not protect against these negative outcomes, as there was no difference in the length of the readmission stay based on the availability of HIE systems. Factors that were found to be associated with longer readmission stays are well known indicators of the complexity of the patient's medical condition, such as the presence of disability, comorbidity, and ICU treatment during the readmission.[24, 27]
The shorter LORS in SHRs may be due to the familiarity of physicians and other healthcare providers with the patient and his or her condition, especially as the policy in SHRs in Israel is to readmit to the same unit from which the patient was recently discharged. This same hospital familiarity is especially important as hospital care in Israel follows the hospitalist model, in which responsibility for patient care is transferred from the patient's primary care physician to the hospital's physician, resulting in increased need for integration through HIE systems, especially when patients are readmitted to a different hospital.[28, 29]
Our findings, congruent with previous research on DHRs and poor outcomes,[7] could also be explained by the inefficiency associated with transitions. For example, patients frequently leave the hospital with pending lab tests, often with abnormal results that would change the course of care.[30] Because these pending tests are often omitted from the hospital discharge summaries,[31] if patients are hospitalized in a different hospital, the same tests may be ordered again, or a course of treatment that does not acknowledge the test results could be taken. Such time‐consuming duplication can be prevented in SHRs, where the index‐hospital records may be already more complete.
Our null findings regarding the contribution of HIE systems may be explained by the low levels of HIE actual use. Although we did not directly assess use, previous research reports that actual use of HIE is limited.[12] An Israeli study on the effects of the use of the OFEK system on ED physicians' admission decisions found that the patient's medical history was viewed in only 31.2% of all 281,750 ED referrals.[19] In another Israeli‐based ED study, even lower usage levels were found, with the OFEK system having been accessed in only 16% of all 3,219,910 ED referrals.[32] Low levels of HIE use have also been reported in the United States. An additional study, which tested the implementation of HIE in hospitals and clinics, showed that in only 2.3% of encounters did providers access the HIE record.[33] Another study conducted in 12 ED sites and 2 ambulatory clinics reported rates of 6.8% HIE use.[34] Moreover, the null effect of integrated health information reported here is congruent with findings from a US study on implementation of an electronic discharge instructions form with embedded computerized medication reconciliation, which was not found to be associated with postdischarge outcomes.[35]
A wide range of factors may influence decisions on HIE use: patient‐level factors,[36] perceived medical complexity of the patient,[33, 34] and the number of prior hospitalizations.[33, 34, 36] Healthcare systemlevel factors may include: time constraints, which may be positively[32] or negatively[33] associated with HIE use, and organizational policies or incentives.[33] Use may also be associated with features of the HIE technology itself, such as difficulty to access, difficulty to use once accessed, and the quality of information it contains.[37] Additionally, there is some evidence of the link between tight functional integration and higher proportions of usage.[38] Although comprehensive studies on factors affecting the use of the OFEK system in Israeli internal medicine units are still needed, the lack of its integration within each hospital's EHR system may serve as a major explanatory factor for the low usage levels.
The findings from this study should be interpreted in light of its limitations. First, compared with previously reported DHR rates (20%30%),[3, 5] the rate observed in our population was relatively low (about 12%). Previous research was restricted to heart failure patients[3] or assessed DHR in surgical, as well as internal medicine, patients.[5] Our lower rates may have been affected by the type of population (hospitalized internal medicine patients) and/or by characteristics of the Clalit healthcare system, which serves as an integrated provider network as well as insurer. Generalization from 1 health care system to others should be made with caution. Nonetheless, our results may underestimate the potential effect in other healthcare systems with less structural integration. Additionally, as noted above, information on the actual use of an HIE in the course of medical decision making during readmission was absent. Future studies should examine the potential benefit of an HIE with measures that capture providers' use of HIEs. Also, the LORS may be influenced by other factors not investigated here, and further future studies should examine additional outcomes such as costs, patient well‐being, and satisfaction. Finally, causality could not be determined, and future research in this realm should aim to search for the pathways connecting readmission to a different hospital, with and without HIEs, to readmission LOS and additional outcomes.
To conclude, our findings show that patients readmitted to a different hospital are at risk for prolonged LORS, regardless of the availability of HIE systems. Implementing HIE systems is the focus of substantial efforts by policymakers and is considered a key part of the meaningful use of electronic health information. HIE features in the provisions of the Health Information Technology for Economic and Clinical Health Act[39] because it can furnish providers with complete, timely information at the point of care. Moreover, although there has been substantial growth in the number of healthcare organizations that have operational an HIE, its ability to lead to improved outcomes has yet to be realized.[8, 10] The Israeli experience reported here suggests that provisions are needed that will ensure actual use of HIEs, which might in turn minimize the difference between DHRs and SHRs.
Acknowledgements
The authors acknowledge Chandra Cohen‐Stavi, MPA, and Orly Tonkikh, MA, for their contribution to this study.
Disclosures
The study was supported in part by a grant from the Israel National Institute for Health Policy Research (NIHP) (10/127). The authors report no conflicts of interest.
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- Assessing preventability in the quest to reduce hospital readmissions. J Hosp Med. 2014;9:598–603. , , , , , .
- Preventing 30‐day hospital readmissions: a systematic review and meta‐analysis of randomized trials. JAMA Intern Med. 2014;174:1095–1107. , , , et al.
- Is same‐hospital readmission rate a good surrogate for all‐hospital readmission rate? Med Care. 2010;48:477–481. , , , et al.
- Hospital readmission rates: the impacts of age, payer, and mental health diagnoses. J Ambul Care Manage. 2013;36(2):147–155. , , , .
- Limitations of using same‐hospital readmission metrics. Int J Qual Health Care. 2013;25(6):633–639. , , , .
- Hospital inpatient and outpatient services. In: Report to the Congress: promoting greater efficiency in Medicare. Washington, DC: Medicare Payment Advisory Commission., March 2012;45–66.
- For‐profit hospital status and rehospitalizations at different hospitals: an analysis of Medicare data. Ann Intern Med. 2010;153:718–727. , , , , .
- Health information technology: an updated systematic review with a focus on meaningful use. Ann Intern Med. 2014;160:48–54. , , , .
- The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Aff (Millwood). 2011;30(3):464–471. , , , .
- Health information exchange among US hospitals. Am J Manag Care. 2011;17:761–768. , , .
- A survey of health information exchange organizations in the United States: implications for meaningful use. Ann Intern Med. 2011;54:666–671. , , .
- Physicians' potential use and preferences related to health information exchange. Int J Med Inform. 2011;80:171–180. , , , , .
- Provider stakeholders' perceived benefit from a nascent health information exchange: a qualitative analysis. J Med Syst. 2012;36:601–613. , , , et al.
- More than just a question of technology: factors related to hospitals' adoption and implementation of health information exchange. Int J Med Inform. 2010;79:797–806. .
- Leveraging health information technology to achieve the “triple aim” of healthcare reform. J Am Med Inform Assoc. 2015;22(4):849–856. , , .
- Health information exchange reduces repeated diagnostic imaging for back pain. Ann Emerg Med. 2013;62:16–24. , , , , , .
- Association between use of a health information exchange system and hospital admissions. Appl Clin Inform. 2014;5:219. , , , , .
- The impact of EHR and HIE on reducing avoidable admissions: controlling main differential diagnoses. BMC Med Inform Decis Mak. 2013;13:49. , , .
- The impact of an integrated hospital‐community medical information system on quality and service utilization in hospital departments. Int J Med Inform. 2010;79(9):649–657. , , , et al.
- Predicting 30‐day readmissions with preadmission electronic health record data. Med Care. 2015;53:283–289. , , , , ,
- Assessing socioeconomic health care utilization inequity in Israel: impact of alternative approaches to morbidity adjustment. BMC Public Health. 2011;11(1):609. , , , , .
- Prevalence of selected chronic diseases in Israel. Isr Med Assoc J. 2001;3:404–408. , .
- A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40:373–383. , , , .
- Systematic review of risk adjustment models of hospital length of stay (LOS). Med Care. 2015;53:355–365. , , , , .
- Use of ranks in one‐criterion variance analysis. J Am Stat Assoc. 1952;47:583–621. , .
- Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. J Am Stat Assoc. 1989;84:1065–1073. , , .
- Disability impacts length of stay in general internal medicine patients. J Gen Intern Med. 2014;29:885–890. , , , , , .
- The hospitalist movement—time to move on. N Engl J Med. 2007;357:2627–2629. .
- Association of hospitalist presence and hospital‐level outcome measures among Medicare patients. J Hosp Med. 2014;9:1–6. , , .
- Patient safety concerns arising from test results that return after hospital discharge. Ann Intern Med. 2005;143:121–128. , , , et al.
- Adequacy of hospital discharge summaries in documenting tests with pending results and outpatient follow‐up providers. J Gen Intern Med. 2009;24:1002–1006. , , , et al.
- Using electronic medical record systems for admission decisions in emergency departments: examining the crowdedness effect. J Med Syst. 2012;36:3795–3803. , , .
- Factors motivating and affecting health information exchange usage. J Am Med Inform Assoc. 2011;18(2):143–149. , , , , , .
- Health information exchange usage in emergency departments and clinics: the who, what, and why. J Am Med Inform Assoc. 2011;18:690–697. , , , et al.
- Effect of standardized electronic discharge instructions on post‐discharge hospital utilization. J Gen Intern Med. 2011;26:718–723. , , , , .
- Health information exchange technology on the front lines of healthcare: workflow factors and patterns of use. J Am Med Inform Assoc. 2012;19:392–400. , , .
- The DeLone and McLean model of information systems success: a ten‐year update. J Manag Inf Syst. 2003;19:9–30. , .
- Architectural strategies and issues with health information exchange. AMIA Annu Symp Proc. 2006:814–818. , , , et al.
- Launching HITECH. N Engl J Med. 2010;362(5):382–385. .
© 2015 Society of Hospital Medicine
Aneuploidy screening: Newer noninvasive test gains traction
Discuss cell-free DNA testing when offering fetal aneuploidy screening to pregnant women.1,2
Strength of recommendation
A: Based on multiple large, multi-center cohort studies.
Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.1
Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.2
Illustrative case
A 28-year-old gravida 2, para 1001 at 10 weeks gestation presents to your clinic for a routine first-trimester prenatal visit. Her first child has no known chromosomal abnormalities and she has no family history of aneuploidy. She asks you which tests are available to screen her fetus for chromosomal abnormalities.
Pregnant women have traditionally been offered some combination of serum biomarkers and nuchal translucency to assess the risk of fetal aneuploidy. Cell-free DNA testing (cfDNA) is a form of noninvasive prenatal testing that uses maternal serum samples to conduct massively parallel sequencing of cell-free fetal DNA fragments. It has been offered to pregnant women as a screening test to detect fetal chromosomal abnormalities since 2011 after multiple clinical studies found high sensitivities, specificities, and negative predictive values (NPVs) for detecting aneuploidy.3-6 However until 2015, practice guidelines from the American Congress of Obstetricians and Gynecologists (ACOG) recommended that standard aneuploidy screening or diagnostic testing be offered to all pregnant women and cfDNA be reserved for women with pregnancies at high risk for aneuploidy (strength of recommendation: B).7
CARE (Comparison of Aneuploidy Risk Evaluation) and NEXT (Noninvasive Examination of Trisomy) are 2 large studies that compared cfDNA and standard aneuploidy screening methods in pregnant women at low risk for fetal aneuploidy. Based on new data from these and other studies, ACOG and the Society for Maternal-Fetal Medicine (SMFM) released a new consensus statement in June 2015 that addressed the use of cfDNA in the general obstetric population. The 2 groups still recommend conventional first- and second-trimester screening by serum chemical biomarkers and nuchal translucency as the first-line approach for low-risk women who want to pursue aneuploidy screening; however, they also recommend that the risks and benefits of cfDNA should be discussed with all patients.8
STUDY SUMMARIES
CARE was a prospective, blinded, multicenter (21 US sites across 14 states) study that compared the aneuploidy detection rates of cfDNA to those of standard screening. Standard aneuploidy screening included assays of first- or second-trimester serum biomarkers with or without fetal nuchal translucency measurement.
This study enrolled 2042 pregnant patients ages 18 to 49 (mean: 29.6 years) with singleton pregnancies. The population was racially and ethnically diverse (65% white, 22% black, 11% Hispanic, 7% Asian). This study included women with diabetes mellitus, thyroid disorders, and other comorbidities. cfDNA testing was done on 1909 maternal blood samples for trisomy 21 and 1905 for trisomy 18.
cfDNA and standard aneuploidy screening results were compared to pregnancy outcomes. The presence of aneuploidy was determined by physician-documented newborn physical exam (97%) or karyotype analysis (3%). In both live and non-live births, the incidence of trisomy 21 was 5 of 1909 cases (0.3%) and the incidence of trisomy 18 was 2 of 1905 cases (0.1%).
The NPV of cfDNA in this study was 100% (95% confidence interval, 99.8%-100%) for both trisomy 21 and trisomy 18. The positive predictive value (PPV) was higher with cfDNA compared to standard screening (45.5% vs 4.2% for trisomy 21 and 40% vs 8.3% for trisomy 18). This means that approximately 1 in 25 women with a positive standard aneuploidy screen actually has aneuploidy. In contrast, nearly one in 2 women with a positive cfDNA result has aneuploidy.
Similarly, false positive rates with cfDNA were significantly lower than those with standard screening. For trisomy 21, the cfDNA false positive rate was 0.3% compared to 3.6% for standard screening (P<.001); for trisomy 18, the cfDNA false positive rate was 0.2% compared to 0.6% for standard screening (P=.03).
NEXT was a prospective, blinded cohort study that compared cfDNA testing with standard first-trimester screening (with measurements of nuchal translucency and serum biochemical analysis) in a routine prenatal population at 35 centers in 6 countries.
This study enrolled 18,955 women ages 18 to 48 (mean: 31 years) who underwent traditional first-trimester screening and cfDNA testing. Eligible patients included pregnant women with a singleton pregnancy with a gestational age between 10 and 14.3 weeks. Prenatal screening results were compared to newborn outcomes using a documented newborn physical examination and, if performed, results of genetic testing. For women who had a miscarriage or stillbirth or chose to terminate the pregnancy, outcomes were determined by diagnostic genetic testing.
The primary outcome was the area under the receiver-operating-characteristic (ROC) curve for trisomy 21. Area under the ROC curve is a measure of a diagnostic test’s accuracy that plots sensitivity against 1-specificity; <.700 is considered a poor test, whereas 1.00 is a perfect test. A secondary analysis evaluated cfDNA testing in low-risk women (ages <35 years).
The area under the ROC curve was 0.999 for cfDNA compared with 0.958 for standard screening (P=.001). For diagnosis of trisomy 21, cfDNA had a higher PPV than standard testing (80.9% vs 3.4%; P<.001) and a lower false positive rate (0.06% vs 5.4%; P<.001). These findings were consistent in the secondary analysis of low-risk women.
Both the CARE and NEXT trials also evaluated cfDNA testing vs standard screening for diagnosis of trisomy 13 and 18 and found higher PPVs and lower false positive rates for cfDNA compared with traditional screening.
WHAT'S NEW
Previously, cfDNA was recommended only for women with high-risk pregnancies. The new data demonstrate that cfDNA has substantially better PPVs and lower false positive rates than standard fetal aneuploidy screening for the general obstetrical population.
So while conventional screening tests remain the most appropriate methods for aneuploidy detection in the general obstetrical population, according to ACOG and SMFM, the 2 groups now recommend that all screening options—including cfDNA—be discussed with every woman. Any woman may choose cfDNA but should be counseled about the risks and benefits.8
CAVEATS
Both the CARE and NEXT studies had limitations. They compared cfDNA testing with first- or second-trimester screening and did not evaluate integrated screening methods (sequential first- and second-trimester biomarkers plus first-trimester nuchal translucency), which have a slightly higher sensitivity and specificity than first-trimester screening alone.
Multiple companies offer cfDNA, and the test is not subject to Food and Drug Administration approval. The CARE and NEXT studies used tests from companies that provided funding for these studies and employ several of the study authors.
Although cfDNA has increased specificity compared to standard screening, there have been case reports of false negative results. Further testing has shown that such false negative results could be caused by mosaicism in either the fetus and/or placenta, vanishing twins, or maternal malignancies.8-10
In the CARE and NEXT trials, cfDNA produced no results in 0.9% and 3% of women, respectively. Patients for whom cfDNA testing yields no results have higher rates of aneuploidy, and therefore require further diagnostic testing.
Because the prevalence of aneuploidy is lower in the general obstetric population than it is among women whose pregnancies are at high risk for aneuploidy, the PPV of cfDNA testing is also lower in the general obstetric population. This means that there are more false positive results for women at lower risk for aneuploidy. Therefore, it is imperative that women with positive cfDNA tests receive follow-up diagnostic testing such as chorionic villus sampling or amniocentesis before making a decision about termination.
All commercially available cfDNA tests have high sensitivity and specificity for trisomy 21, 18, and 13. Some offer testing for sex chromosome abnormalities and microdeletions. However, current cfDNA testing methods are unable to detect up to 17% of other clinically significant chromosomal abnormalities,11 and cfDNA cannot detect neural tube or ventral wall defects. Therefore, ACOG and SMFM recommend that women who choose cfDNA as their aneuploidy screening method should also be offered maternal serum alpha-fetoprotein or ultrasound evaluation.
CHALLENGES TO IMPLEMENTATION
cfDNA testing is validated only for singleton pregnancies. Physicians should obtain a baseline fetal ultrasound to confirm the number of fetuses, gestational age, and viability before ordering cfDNA to ensure it is the most appropriate screening test. This may add to the overall number of early pregnancy ultrasounds conducted.
Counseling patients about aneuploidy screening options is time-consuming, and requires discussion of the limitations of each screening method and caution that a negative cfDNA result does not guarantee an unaffected fetus, nor does a positive result guarantee an affected fetus. However, aneuploidy screening is well within the scope of care for family physicians who provide prenatal care, and referral to genetic specialists is not necessary or recommended.
Some patients may request cfDNA in order to facilitate earlier identification of fetal sex. In such cases, physicians should advise patients that cfDNA testing also assesses trisomy risk. Patients who do not wish to assess their risk for aneuploidy should not receive cfDNA testing.
Finally, while cfDNA is routinely recommended for women with pregnancies considered at high risk for aneuploidy, many insurance companies do not cover the cost of cfDNA for women with low-risk pregnancies, and the test may cost up to $1,700.12 The overall cost-effectiveness of cfDNA for aneuploidy screening in low-risk women is unknown.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
1. Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.
2. Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.
3. Chiu RW, Akolekar R, Zheng YW, et al. Non-invasive prenatal assessment of trisomy 21 by multiplexed maternal plasma DNA sequencing: large scale validity study. BMJ. 2011;342:c7401.
4. Ehrich M, Deciu C, Zwiefelhofer T, et al. Noninvasive detection of fetal trisomy 21 by sequencing of DNA in maternal blood: a study in a clinical setting. Am J Obstet Gynecol. 2011;204:205.e1-11.
5. Bianchi DW, Platt LD, Goldberg JD, et al; MatERNal BLood IS Source to Accurately diagnose fetal aneuploidy (MELISSA) Study Group. Genome-wide fetal aneuploidy detection by maternal plasma DNA sequencing. Obstet Gynecol. 2012;119:890-901.
6. Norton ME, Brar H, Weiss J, et al. Non-invasive chromosomal evaluation (NICE) study: results of a multicenter prospective cohort study for detection of fetal trisomy 21 and trisomy 18. Am J Obstet Gynecol. 2012;207:137.e1-8.
7. American College of Obstetricians and Gynecologists Committee on Genetics. Committee Opinion No. 545: Noninvasive prenatal testing for fetal aneuploidy. Obstet Gynecol. 2012;120:1532-1534.
8. Committee Opinion No. 640: Cell-Free DNA Screening For Fetal Aneuploidy. Obstet Gynecol. 2015;126:e31-37.
9. Wang Y, Zhu J, Chen Y, et al. Two cases of placental T21 mosaicism: challenging the detection limits of non-invasive prenatal testing. Prenat Diagn. 2013;33:1207-1210.
10. Choi H, Lau TK, Jiang FM, et al. Fetal aneuploidy screening by maternal plasma DNA sequencing: ‘false positive’ due to confined placental mosaicism. Prenat Diagn. 2013;33:198-200.
11. Norton ME, Jelliffe-Pawlowski LL, Currier RJ. Chromosome abnormalities detected by current prenatal screening and noninvasive prenatal testing. Obstet Gynecol. 2014;124:979-986.
12. Agarwal A, Sayres LC, Cho MK, et al. Commercial landscape of noninvasive prenatal testing in the United States. Prenat Diagn. 2013;33:521-531.
Discuss cell-free DNA testing when offering fetal aneuploidy screening to pregnant women.1,2
Strength of recommendation
A: Based on multiple large, multi-center cohort studies.
Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.1
Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.2
Illustrative case
A 28-year-old gravida 2, para 1001 at 10 weeks gestation presents to your clinic for a routine first-trimester prenatal visit. Her first child has no known chromosomal abnormalities and she has no family history of aneuploidy. She asks you which tests are available to screen her fetus for chromosomal abnormalities.
Pregnant women have traditionally been offered some combination of serum biomarkers and nuchal translucency to assess the risk of fetal aneuploidy. Cell-free DNA testing (cfDNA) is a form of noninvasive prenatal testing that uses maternal serum samples to conduct massively parallel sequencing of cell-free fetal DNA fragments. It has been offered to pregnant women as a screening test to detect fetal chromosomal abnormalities since 2011 after multiple clinical studies found high sensitivities, specificities, and negative predictive values (NPVs) for detecting aneuploidy.3-6 However until 2015, practice guidelines from the American Congress of Obstetricians and Gynecologists (ACOG) recommended that standard aneuploidy screening or diagnostic testing be offered to all pregnant women and cfDNA be reserved for women with pregnancies at high risk for aneuploidy (strength of recommendation: B).7
CARE (Comparison of Aneuploidy Risk Evaluation) and NEXT (Noninvasive Examination of Trisomy) are 2 large studies that compared cfDNA and standard aneuploidy screening methods in pregnant women at low risk for fetal aneuploidy. Based on new data from these and other studies, ACOG and the Society for Maternal-Fetal Medicine (SMFM) released a new consensus statement in June 2015 that addressed the use of cfDNA in the general obstetric population. The 2 groups still recommend conventional first- and second-trimester screening by serum chemical biomarkers and nuchal translucency as the first-line approach for low-risk women who want to pursue aneuploidy screening; however, they also recommend that the risks and benefits of cfDNA should be discussed with all patients.8
STUDY SUMMARIES
CARE was a prospective, blinded, multicenter (21 US sites across 14 states) study that compared the aneuploidy detection rates of cfDNA to those of standard screening. Standard aneuploidy screening included assays of first- or second-trimester serum biomarkers with or without fetal nuchal translucency measurement.
This study enrolled 2042 pregnant patients ages 18 to 49 (mean: 29.6 years) with singleton pregnancies. The population was racially and ethnically diverse (65% white, 22% black, 11% Hispanic, 7% Asian). This study included women with diabetes mellitus, thyroid disorders, and other comorbidities. cfDNA testing was done on 1909 maternal blood samples for trisomy 21 and 1905 for trisomy 18.
cfDNA and standard aneuploidy screening results were compared to pregnancy outcomes. The presence of aneuploidy was determined by physician-documented newborn physical exam (97%) or karyotype analysis (3%). In both live and non-live births, the incidence of trisomy 21 was 5 of 1909 cases (0.3%) and the incidence of trisomy 18 was 2 of 1905 cases (0.1%).
The NPV of cfDNA in this study was 100% (95% confidence interval, 99.8%-100%) for both trisomy 21 and trisomy 18. The positive predictive value (PPV) was higher with cfDNA compared to standard screening (45.5% vs 4.2% for trisomy 21 and 40% vs 8.3% for trisomy 18). This means that approximately 1 in 25 women with a positive standard aneuploidy screen actually has aneuploidy. In contrast, nearly one in 2 women with a positive cfDNA result has aneuploidy.
Similarly, false positive rates with cfDNA were significantly lower than those with standard screening. For trisomy 21, the cfDNA false positive rate was 0.3% compared to 3.6% for standard screening (P<.001); for trisomy 18, the cfDNA false positive rate was 0.2% compared to 0.6% for standard screening (P=.03).
NEXT was a prospective, blinded cohort study that compared cfDNA testing with standard first-trimester screening (with measurements of nuchal translucency and serum biochemical analysis) in a routine prenatal population at 35 centers in 6 countries.
This study enrolled 18,955 women ages 18 to 48 (mean: 31 years) who underwent traditional first-trimester screening and cfDNA testing. Eligible patients included pregnant women with a singleton pregnancy with a gestational age between 10 and 14.3 weeks. Prenatal screening results were compared to newborn outcomes using a documented newborn physical examination and, if performed, results of genetic testing. For women who had a miscarriage or stillbirth or chose to terminate the pregnancy, outcomes were determined by diagnostic genetic testing.
The primary outcome was the area under the receiver-operating-characteristic (ROC) curve for trisomy 21. Area under the ROC curve is a measure of a diagnostic test’s accuracy that plots sensitivity against 1-specificity; <.700 is considered a poor test, whereas 1.00 is a perfect test. A secondary analysis evaluated cfDNA testing in low-risk women (ages <35 years).
The area under the ROC curve was 0.999 for cfDNA compared with 0.958 for standard screening (P=.001). For diagnosis of trisomy 21, cfDNA had a higher PPV than standard testing (80.9% vs 3.4%; P<.001) and a lower false positive rate (0.06% vs 5.4%; P<.001). These findings were consistent in the secondary analysis of low-risk women.
Both the CARE and NEXT trials also evaluated cfDNA testing vs standard screening for diagnosis of trisomy 13 and 18 and found higher PPVs and lower false positive rates for cfDNA compared with traditional screening.
WHAT'S NEW
Previously, cfDNA was recommended only for women with high-risk pregnancies. The new data demonstrate that cfDNA has substantially better PPVs and lower false positive rates than standard fetal aneuploidy screening for the general obstetrical population.
So while conventional screening tests remain the most appropriate methods for aneuploidy detection in the general obstetrical population, according to ACOG and SMFM, the 2 groups now recommend that all screening options—including cfDNA—be discussed with every woman. Any woman may choose cfDNA but should be counseled about the risks and benefits.8
CAVEATS
Both the CARE and NEXT studies had limitations. They compared cfDNA testing with first- or second-trimester screening and did not evaluate integrated screening methods (sequential first- and second-trimester biomarkers plus first-trimester nuchal translucency), which have a slightly higher sensitivity and specificity than first-trimester screening alone.
Multiple companies offer cfDNA, and the test is not subject to Food and Drug Administration approval. The CARE and NEXT studies used tests from companies that provided funding for these studies and employ several of the study authors.
Although cfDNA has increased specificity compared to standard screening, there have been case reports of false negative results. Further testing has shown that such false negative results could be caused by mosaicism in either the fetus and/or placenta, vanishing twins, or maternal malignancies.8-10
In the CARE and NEXT trials, cfDNA produced no results in 0.9% and 3% of women, respectively. Patients for whom cfDNA testing yields no results have higher rates of aneuploidy, and therefore require further diagnostic testing.
Because the prevalence of aneuploidy is lower in the general obstetric population than it is among women whose pregnancies are at high risk for aneuploidy, the PPV of cfDNA testing is also lower in the general obstetric population. This means that there are more false positive results for women at lower risk for aneuploidy. Therefore, it is imperative that women with positive cfDNA tests receive follow-up diagnostic testing such as chorionic villus sampling or amniocentesis before making a decision about termination.
All commercially available cfDNA tests have high sensitivity and specificity for trisomy 21, 18, and 13. Some offer testing for sex chromosome abnormalities and microdeletions. However, current cfDNA testing methods are unable to detect up to 17% of other clinically significant chromosomal abnormalities,11 and cfDNA cannot detect neural tube or ventral wall defects. Therefore, ACOG and SMFM recommend that women who choose cfDNA as their aneuploidy screening method should also be offered maternal serum alpha-fetoprotein or ultrasound evaluation.
CHALLENGES TO IMPLEMENTATION
cfDNA testing is validated only for singleton pregnancies. Physicians should obtain a baseline fetal ultrasound to confirm the number of fetuses, gestational age, and viability before ordering cfDNA to ensure it is the most appropriate screening test. This may add to the overall number of early pregnancy ultrasounds conducted.
Counseling patients about aneuploidy screening options is time-consuming, and requires discussion of the limitations of each screening method and caution that a negative cfDNA result does not guarantee an unaffected fetus, nor does a positive result guarantee an affected fetus. However, aneuploidy screening is well within the scope of care for family physicians who provide prenatal care, and referral to genetic specialists is not necessary or recommended.
Some patients may request cfDNA in order to facilitate earlier identification of fetal sex. In such cases, physicians should advise patients that cfDNA testing also assesses trisomy risk. Patients who do not wish to assess their risk for aneuploidy should not receive cfDNA testing.
Finally, while cfDNA is routinely recommended for women with pregnancies considered at high risk for aneuploidy, many insurance companies do not cover the cost of cfDNA for women with low-risk pregnancies, and the test may cost up to $1,700.12 The overall cost-effectiveness of cfDNA for aneuploidy screening in low-risk women is unknown.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
Discuss cell-free DNA testing when offering fetal aneuploidy screening to pregnant women.1,2
Strength of recommendation
A: Based on multiple large, multi-center cohort studies.
Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.1
Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.2
Illustrative case
A 28-year-old gravida 2, para 1001 at 10 weeks gestation presents to your clinic for a routine first-trimester prenatal visit. Her first child has no known chromosomal abnormalities and she has no family history of aneuploidy. She asks you which tests are available to screen her fetus for chromosomal abnormalities.
Pregnant women have traditionally been offered some combination of serum biomarkers and nuchal translucency to assess the risk of fetal aneuploidy. Cell-free DNA testing (cfDNA) is a form of noninvasive prenatal testing that uses maternal serum samples to conduct massively parallel sequencing of cell-free fetal DNA fragments. It has been offered to pregnant women as a screening test to detect fetal chromosomal abnormalities since 2011 after multiple clinical studies found high sensitivities, specificities, and negative predictive values (NPVs) for detecting aneuploidy.3-6 However until 2015, practice guidelines from the American Congress of Obstetricians and Gynecologists (ACOG) recommended that standard aneuploidy screening or diagnostic testing be offered to all pregnant women and cfDNA be reserved for women with pregnancies at high risk for aneuploidy (strength of recommendation: B).7
CARE (Comparison of Aneuploidy Risk Evaluation) and NEXT (Noninvasive Examination of Trisomy) are 2 large studies that compared cfDNA and standard aneuploidy screening methods in pregnant women at low risk for fetal aneuploidy. Based on new data from these and other studies, ACOG and the Society for Maternal-Fetal Medicine (SMFM) released a new consensus statement in June 2015 that addressed the use of cfDNA in the general obstetric population. The 2 groups still recommend conventional first- and second-trimester screening by serum chemical biomarkers and nuchal translucency as the first-line approach for low-risk women who want to pursue aneuploidy screening; however, they also recommend that the risks and benefits of cfDNA should be discussed with all patients.8
STUDY SUMMARIES
CARE was a prospective, blinded, multicenter (21 US sites across 14 states) study that compared the aneuploidy detection rates of cfDNA to those of standard screening. Standard aneuploidy screening included assays of first- or second-trimester serum biomarkers with or without fetal nuchal translucency measurement.
This study enrolled 2042 pregnant patients ages 18 to 49 (mean: 29.6 years) with singleton pregnancies. The population was racially and ethnically diverse (65% white, 22% black, 11% Hispanic, 7% Asian). This study included women with diabetes mellitus, thyroid disorders, and other comorbidities. cfDNA testing was done on 1909 maternal blood samples for trisomy 21 and 1905 for trisomy 18.
cfDNA and standard aneuploidy screening results were compared to pregnancy outcomes. The presence of aneuploidy was determined by physician-documented newborn physical exam (97%) or karyotype analysis (3%). In both live and non-live births, the incidence of trisomy 21 was 5 of 1909 cases (0.3%) and the incidence of trisomy 18 was 2 of 1905 cases (0.1%).
The NPV of cfDNA in this study was 100% (95% confidence interval, 99.8%-100%) for both trisomy 21 and trisomy 18. The positive predictive value (PPV) was higher with cfDNA compared to standard screening (45.5% vs 4.2% for trisomy 21 and 40% vs 8.3% for trisomy 18). This means that approximately 1 in 25 women with a positive standard aneuploidy screen actually has aneuploidy. In contrast, nearly one in 2 women with a positive cfDNA result has aneuploidy.
Similarly, false positive rates with cfDNA were significantly lower than those with standard screening. For trisomy 21, the cfDNA false positive rate was 0.3% compared to 3.6% for standard screening (P<.001); for trisomy 18, the cfDNA false positive rate was 0.2% compared to 0.6% for standard screening (P=.03).
NEXT was a prospective, blinded cohort study that compared cfDNA testing with standard first-trimester screening (with measurements of nuchal translucency and serum biochemical analysis) in a routine prenatal population at 35 centers in 6 countries.
This study enrolled 18,955 women ages 18 to 48 (mean: 31 years) who underwent traditional first-trimester screening and cfDNA testing. Eligible patients included pregnant women with a singleton pregnancy with a gestational age between 10 and 14.3 weeks. Prenatal screening results were compared to newborn outcomes using a documented newborn physical examination and, if performed, results of genetic testing. For women who had a miscarriage or stillbirth or chose to terminate the pregnancy, outcomes were determined by diagnostic genetic testing.
The primary outcome was the area under the receiver-operating-characteristic (ROC) curve for trisomy 21. Area under the ROC curve is a measure of a diagnostic test’s accuracy that plots sensitivity against 1-specificity; <.700 is considered a poor test, whereas 1.00 is a perfect test. A secondary analysis evaluated cfDNA testing in low-risk women (ages <35 years).
The area under the ROC curve was 0.999 for cfDNA compared with 0.958 for standard screening (P=.001). For diagnosis of trisomy 21, cfDNA had a higher PPV than standard testing (80.9% vs 3.4%; P<.001) and a lower false positive rate (0.06% vs 5.4%; P<.001). These findings were consistent in the secondary analysis of low-risk women.
Both the CARE and NEXT trials also evaluated cfDNA testing vs standard screening for diagnosis of trisomy 13 and 18 and found higher PPVs and lower false positive rates for cfDNA compared with traditional screening.
WHAT'S NEW
Previously, cfDNA was recommended only for women with high-risk pregnancies. The new data demonstrate that cfDNA has substantially better PPVs and lower false positive rates than standard fetal aneuploidy screening for the general obstetrical population.
So while conventional screening tests remain the most appropriate methods for aneuploidy detection in the general obstetrical population, according to ACOG and SMFM, the 2 groups now recommend that all screening options—including cfDNA—be discussed with every woman. Any woman may choose cfDNA but should be counseled about the risks and benefits.8
CAVEATS
Both the CARE and NEXT studies had limitations. They compared cfDNA testing with first- or second-trimester screening and did not evaluate integrated screening methods (sequential first- and second-trimester biomarkers plus first-trimester nuchal translucency), which have a slightly higher sensitivity and specificity than first-trimester screening alone.
Multiple companies offer cfDNA, and the test is not subject to Food and Drug Administration approval. The CARE and NEXT studies used tests from companies that provided funding for these studies and employ several of the study authors.
Although cfDNA has increased specificity compared to standard screening, there have been case reports of false negative results. Further testing has shown that such false negative results could be caused by mosaicism in either the fetus and/or placenta, vanishing twins, or maternal malignancies.8-10
In the CARE and NEXT trials, cfDNA produced no results in 0.9% and 3% of women, respectively. Patients for whom cfDNA testing yields no results have higher rates of aneuploidy, and therefore require further diagnostic testing.
Because the prevalence of aneuploidy is lower in the general obstetric population than it is among women whose pregnancies are at high risk for aneuploidy, the PPV of cfDNA testing is also lower in the general obstetric population. This means that there are more false positive results for women at lower risk for aneuploidy. Therefore, it is imperative that women with positive cfDNA tests receive follow-up diagnostic testing such as chorionic villus sampling or amniocentesis before making a decision about termination.
All commercially available cfDNA tests have high sensitivity and specificity for trisomy 21, 18, and 13. Some offer testing for sex chromosome abnormalities and microdeletions. However, current cfDNA testing methods are unable to detect up to 17% of other clinically significant chromosomal abnormalities,11 and cfDNA cannot detect neural tube or ventral wall defects. Therefore, ACOG and SMFM recommend that women who choose cfDNA as their aneuploidy screening method should also be offered maternal serum alpha-fetoprotein or ultrasound evaluation.
CHALLENGES TO IMPLEMENTATION
cfDNA testing is validated only for singleton pregnancies. Physicians should obtain a baseline fetal ultrasound to confirm the number of fetuses, gestational age, and viability before ordering cfDNA to ensure it is the most appropriate screening test. This may add to the overall number of early pregnancy ultrasounds conducted.
Counseling patients about aneuploidy screening options is time-consuming, and requires discussion of the limitations of each screening method and caution that a negative cfDNA result does not guarantee an unaffected fetus, nor does a positive result guarantee an affected fetus. However, aneuploidy screening is well within the scope of care for family physicians who provide prenatal care, and referral to genetic specialists is not necessary or recommended.
Some patients may request cfDNA in order to facilitate earlier identification of fetal sex. In such cases, physicians should advise patients that cfDNA testing also assesses trisomy risk. Patients who do not wish to assess their risk for aneuploidy should not receive cfDNA testing.
Finally, while cfDNA is routinely recommended for women with pregnancies considered at high risk for aneuploidy, many insurance companies do not cover the cost of cfDNA for women with low-risk pregnancies, and the test may cost up to $1,700.12 The overall cost-effectiveness of cfDNA for aneuploidy screening in low-risk women is unknown.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
1. Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.
2. Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.
3. Chiu RW, Akolekar R, Zheng YW, et al. Non-invasive prenatal assessment of trisomy 21 by multiplexed maternal plasma DNA sequencing: large scale validity study. BMJ. 2011;342:c7401.
4. Ehrich M, Deciu C, Zwiefelhofer T, et al. Noninvasive detection of fetal trisomy 21 by sequencing of DNA in maternal blood: a study in a clinical setting. Am J Obstet Gynecol. 2011;204:205.e1-11.
5. Bianchi DW, Platt LD, Goldberg JD, et al; MatERNal BLood IS Source to Accurately diagnose fetal aneuploidy (MELISSA) Study Group. Genome-wide fetal aneuploidy detection by maternal plasma DNA sequencing. Obstet Gynecol. 2012;119:890-901.
6. Norton ME, Brar H, Weiss J, et al. Non-invasive chromosomal evaluation (NICE) study: results of a multicenter prospective cohort study for detection of fetal trisomy 21 and trisomy 18. Am J Obstet Gynecol. 2012;207:137.e1-8.
7. American College of Obstetricians and Gynecologists Committee on Genetics. Committee Opinion No. 545: Noninvasive prenatal testing for fetal aneuploidy. Obstet Gynecol. 2012;120:1532-1534.
8. Committee Opinion No. 640: Cell-Free DNA Screening For Fetal Aneuploidy. Obstet Gynecol. 2015;126:e31-37.
9. Wang Y, Zhu J, Chen Y, et al. Two cases of placental T21 mosaicism: challenging the detection limits of non-invasive prenatal testing. Prenat Diagn. 2013;33:1207-1210.
10. Choi H, Lau TK, Jiang FM, et al. Fetal aneuploidy screening by maternal plasma DNA sequencing: ‘false positive’ due to confined placental mosaicism. Prenat Diagn. 2013;33:198-200.
11. Norton ME, Jelliffe-Pawlowski LL, Currier RJ. Chromosome abnormalities detected by current prenatal screening and noninvasive prenatal testing. Obstet Gynecol. 2014;124:979-986.
12. Agarwal A, Sayres LC, Cho MK, et al. Commercial landscape of noninvasive prenatal testing in the United States. Prenat Diagn. 2013;33:521-531.
1. Bianchi DW, Parker RL, Wentworth J, et al; CARE Study Group. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370:799-808.
2. Norton ME, Jacobsson B, Swamy GK, et al. Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med. 2015;372:1589-1597.
3. Chiu RW, Akolekar R, Zheng YW, et al. Non-invasive prenatal assessment of trisomy 21 by multiplexed maternal plasma DNA sequencing: large scale validity study. BMJ. 2011;342:c7401.
4. Ehrich M, Deciu C, Zwiefelhofer T, et al. Noninvasive detection of fetal trisomy 21 by sequencing of DNA in maternal blood: a study in a clinical setting. Am J Obstet Gynecol. 2011;204:205.e1-11.
5. Bianchi DW, Platt LD, Goldberg JD, et al; MatERNal BLood IS Source to Accurately diagnose fetal aneuploidy (MELISSA) Study Group. Genome-wide fetal aneuploidy detection by maternal plasma DNA sequencing. Obstet Gynecol. 2012;119:890-901.
6. Norton ME, Brar H, Weiss J, et al. Non-invasive chromosomal evaluation (NICE) study: results of a multicenter prospective cohort study for detection of fetal trisomy 21 and trisomy 18. Am J Obstet Gynecol. 2012;207:137.e1-8.
7. American College of Obstetricians and Gynecologists Committee on Genetics. Committee Opinion No. 545: Noninvasive prenatal testing for fetal aneuploidy. Obstet Gynecol. 2012;120:1532-1534.
8. Committee Opinion No. 640: Cell-Free DNA Screening For Fetal Aneuploidy. Obstet Gynecol. 2015;126:e31-37.
9. Wang Y, Zhu J, Chen Y, et al. Two cases of placental T21 mosaicism: challenging the detection limits of non-invasive prenatal testing. Prenat Diagn. 2013;33:1207-1210.
10. Choi H, Lau TK, Jiang FM, et al. Fetal aneuploidy screening by maternal plasma DNA sequencing: ‘false positive’ due to confined placental mosaicism. Prenat Diagn. 2013;33:198-200.
11. Norton ME, Jelliffe-Pawlowski LL, Currier RJ. Chromosome abnormalities detected by current prenatal screening and noninvasive prenatal testing. Obstet Gynecol. 2014;124:979-986.
12. Agarwal A, Sayres LC, Cho MK, et al. Commercial landscape of noninvasive prenatal testing in the United States. Prenat Diagn. 2013;33:521-531.
Copyright © 2016. The Family Physicians Inquiries Network. All rights reserved.
Holiday Trip Marred by Illness
ANSWER
This ECG is representative of marked sinus bradycardia with second-degree atrioventricular block (Mobitz I) with an occasional junctional escape, left-axis deviation, and poor R-wave progression in the precordial leads.
Marked sinus bradycardia is evidenced by P waves that are regular except where expected, prior to the third QRS complex on the rhythm strip (lead 1).
Second-degree Mobitz I (Wenckebach) block is indicated by a gradual prolonging of the PR interval until there is loss of conduction from the atria to the ventricle (following the third P wave). Careful inspection of the third QRS complex shows a slight difference in the normally conducted sinus beat, indicative of a junctional escape beat. Left-axis deviation entails an R-wave axis of –78°.
Finally, there is poor R-wave progression in the precordial leads, including the lateral leads.
Although Mobitz I block is not an indication for pacemaker placement, symptomatic bradycardia is. The patient underwent implantation of a dual-chamber permanent pacemaker, with complete resolution of symptoms.
ANSWER
This ECG is representative of marked sinus bradycardia with second-degree atrioventricular block (Mobitz I) with an occasional junctional escape, left-axis deviation, and poor R-wave progression in the precordial leads.
Marked sinus bradycardia is evidenced by P waves that are regular except where expected, prior to the third QRS complex on the rhythm strip (lead 1).
Second-degree Mobitz I (Wenckebach) block is indicated by a gradual prolonging of the PR interval until there is loss of conduction from the atria to the ventricle (following the third P wave). Careful inspection of the third QRS complex shows a slight difference in the normally conducted sinus beat, indicative of a junctional escape beat. Left-axis deviation entails an R-wave axis of –78°.
Finally, there is poor R-wave progression in the precordial leads, including the lateral leads.
Although Mobitz I block is not an indication for pacemaker placement, symptomatic bradycardia is. The patient underwent implantation of a dual-chamber permanent pacemaker, with complete resolution of symptoms.
ANSWER
This ECG is representative of marked sinus bradycardia with second-degree atrioventricular block (Mobitz I) with an occasional junctional escape, left-axis deviation, and poor R-wave progression in the precordial leads.
Marked sinus bradycardia is evidenced by P waves that are regular except where expected, prior to the third QRS complex on the rhythm strip (lead 1).
Second-degree Mobitz I (Wenckebach) block is indicated by a gradual prolonging of the PR interval until there is loss of conduction from the atria to the ventricle (following the third P wave). Careful inspection of the third QRS complex shows a slight difference in the normally conducted sinus beat, indicative of a junctional escape beat. Left-axis deviation entails an R-wave axis of –78°.
Finally, there is poor R-wave progression in the precordial leads, including the lateral leads.
Although Mobitz I block is not an indication for pacemaker placement, symptomatic bradycardia is. The patient underwent implantation of a dual-chamber permanent pacemaker, with complete resolution of symptoms.
While visiting family over the holidays, an 84-year-old man is (plaintively) informed by his wife that he appears unwell; she suspects he has the flu. The patient’s son, whom they are visiting, learns through conversation that his father has been feeling very tired and lethargic and becomes dizzy if he stands too quickly. The son, concerned for his father’s well-being, brings him to your clinic in the hope of obtaining a prescription for antibiotics. According to the patient, his symptoms, which have waxed and waned for several weeks, have become constant in the past week. He denies fever, cough, nausea, and vomiting, as well as chest pain, shortness of breath, palpitations, and lower extremity swelling. He reports that he has not recently changed his medication regimen and, aside from this current visit, has not traveled anywhere; he reiterates that his symptoms started prior to this trip. Medical history is remarkable for hypertension, peripheral atherosclerosis, osteoarthritis, gout, and pneumonia. Surgical history is remarkable for appendectomy, cholecystectomy, and removal of multiple lipomas from the patient’s upper extremities. Via the family history, you learn that the man’s father had a myocardial infarction and died of complications from a stroke at age 92 and his mother died of complications of diabetes at age 87. The patient is married, with three sons and one daughter, all of whom are in good health. He is a retired owner of a hardware store. He has never smoked or used recreational drugs and says he rarely drinks alcohol. The patient’s medication list includes metoprolol, atorvastatin, furosemide, and a daily baby aspirin. He is allergic to sulfa, which causes shortness of breath and wheezing. Review of systems reveals that he wears corrective lenses and hearing aids. He walks with a cane due to pain in both knees but is not dependent on it. He denies constitutional symptoms. A review of cardiovascular, respiratory, gastrointestinal, urologic, neurologic, and integumentary systems is noncontributory. Chest x-ray and laboratory testing, including complete blood count and chemistry panel, yield normal results. Vital signs include a blood pressure of 162/92 mm Hg; pulse, 40 beats/min; respiratory rate, 14 breaths/min; temperature, 99.2°F; and O2 saturation, 97% on room air. Pertinent physical findings include clear lung fields bilaterally, no evidence of jugular venous distention, and a heart rate of 40 beats/min that is regular and without evidence of a murmur or rub. There are well-healed scars on the abdomen and no evidence of organomegaly. Peripheral pulses are diminished but present bilaterally in both lower extremities. The neurologic exam is grossly intact, and the patient is alert, cooperative, and cognizant. Your concern about the patient’s heart rate prompts you to order an ECG. It reveals a ventricular rate of 38 beats/min; no measurable PR interval; QRS duration, 78 ms; QT/QTc interval, 434/345 ms; P axis, 25°; R axis, –78°; and T axis, 13°. What is your interpretation of this ECG?
HIV prevention: A 3-pronged approach
› Screen all pregnant women and individuals ages 15 to 65 for human immunodeficiency virus (HIV) infection. A
› Prescribe tenofovir disoproxil fumarate/emtricitabine (Truvada) for pre-exposure prophylaxis for patients at high risk of acquiring HIV. A
› Offer needle and syringe exchange programs and, when appropriate, opioid substitution therapy to individuals who inject drugs. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
Despite advances in human immunodeficiency virus (HIV) screening and treatment over the last 30 years, HIV remains a public health concern. In the United States, after an initial decline, total HIV incidence has failed to significantly decrease in the last 25 years. More than 1.2 million people are living with HIV in the United States, and 12.8% of them (156,300) are unaware they are affected.1 Of those diagnosed with HIV, only 30% are receiving treatment and are virally suppressed.2 Due to structural inequalities and psychosocial factors, African American and Latino patients remain disproportionately affected.3 The incidence of HIV infection among men who have sex with men has increased, and the incidence of HIV infection among people who inject drugs has plateaued after years of progressive decline.4
HIV prevention strategies are highly effective, but in general are underutilized. This article reviews 3 prevention strategies that can be administered by family physicians: HIV screening, pre-exposure prophylaxis (PrEP), and harm reduction.
Who and how to screen for HIV
Early identification of HIV infection generally leads to reduced transmission because diagnosis is associated with decreases in risky behavior.5,6 In addition, antiretroviral therapy (ART) is more effective when initiated early, before the development of advanced immunosuppression.7-9
The “window period” of acute HIV infection (AHI) is the time from when the virus is transmitted to when markers of infection can be detected. Because this window period is associated with high viral transmission rates, family physicians must be familiar with symptoms of AHI (TABLE 1)10,11 and associated risk factors (eg, recent condomless sex or sharing of drug injection equipment with someone who is HIV-positive or of unknown HIV status).
Screening for HIV solely based on the presence of risk factors or clinical symptoms is not enough, however. The United States Preventive Services Task Force (USPSTF) recommends screening all pregnant women and individuals ages 15 to 65 for HIV.12 Screening based solely on risk factors or clinical symptoms frequently leads to missed diagnoses and identification of HIV infection at more advanced stages.13,14 Both the USPSTF and the Centers for Disease Control and Prevention (CDC) recommend universal opt-out screening (patients are informed that HIV screening will be performed and that they may decline testing) because such screening identifies HIV earlier and is associated with higher testing rates than opt-in screening, which requires explicit written consent and extensive pre-test counseling.
Which test to use. HIV screening with a fourth-generation antigen/antibody combination immunoassay—which detects both HIV p24 antigen and HIV antibodies—provides greater diagnostic accuracy than older tests.15 These newer tests detect HIV approximately 15 days after initial infection, reducing the window period of AHI.15,16 If you suspect a patient has AHI, consider early repeat HIV testing with a fourth-generation assay, or initial co-testing with a fourth-generation assay and a nucleic acid amplification test for HIV RNA, which makes it possible to detect infection approximately 5 days earlier than fourth-generation assays.15
Offer pre-exposure prophylaxis to high-risk patients
PrEP is the use of ART prior to HIV exposure to prevent transmission of the virus. It should be used with conventional risk reduction strategies, such as providing condoms, counseling patients about reducing risky behaviors, supporting medication adherence, and screening for and treating other sexually transmitted infections.
The US Food and Drug Administration (FDA) has approved only one medication, Truvada (tenofovir disoproxil fumarate/emtricitabine; TDF/FTC), for use as PrEP. Oral tenofovir-based regimens can effectively prevent HIV transmission,17-20 and strong adherence is associated with a risk reduction of 90% to 100%.17-23 The protective effect of oral PrEP is particularly strong in high-risk populations (eg, men who have sex with men, people who inject drugs), where the number needed to treat to prevent one HIV infection ranges from 12 to 100, depending on the patients’ risk profile.24-26 The CDC and Department of Health and Human Services have issued guidelines for using PrEP in high-risk patients.27
Barriers to implementing PrEP. Despite being highly effective, PrEP is not routinely prescribed to high-risk patients; modeling suggests that current use of PrEP is insufficient to significantly impact the incidence of HIV.28 Demand for PrEP is high among target groups,21,29,30 but patients have expressed concerns about adverse effects31 and stigma related to ART, HIV, and being at risk for HIV.32,33 Young age, lack of social support, low perception of risk, and failure to show up for appointments are also barriers to PrEP use.28,30,34
Some physicians have expressed concern that prescribing PrEP may promote high-risk sexual behavior.35 However, because PrEP is most beneficial in individuals who already engage in high-risk sexual behavior, strategic delivery of PrEP remains an effective risk-reducing strategy.17,18,21,26,36,37 Even in instances where PrEP has been associated with higher-risk sexual behavior and higher rates of sexually transmitted infections, it still prevents as much as 100% of new HIV infections.38
Fear of drug resistance also contributes to slow implementation of PrEP. Drug resistance has been observed in clinical trials of PrEP, but it has been exceedingly rare and predominantly limited to patients who had unrecognized AHI when they started PrEP.39 Furthermore, the few cases of drug resistance attributable to PrEP pale in comparison to the large number of estimated HIV infections averted—infections that would require lifelong ART with its own associated risks of drug resistance. By decreasing HIV transmission, PrEP is expected to decrease total drug resistance.40
Cost is another obstacle. Truvada costs approximately $1,540 per month.41 However, analysis has demonstrated that PrEP is cost-effective when targeted to high-risk patients.42 Most insurance plans cover PrEP, but often require high deductibles and copays; fortunately, this financial burden for patients can be mitigated or eliminated by co-pay assistance programs. The manufacturer of Truvada offers assistance programs for both insured and uninsured patients who are candidates for PrEP; details are available at http://www.truvada.com/truvada-patient-assistance.
Stigma has historically burdened individuals who seek to protect their sexual health, including HIV-negative individuals who are candidates for PrEP. Stigma surrounding HIV may decrease ART-based HIV prevention in men who have sex with men,43 while increasing high-risk behaviors44 and all-cause mortality.45
The resources listed in TABLE 2 can help physicians overcome some of the barriers to implementing PrEP.
How to deliver PrEP
Whether HIV specialists or primary care clinicians are best suited to provide PrEP is a subject of debate. HIV specialists are most familiar with ART and routine monitoring of adherence; however, they have less access to HIV-negative patients, who are the target group for PrEP.35 Family physicians tend to work in closer proximity and maintain longitudinal relationships with PrEP target groups, but in general have less experience with ART and evaluating AHI. Some may argue that competing demands may make it impractical to take a detailed sexual history during a primary care visit.46 In truth, both HIV specialists and family physicians can be appropriately equipped to provide PrEP.
TABLE 3 outlines the steps necessary to provide a patient with PrEP.47 Assessing risk is the initial step; PrEP is beneficial for patients who have one or more risk factors for HIV infection. To be eligible for TDF/FTC, a patient must be HIV-negative, and should be tested for hepatitis B virus (HBV) infection and kidney disease. Because TDF/FTC treats HBV infection, candidates for PrEP who test positive for HBV should be evaluated for treatment of HBV before initiating PrEP. Candidates for PrEP who test negative for HBV infection and immunity should be vaccinated.
Candidates for PrEP should also be screened and monitored for kidney disease. TDF can cause increased serum creatinine due to tubular toxicity. A patient who has an estimated creatinine clearance <60 mL/min should not receive TDF/FTC for PrEP. If a patient’s estimated creatinine clearance falls below 60 mL/min or serum creatinine increases by 0.3 mg/dL above baseline after PrEP is started, TDF/FTC should be discontinued, and the patient should be evaluated for the underlying cause of the kidney disease.27
Before starting PrEP, candidates should be screened for HIV infection and symptoms of AHI. Strongly consider testing for sexually transmitted infections that may increase the risk of HIV transmission, such as syphilis, gonorrhea, or chlamydia.
Candidates who are eligible for PrEP must be counseled on medication adverse effects, adherence strategies, and symptoms of sexually transmitted infections. To initiate PrEP, candidates may be given a one-month supply of TDF/FTC; adherence, adverse effects, and other risk-reduction strategies are assessed at an office visit 3 to 4 weeks later. Subsequent prescriptions are then dispensed as a 3-month supply, with office visits to monitor PrEP scheduled for at least once every 3 months. During these monitoring visits, evaluate the patient’s HIV status, pregnancy status, adherence, adverse effects, risk-reduction behaviors, and indications for continued PrEP. Every 6 months, renal function and sexually transmitted infection status should be reassessed.
Reducing risk of harm among patients who inject drugs
Nonsexual transmission of HIV is a route of high infectivity.48 It includes transfusion of infected blood, sharing of equipment during injection drug use, and percutaneous needle sticks. Sharing of equipment during injection drug use is estimated to account for 8% of new infections in the United States.4
Harm reduction is a collection of strategies meant to reduce complications of illicit drug use, including HIV transmission. These strategies include needle and syringe programs that provide injection drug users with sterile equipment, and opioid substitution therapy.
Needle and syringe programs decrease HIV transmission49 and risky behaviors related to injection drug use,50 but federal funding of such programs is prohibited. Opioid substitution therapy reduces the incidence of HIV,50,51 injection drug use, sharing of drug preparation and injection equipment, and drug-related behaviors associated with a high risk of HIV transmission.50,52 However, in the United States, the quality of these programs varies; a study of opioid substitution therapy delivery found that 22.8% of programs provided doses that were too low to be effective.53
FDA-approved medications for opioid substitution therapy include sublingual buprenorphine, sublingual buprenorphine/naloxone tablets or strips (Suboxone), and oral methadone. Buprenorphine-based regimens can be provided by appropriately trained primary care clinicians; methadone requires a referral to a narcotic treatment program. TABLE 4 provides training and support resources for physicians who want to integrate opioid substitution therapy into their clinical practice.
CORRESPONDENCE
Richard Moore II, MD, 250 Smith Church Road, Roanoke Rapids, NC 27870; [email protected].
1. Hall HI, An Q, Tang T, et al; Centers for Disease Control and Prevention (CDC). Prevalence of diagnosed and undiagnosed HIV infection--United States, 2008-2012. MMWR Morb Mortal Wkly Rep. 2015;64:657-662.
2. Bradley H, Hall HI, Wolitski RJ, et al. Vital signs: HIV diagnosis, care, and treatment among persons living with HIV--United States, 2011. MMWR Morb Mortal Wkly Rep. 2014;63:1113-1117.
3. Maulsby C, Millet G, Lindsey K, et al. HIV among black men who have sex with men (MSM) in the United States: a review of the literature. AIDS Behav. 2014;18:10-25.
4. Centers for Disease Control and Prevention. Estimated HIV incidence among adults and adolescents in the United States, 2007-2010, HIV Surveillance Supplemental Report. 2012. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/statistics_hssr_vol_17_no_4.pdf. Accessed October 8, 2015.
5. Cleary PD, Van Devanter N, Rogers TF, et al. Behavior changes after notification of HIV infection. Am J Public Health. 1991;81:1586-1590.
6. Higgins DL, Galavotti C, O’Reilly KR, et al. Evidence for the effects of HIV antibody counseling and testing on risk behaviors. JAMA. 1991;266:2419-2429.
7. Murphy EL, Collier AC, Kalish LA, et al. Highly active antiretroviral therapy decreases mortality and morbidity in patients with advanced HIV disease. Ann Intern Med. 2001;135:17-26.
8. Palella FJ Jr, Deloria-Knoll M, Chmiel JS, et al. Survival benefit of initiating antiretroviral therapy in HIV-infected persons in different CD4 cell strata. Ann Intern Med. 2003;138:620-626.
9. INSIGHT START Study Group, Lundgren JD, Babiker AG, Gordin F, et al. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med. 2015;373:795-807.
10. Daar ES, Pilcher CD, Hecht FM. Clinical presentation and diagnosis of primary HIV-1 infection. Curr Opin HIV AIDS. 2008;3:10-15.
11. Tindall B, Barker S, Donovan B, et al. Characterization of the acute clinical illness associated with human immunodeficiency virus infection. Arch Intern Med. 1988;148:945-949.
12. Moyer V, US Preventative Services Task Force. Screening for HIV: US Preventive Services Task Force recommendation statement. Ann Intern Med. 2013;159:51-60.
13. Jenkins T, Gardner E, Thrun M, et al. Risk-based HIV testing fails to detect the majority of HIV-infected persons in medical care settings. Sex Transm Dis. 2006;33:329-333.
14. Klein D, Hurley LB, Merrill D, et al. Review of medical encounters in the 5 years before a diagnosis of HIV-1 infection: implications for early detection. J Acquir Immune Defic Syndr. 2003;32:143-152.
15. Pandori M, Hackett J Jr, Louie B, et al. Assessment of the ability of a fourth-generation immunoassay for human immunodeficiency virus (HIV) antibody and p24 antigen to detect both acute and recent HIV infections in a high-risk setting. J Clin Microbiol. 2009;47:2639-2642.
16. Branson BM. The future of HIV testing. J Acquir Imm Defic Syndr. 2010;55 Suppl 2:S102-S105.
17. Grant RM, Lama JR, Anderson PL, et al; iPrEx Study Team. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587-2599.
18. Baeten JM, Donnell D, Ndase P, et al; Partners PrEP Study Team. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367:399-410.
19. Thigpen MC, Kebaabetswe PM, Paxton LA, et al. Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in Botswana. N Engl J Med. 2012;367:423-434.
20. Choopanya K, Martin M, Suntharasamai P, et al. Antiretroviral prophylaxis for HIV infection in injecting drug users in Bangkok, Thailand (the Bangkok Tenofovir Study): a randomised, doubleblind, placebo-controlled phase 3 trial. Lancet. 2013;381:2083-2090.
21. Grant RM, Anderson PL, McMahan V, et al. Uptake of pre-exposure prophylaxis, sexual practices, and HIV incidence in men and transgender women who have sex with men: a cohort study. Lancet Infect Dis. 2014;14:820-829.
22. Anderson PL, Glidden DV, Liu A, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4:151ra125.
23. Henderson FL, Taylor AW, Chirwa LI, et al. Characteristics and oral PrEP adherence in the TDF2 open-label extension in Botswana. Paper presented at International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention; July 1922, 2015; Vancouver, Canada.
24. Murnane PM, Celum C, Mugo N, et al. Efficacy of preexposure prophylaxis for HIV-1 prevention among high-risk heterosexuals: subgroup analyses from a randomized trial. AIDS. 2013;27:2155-2160.
25. Heffron R, Mugo N, Were E, et al. Preexposure prophylaxis is efficacious for HIV-1 prevention among women using depot medroxyprogesterone acetate for contraception. AIDS. 2014;28:2771-2776.
26. Buchbinder SP, Glidden DV, Liu AY, et al. HIV pre-exposure prophylaxis in men who have sex with men and transgender women: a secondary analysis of a phase 3 randomised controlled efficacy trial. Lancet Infect Dis. 2014;14:468-475.
27. Center for Disease Control and Prevention. Preexposure prophylaxis for the prevention of HIV infection in the United States – 2014. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/PrEPguidelines2014.pdf. Accessed June 18, 2015.
28. Grant RM. Scale-up of preexposure prophylaxis in San Francisco to impact HIV incidence. Abstract 25. Paper presented at Conference on Retroviruses and Opportunistic Infections; February 23-26, 2015; Seattle, WA.
29. Cohen SE, Vittinghoff E, Bacon O, et al. High interest in preexposure prophylaxis among men who have sex with men at risk for HIV infection: baseline data from the US PrEP demonstration project. J Acquir Immune Defic Syndr. 2015;68:439-448.
30. Haberer JE, Baeten JM, Campbell J, et al. Adherence to antiretroviral prophylaxis for HIV prevention: a substudy cohort within a clinical trial of serodiscordant couples in East Africa. PLoS Med. 2013;10:e1001511.
31. Gilmore H, Koester K, Liu A, et al. To PrEP or not to PrEP: Perspectives from US iPrEx open label extension (OLE) participants. Abstract 440. Paper presented at 9th International Conference on HIV Treatment and Prevention Adherence; June 9, 2014; Miami Beach, FL.
32. Jain S, Gregor C, Krakower D, et al. Attitudes and interest toward HIV pre-exposure prophylaxis (PrEP) among participants using HIV non-occupational post-exposure prophylaxis (NPEP). Poster Abstract 1523. Poster presented at Infectious Disease Society of America Conference; October 8-12, 2014; Philadelphia, PA.
33. van der Straten A, Stadler J, Luecke E, et al; VOICE-C Study Team, Perspectives on use of oral and vaginal antiretrovirals for HIV prevention: the VOICE-C qualitative study in Johannesburg, South Africa. J Int AIDS Soc. 2014;17:19146.
34. Corneli AL, McKenna K, Headley J, et al; FEM-PrEP Study Group. A descriptive analysis of perceptions of HIV risk and worry about acquiring HIV among FEM-PrEP participants who seroconverted in Bondo, Kenya, and Pretoria, South Africa. J Int AIDS Soc. 2014;17:19152.
35. Krakower D, Ware N, Mitty JA, et al. HIV providers’ perceived barriers and facilitators to implementing pre-exposure prophylaxis in care settings: a qualitative study. AIDS Behav. 2014;18:1712-1721.
36. McCormack S, Dunn DT, Desai M, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2015. [Epub ahead of print].
37. Mugwanya KK, Donnell D, Celum C, et al. Sexual behaviour of heterosexual men and women receiving antiretroviral pre-exposure prophylaxis for HIV prevention: a longitudinal analysis. Lancet Infect Dis. 2013;13:1021-1028.
38. Volk JE, Marcus JL, Phengrasamy T, et al. No new HIV infections with increasing use of HIV preexposure prophylaxis in a clinical practice setting. Clin Infect Dis. 2015;61:1601-1603.
39. Lehman DA, Baeten JM, McCoy CO, et al. Risk of drug resistance among persons acquiring HIV within a randomized clinical trial of single- or dual-agent preexposure prophylaxis. J Infect Dis. 2015;211:1211-1218.
40. Supervie V, Garcia-Lerma JG, Heneine W, et al. HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis. Proc Natl Acad Sci U S A. 2010;107:12381-12386.
41. AIDSinfo. Cost considerations and antiretroviral therapy. AIDSinfo Web site. Available at: https://aidsinfo.nih.gov/guidelines/html/1/adult-and-adolescent-arv-guidelines/459/cost-considerations-and-antiretroviral-therapy. Accessed December 14, 2015.
42. Gomez GB, Borquez A, Case KK, et al. The cost and impact of scaling up pre-exposure prophylaxis for HIV prevention: a systematic review of cost-effectiveness modelling studies. PLoS Med. 2013;10:e1001401.
43. Oldenburg CE, Perez-Brumer AG, Hatzenbuehler ML, et al. State-level structural sexual stigma and HIV prevention in a national online sample of HIV-uninfected MSM in the United States. AIDS. 2015;29:837-845.
44. Hatzenbuehler ML, O’Cleirigh C, Mayer KH, et al. Prospective associations between HIV-related stigma, transmission risk behaviors, and adverse mental health outcomes in men who have sex with men. Ann Behav Med. 2011;42:227-234.
45. Hatzenbuehler ML, Bellatorre A, Lee Y, et al. Structural stigma and all-cause mortality in sexual minority populations. Soc Sci Med. 2014;103:33-41.
46. Arnold EA, Hazelton P, Lane T, et al. A qualitative study of provider thoughts on implementing pre-exposure prophylaxis (PrEP) in clinical settings to prevent HIV infection. PLoS One. 2012;7:e40603.
47. North Carolina AIDS Training and Education Center. For PrEP Providers. North Carolina AIDS Training and Education Center Web site. Available at: http://www.med.unc.edu/ncaidstraining/prep/for-providers/for-prep-prescribers. Accessed July 7, 2015.
48. Patel P, Borkowf CB, Brook JT, et al. Estimating per-act HIV transmission risk: a systematic review. AIDS. 2014;28:1509-1519.
49. Aspinall EJ, Nambiar D, Goldberg DJ, et al. Are needle and syringe programmes associated with a reduction in HIV transmission among people who inject drugs: a systematic review and metaanalysis. Int J Epidemiol. 2014;43:235-248.
50. MacArthur GJ, van Velzen E, Palmateer N, et al. Interventions to prevent HIV and Hepatitis C in people who inject drugs: a review of reviews to assess evidence of effectiveness. Int J Drug Policy. 2014;25:34-52.
51. MacArthur GJ, Minozzi S, Martin N, et al. Opiate substitution treatment and HIV transmission in people who inject drugs: systematic review and meta-analysis. BMJ. 2012;345:e5945.
52. Gowing L, Farrell MF, Bornemann R, et al. Oral substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev. 2011;(8):CD004145.
53. D’Aunno T, Pollack HA, Frimpong JA, et al. Evidence-based treatment for opioid disorders: a 23-year national study of methadone dose levels. J Subst Abuse Treat. 2014;47:245-250.
› Screen all pregnant women and individuals ages 15 to 65 for human immunodeficiency virus (HIV) infection. A
› Prescribe tenofovir disoproxil fumarate/emtricitabine (Truvada) for pre-exposure prophylaxis for patients at high risk of acquiring HIV. A
› Offer needle and syringe exchange programs and, when appropriate, opioid substitution therapy to individuals who inject drugs. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
Despite advances in human immunodeficiency virus (HIV) screening and treatment over the last 30 years, HIV remains a public health concern. In the United States, after an initial decline, total HIV incidence has failed to significantly decrease in the last 25 years. More than 1.2 million people are living with HIV in the United States, and 12.8% of them (156,300) are unaware they are affected.1 Of those diagnosed with HIV, only 30% are receiving treatment and are virally suppressed.2 Due to structural inequalities and psychosocial factors, African American and Latino patients remain disproportionately affected.3 The incidence of HIV infection among men who have sex with men has increased, and the incidence of HIV infection among people who inject drugs has plateaued after years of progressive decline.4
HIV prevention strategies are highly effective, but in general are underutilized. This article reviews 3 prevention strategies that can be administered by family physicians: HIV screening, pre-exposure prophylaxis (PrEP), and harm reduction.
Who and how to screen for HIV
Early identification of HIV infection generally leads to reduced transmission because diagnosis is associated with decreases in risky behavior.5,6 In addition, antiretroviral therapy (ART) is more effective when initiated early, before the development of advanced immunosuppression.7-9
The “window period” of acute HIV infection (AHI) is the time from when the virus is transmitted to when markers of infection can be detected. Because this window period is associated with high viral transmission rates, family physicians must be familiar with symptoms of AHI (TABLE 1)10,11 and associated risk factors (eg, recent condomless sex or sharing of drug injection equipment with someone who is HIV-positive or of unknown HIV status).
Screening for HIV solely based on the presence of risk factors or clinical symptoms is not enough, however. The United States Preventive Services Task Force (USPSTF) recommends screening all pregnant women and individuals ages 15 to 65 for HIV.12 Screening based solely on risk factors or clinical symptoms frequently leads to missed diagnoses and identification of HIV infection at more advanced stages.13,14 Both the USPSTF and the Centers for Disease Control and Prevention (CDC) recommend universal opt-out screening (patients are informed that HIV screening will be performed and that they may decline testing) because such screening identifies HIV earlier and is associated with higher testing rates than opt-in screening, which requires explicit written consent and extensive pre-test counseling.
Which test to use. HIV screening with a fourth-generation antigen/antibody combination immunoassay—which detects both HIV p24 antigen and HIV antibodies—provides greater diagnostic accuracy than older tests.15 These newer tests detect HIV approximately 15 days after initial infection, reducing the window period of AHI.15,16 If you suspect a patient has AHI, consider early repeat HIV testing with a fourth-generation assay, or initial co-testing with a fourth-generation assay and a nucleic acid amplification test for HIV RNA, which makes it possible to detect infection approximately 5 days earlier than fourth-generation assays.15
Offer pre-exposure prophylaxis to high-risk patients
PrEP is the use of ART prior to HIV exposure to prevent transmission of the virus. It should be used with conventional risk reduction strategies, such as providing condoms, counseling patients about reducing risky behaviors, supporting medication adherence, and screening for and treating other sexually transmitted infections.
The US Food and Drug Administration (FDA) has approved only one medication, Truvada (tenofovir disoproxil fumarate/emtricitabine; TDF/FTC), for use as PrEP. Oral tenofovir-based regimens can effectively prevent HIV transmission,17-20 and strong adherence is associated with a risk reduction of 90% to 100%.17-23 The protective effect of oral PrEP is particularly strong in high-risk populations (eg, men who have sex with men, people who inject drugs), where the number needed to treat to prevent one HIV infection ranges from 12 to 100, depending on the patients’ risk profile.24-26 The CDC and Department of Health and Human Services have issued guidelines for using PrEP in high-risk patients.27
Barriers to implementing PrEP. Despite being highly effective, PrEP is not routinely prescribed to high-risk patients; modeling suggests that current use of PrEP is insufficient to significantly impact the incidence of HIV.28 Demand for PrEP is high among target groups,21,29,30 but patients have expressed concerns about adverse effects31 and stigma related to ART, HIV, and being at risk for HIV.32,33 Young age, lack of social support, low perception of risk, and failure to show up for appointments are also barriers to PrEP use.28,30,34
Some physicians have expressed concern that prescribing PrEP may promote high-risk sexual behavior.35 However, because PrEP is most beneficial in individuals who already engage in high-risk sexual behavior, strategic delivery of PrEP remains an effective risk-reducing strategy.17,18,21,26,36,37 Even in instances where PrEP has been associated with higher-risk sexual behavior and higher rates of sexually transmitted infections, it still prevents as much as 100% of new HIV infections.38
Fear of drug resistance also contributes to slow implementation of PrEP. Drug resistance has been observed in clinical trials of PrEP, but it has been exceedingly rare and predominantly limited to patients who had unrecognized AHI when they started PrEP.39 Furthermore, the few cases of drug resistance attributable to PrEP pale in comparison to the large number of estimated HIV infections averted—infections that would require lifelong ART with its own associated risks of drug resistance. By decreasing HIV transmission, PrEP is expected to decrease total drug resistance.40
Cost is another obstacle. Truvada costs approximately $1,540 per month.41 However, analysis has demonstrated that PrEP is cost-effective when targeted to high-risk patients.42 Most insurance plans cover PrEP, but often require high deductibles and copays; fortunately, this financial burden for patients can be mitigated or eliminated by co-pay assistance programs. The manufacturer of Truvada offers assistance programs for both insured and uninsured patients who are candidates for PrEP; details are available at http://www.truvada.com/truvada-patient-assistance.
Stigma has historically burdened individuals who seek to protect their sexual health, including HIV-negative individuals who are candidates for PrEP. Stigma surrounding HIV may decrease ART-based HIV prevention in men who have sex with men,43 while increasing high-risk behaviors44 and all-cause mortality.45
The resources listed in TABLE 2 can help physicians overcome some of the barriers to implementing PrEP.
How to deliver PrEP
Whether HIV specialists or primary care clinicians are best suited to provide PrEP is a subject of debate. HIV specialists are most familiar with ART and routine monitoring of adherence; however, they have less access to HIV-negative patients, who are the target group for PrEP.35 Family physicians tend to work in closer proximity and maintain longitudinal relationships with PrEP target groups, but in general have less experience with ART and evaluating AHI. Some may argue that competing demands may make it impractical to take a detailed sexual history during a primary care visit.46 In truth, both HIV specialists and family physicians can be appropriately equipped to provide PrEP.
TABLE 3 outlines the steps necessary to provide a patient with PrEP.47 Assessing risk is the initial step; PrEP is beneficial for patients who have one or more risk factors for HIV infection. To be eligible for TDF/FTC, a patient must be HIV-negative, and should be tested for hepatitis B virus (HBV) infection and kidney disease. Because TDF/FTC treats HBV infection, candidates for PrEP who test positive for HBV should be evaluated for treatment of HBV before initiating PrEP. Candidates for PrEP who test negative for HBV infection and immunity should be vaccinated.
Candidates for PrEP should also be screened and monitored for kidney disease. TDF can cause increased serum creatinine due to tubular toxicity. A patient who has an estimated creatinine clearance <60 mL/min should not receive TDF/FTC for PrEP. If a patient’s estimated creatinine clearance falls below 60 mL/min or serum creatinine increases by 0.3 mg/dL above baseline after PrEP is started, TDF/FTC should be discontinued, and the patient should be evaluated for the underlying cause of the kidney disease.27
Before starting PrEP, candidates should be screened for HIV infection and symptoms of AHI. Strongly consider testing for sexually transmitted infections that may increase the risk of HIV transmission, such as syphilis, gonorrhea, or chlamydia.
Candidates who are eligible for PrEP must be counseled on medication adverse effects, adherence strategies, and symptoms of sexually transmitted infections. To initiate PrEP, candidates may be given a one-month supply of TDF/FTC; adherence, adverse effects, and other risk-reduction strategies are assessed at an office visit 3 to 4 weeks later. Subsequent prescriptions are then dispensed as a 3-month supply, with office visits to monitor PrEP scheduled for at least once every 3 months. During these monitoring visits, evaluate the patient’s HIV status, pregnancy status, adherence, adverse effects, risk-reduction behaviors, and indications for continued PrEP. Every 6 months, renal function and sexually transmitted infection status should be reassessed.
Reducing risk of harm among patients who inject drugs
Nonsexual transmission of HIV is a route of high infectivity.48 It includes transfusion of infected blood, sharing of equipment during injection drug use, and percutaneous needle sticks. Sharing of equipment during injection drug use is estimated to account for 8% of new infections in the United States.4
Harm reduction is a collection of strategies meant to reduce complications of illicit drug use, including HIV transmission. These strategies include needle and syringe programs that provide injection drug users with sterile equipment, and opioid substitution therapy.
Needle and syringe programs decrease HIV transmission49 and risky behaviors related to injection drug use,50 but federal funding of such programs is prohibited. Opioid substitution therapy reduces the incidence of HIV,50,51 injection drug use, sharing of drug preparation and injection equipment, and drug-related behaviors associated with a high risk of HIV transmission.50,52 However, in the United States, the quality of these programs varies; a study of opioid substitution therapy delivery found that 22.8% of programs provided doses that were too low to be effective.53
FDA-approved medications for opioid substitution therapy include sublingual buprenorphine, sublingual buprenorphine/naloxone tablets or strips (Suboxone), and oral methadone. Buprenorphine-based regimens can be provided by appropriately trained primary care clinicians; methadone requires a referral to a narcotic treatment program. TABLE 4 provides training and support resources for physicians who want to integrate opioid substitution therapy into their clinical practice.
CORRESPONDENCE
Richard Moore II, MD, 250 Smith Church Road, Roanoke Rapids, NC 27870; [email protected].
› Screen all pregnant women and individuals ages 15 to 65 for human immunodeficiency virus (HIV) infection. A
› Prescribe tenofovir disoproxil fumarate/emtricitabine (Truvada) for pre-exposure prophylaxis for patients at high risk of acquiring HIV. A
› Offer needle and syringe exchange programs and, when appropriate, opioid substitution therapy to individuals who inject drugs. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
Despite advances in human immunodeficiency virus (HIV) screening and treatment over the last 30 years, HIV remains a public health concern. In the United States, after an initial decline, total HIV incidence has failed to significantly decrease in the last 25 years. More than 1.2 million people are living with HIV in the United States, and 12.8% of them (156,300) are unaware they are affected.1 Of those diagnosed with HIV, only 30% are receiving treatment and are virally suppressed.2 Due to structural inequalities and psychosocial factors, African American and Latino patients remain disproportionately affected.3 The incidence of HIV infection among men who have sex with men has increased, and the incidence of HIV infection among people who inject drugs has plateaued after years of progressive decline.4
HIV prevention strategies are highly effective, but in general are underutilized. This article reviews 3 prevention strategies that can be administered by family physicians: HIV screening, pre-exposure prophylaxis (PrEP), and harm reduction.
Who and how to screen for HIV
Early identification of HIV infection generally leads to reduced transmission because diagnosis is associated with decreases in risky behavior.5,6 In addition, antiretroviral therapy (ART) is more effective when initiated early, before the development of advanced immunosuppression.7-9
The “window period” of acute HIV infection (AHI) is the time from when the virus is transmitted to when markers of infection can be detected. Because this window period is associated with high viral transmission rates, family physicians must be familiar with symptoms of AHI (TABLE 1)10,11 and associated risk factors (eg, recent condomless sex or sharing of drug injection equipment with someone who is HIV-positive or of unknown HIV status).
Screening for HIV solely based on the presence of risk factors or clinical symptoms is not enough, however. The United States Preventive Services Task Force (USPSTF) recommends screening all pregnant women and individuals ages 15 to 65 for HIV.12 Screening based solely on risk factors or clinical symptoms frequently leads to missed diagnoses and identification of HIV infection at more advanced stages.13,14 Both the USPSTF and the Centers for Disease Control and Prevention (CDC) recommend universal opt-out screening (patients are informed that HIV screening will be performed and that they may decline testing) because such screening identifies HIV earlier and is associated with higher testing rates than opt-in screening, which requires explicit written consent and extensive pre-test counseling.
Which test to use. HIV screening with a fourth-generation antigen/antibody combination immunoassay—which detects both HIV p24 antigen and HIV antibodies—provides greater diagnostic accuracy than older tests.15 These newer tests detect HIV approximately 15 days after initial infection, reducing the window period of AHI.15,16 If you suspect a patient has AHI, consider early repeat HIV testing with a fourth-generation assay, or initial co-testing with a fourth-generation assay and a nucleic acid amplification test for HIV RNA, which makes it possible to detect infection approximately 5 days earlier than fourth-generation assays.15
Offer pre-exposure prophylaxis to high-risk patients
PrEP is the use of ART prior to HIV exposure to prevent transmission of the virus. It should be used with conventional risk reduction strategies, such as providing condoms, counseling patients about reducing risky behaviors, supporting medication adherence, and screening for and treating other sexually transmitted infections.
The US Food and Drug Administration (FDA) has approved only one medication, Truvada (tenofovir disoproxil fumarate/emtricitabine; TDF/FTC), for use as PrEP. Oral tenofovir-based regimens can effectively prevent HIV transmission,17-20 and strong adherence is associated with a risk reduction of 90% to 100%.17-23 The protective effect of oral PrEP is particularly strong in high-risk populations (eg, men who have sex with men, people who inject drugs), where the number needed to treat to prevent one HIV infection ranges from 12 to 100, depending on the patients’ risk profile.24-26 The CDC and Department of Health and Human Services have issued guidelines for using PrEP in high-risk patients.27
Barriers to implementing PrEP. Despite being highly effective, PrEP is not routinely prescribed to high-risk patients; modeling suggests that current use of PrEP is insufficient to significantly impact the incidence of HIV.28 Demand for PrEP is high among target groups,21,29,30 but patients have expressed concerns about adverse effects31 and stigma related to ART, HIV, and being at risk for HIV.32,33 Young age, lack of social support, low perception of risk, and failure to show up for appointments are also barriers to PrEP use.28,30,34
Some physicians have expressed concern that prescribing PrEP may promote high-risk sexual behavior.35 However, because PrEP is most beneficial in individuals who already engage in high-risk sexual behavior, strategic delivery of PrEP remains an effective risk-reducing strategy.17,18,21,26,36,37 Even in instances where PrEP has been associated with higher-risk sexual behavior and higher rates of sexually transmitted infections, it still prevents as much as 100% of new HIV infections.38
Fear of drug resistance also contributes to slow implementation of PrEP. Drug resistance has been observed in clinical trials of PrEP, but it has been exceedingly rare and predominantly limited to patients who had unrecognized AHI when they started PrEP.39 Furthermore, the few cases of drug resistance attributable to PrEP pale in comparison to the large number of estimated HIV infections averted—infections that would require lifelong ART with its own associated risks of drug resistance. By decreasing HIV transmission, PrEP is expected to decrease total drug resistance.40
Cost is another obstacle. Truvada costs approximately $1,540 per month.41 However, analysis has demonstrated that PrEP is cost-effective when targeted to high-risk patients.42 Most insurance plans cover PrEP, but often require high deductibles and copays; fortunately, this financial burden for patients can be mitigated or eliminated by co-pay assistance programs. The manufacturer of Truvada offers assistance programs for both insured and uninsured patients who are candidates for PrEP; details are available at http://www.truvada.com/truvada-patient-assistance.
Stigma has historically burdened individuals who seek to protect their sexual health, including HIV-negative individuals who are candidates for PrEP. Stigma surrounding HIV may decrease ART-based HIV prevention in men who have sex with men,43 while increasing high-risk behaviors44 and all-cause mortality.45
The resources listed in TABLE 2 can help physicians overcome some of the barriers to implementing PrEP.
How to deliver PrEP
Whether HIV specialists or primary care clinicians are best suited to provide PrEP is a subject of debate. HIV specialists are most familiar with ART and routine monitoring of adherence; however, they have less access to HIV-negative patients, who are the target group for PrEP.35 Family physicians tend to work in closer proximity and maintain longitudinal relationships with PrEP target groups, but in general have less experience with ART and evaluating AHI. Some may argue that competing demands may make it impractical to take a detailed sexual history during a primary care visit.46 In truth, both HIV specialists and family physicians can be appropriately equipped to provide PrEP.
TABLE 3 outlines the steps necessary to provide a patient with PrEP.47 Assessing risk is the initial step; PrEP is beneficial for patients who have one or more risk factors for HIV infection. To be eligible for TDF/FTC, a patient must be HIV-negative, and should be tested for hepatitis B virus (HBV) infection and kidney disease. Because TDF/FTC treats HBV infection, candidates for PrEP who test positive for HBV should be evaluated for treatment of HBV before initiating PrEP. Candidates for PrEP who test negative for HBV infection and immunity should be vaccinated.
Candidates for PrEP should also be screened and monitored for kidney disease. TDF can cause increased serum creatinine due to tubular toxicity. A patient who has an estimated creatinine clearance <60 mL/min should not receive TDF/FTC for PrEP. If a patient’s estimated creatinine clearance falls below 60 mL/min or serum creatinine increases by 0.3 mg/dL above baseline after PrEP is started, TDF/FTC should be discontinued, and the patient should be evaluated for the underlying cause of the kidney disease.27
Before starting PrEP, candidates should be screened for HIV infection and symptoms of AHI. Strongly consider testing for sexually transmitted infections that may increase the risk of HIV transmission, such as syphilis, gonorrhea, or chlamydia.
Candidates who are eligible for PrEP must be counseled on medication adverse effects, adherence strategies, and symptoms of sexually transmitted infections. To initiate PrEP, candidates may be given a one-month supply of TDF/FTC; adherence, adverse effects, and other risk-reduction strategies are assessed at an office visit 3 to 4 weeks later. Subsequent prescriptions are then dispensed as a 3-month supply, with office visits to monitor PrEP scheduled for at least once every 3 months. During these monitoring visits, evaluate the patient’s HIV status, pregnancy status, adherence, adverse effects, risk-reduction behaviors, and indications for continued PrEP. Every 6 months, renal function and sexually transmitted infection status should be reassessed.
Reducing risk of harm among patients who inject drugs
Nonsexual transmission of HIV is a route of high infectivity.48 It includes transfusion of infected blood, sharing of equipment during injection drug use, and percutaneous needle sticks. Sharing of equipment during injection drug use is estimated to account for 8% of new infections in the United States.4
Harm reduction is a collection of strategies meant to reduce complications of illicit drug use, including HIV transmission. These strategies include needle and syringe programs that provide injection drug users with sterile equipment, and opioid substitution therapy.
Needle and syringe programs decrease HIV transmission49 and risky behaviors related to injection drug use,50 but federal funding of such programs is prohibited. Opioid substitution therapy reduces the incidence of HIV,50,51 injection drug use, sharing of drug preparation and injection equipment, and drug-related behaviors associated with a high risk of HIV transmission.50,52 However, in the United States, the quality of these programs varies; a study of opioid substitution therapy delivery found that 22.8% of programs provided doses that were too low to be effective.53
FDA-approved medications for opioid substitution therapy include sublingual buprenorphine, sublingual buprenorphine/naloxone tablets or strips (Suboxone), and oral methadone. Buprenorphine-based regimens can be provided by appropriately trained primary care clinicians; methadone requires a referral to a narcotic treatment program. TABLE 4 provides training and support resources for physicians who want to integrate opioid substitution therapy into their clinical practice.
CORRESPONDENCE
Richard Moore II, MD, 250 Smith Church Road, Roanoke Rapids, NC 27870; [email protected].
1. Hall HI, An Q, Tang T, et al; Centers for Disease Control and Prevention (CDC). Prevalence of diagnosed and undiagnosed HIV infection--United States, 2008-2012. MMWR Morb Mortal Wkly Rep. 2015;64:657-662.
2. Bradley H, Hall HI, Wolitski RJ, et al. Vital signs: HIV diagnosis, care, and treatment among persons living with HIV--United States, 2011. MMWR Morb Mortal Wkly Rep. 2014;63:1113-1117.
3. Maulsby C, Millet G, Lindsey K, et al. HIV among black men who have sex with men (MSM) in the United States: a review of the literature. AIDS Behav. 2014;18:10-25.
4. Centers for Disease Control and Prevention. Estimated HIV incidence among adults and adolescents in the United States, 2007-2010, HIV Surveillance Supplemental Report. 2012. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/statistics_hssr_vol_17_no_4.pdf. Accessed October 8, 2015.
5. Cleary PD, Van Devanter N, Rogers TF, et al. Behavior changes after notification of HIV infection. Am J Public Health. 1991;81:1586-1590.
6. Higgins DL, Galavotti C, O’Reilly KR, et al. Evidence for the effects of HIV antibody counseling and testing on risk behaviors. JAMA. 1991;266:2419-2429.
7. Murphy EL, Collier AC, Kalish LA, et al. Highly active antiretroviral therapy decreases mortality and morbidity in patients with advanced HIV disease. Ann Intern Med. 2001;135:17-26.
8. Palella FJ Jr, Deloria-Knoll M, Chmiel JS, et al. Survival benefit of initiating antiretroviral therapy in HIV-infected persons in different CD4 cell strata. Ann Intern Med. 2003;138:620-626.
9. INSIGHT START Study Group, Lundgren JD, Babiker AG, Gordin F, et al. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med. 2015;373:795-807.
10. Daar ES, Pilcher CD, Hecht FM. Clinical presentation and diagnosis of primary HIV-1 infection. Curr Opin HIV AIDS. 2008;3:10-15.
11. Tindall B, Barker S, Donovan B, et al. Characterization of the acute clinical illness associated with human immunodeficiency virus infection. Arch Intern Med. 1988;148:945-949.
12. Moyer V, US Preventative Services Task Force. Screening for HIV: US Preventive Services Task Force recommendation statement. Ann Intern Med. 2013;159:51-60.
13. Jenkins T, Gardner E, Thrun M, et al. Risk-based HIV testing fails to detect the majority of HIV-infected persons in medical care settings. Sex Transm Dis. 2006;33:329-333.
14. Klein D, Hurley LB, Merrill D, et al. Review of medical encounters in the 5 years before a diagnosis of HIV-1 infection: implications for early detection. J Acquir Immune Defic Syndr. 2003;32:143-152.
15. Pandori M, Hackett J Jr, Louie B, et al. Assessment of the ability of a fourth-generation immunoassay for human immunodeficiency virus (HIV) antibody and p24 antigen to detect both acute and recent HIV infections in a high-risk setting. J Clin Microbiol. 2009;47:2639-2642.
16. Branson BM. The future of HIV testing. J Acquir Imm Defic Syndr. 2010;55 Suppl 2:S102-S105.
17. Grant RM, Lama JR, Anderson PL, et al; iPrEx Study Team. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587-2599.
18. Baeten JM, Donnell D, Ndase P, et al; Partners PrEP Study Team. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367:399-410.
19. Thigpen MC, Kebaabetswe PM, Paxton LA, et al. Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in Botswana. N Engl J Med. 2012;367:423-434.
20. Choopanya K, Martin M, Suntharasamai P, et al. Antiretroviral prophylaxis for HIV infection in injecting drug users in Bangkok, Thailand (the Bangkok Tenofovir Study): a randomised, doubleblind, placebo-controlled phase 3 trial. Lancet. 2013;381:2083-2090.
21. Grant RM, Anderson PL, McMahan V, et al. Uptake of pre-exposure prophylaxis, sexual practices, and HIV incidence in men and transgender women who have sex with men: a cohort study. Lancet Infect Dis. 2014;14:820-829.
22. Anderson PL, Glidden DV, Liu A, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4:151ra125.
23. Henderson FL, Taylor AW, Chirwa LI, et al. Characteristics and oral PrEP adherence in the TDF2 open-label extension in Botswana. Paper presented at International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention; July 1922, 2015; Vancouver, Canada.
24. Murnane PM, Celum C, Mugo N, et al. Efficacy of preexposure prophylaxis for HIV-1 prevention among high-risk heterosexuals: subgroup analyses from a randomized trial. AIDS. 2013;27:2155-2160.
25. Heffron R, Mugo N, Were E, et al. Preexposure prophylaxis is efficacious for HIV-1 prevention among women using depot medroxyprogesterone acetate for contraception. AIDS. 2014;28:2771-2776.
26. Buchbinder SP, Glidden DV, Liu AY, et al. HIV pre-exposure prophylaxis in men who have sex with men and transgender women: a secondary analysis of a phase 3 randomised controlled efficacy trial. Lancet Infect Dis. 2014;14:468-475.
27. Center for Disease Control and Prevention. Preexposure prophylaxis for the prevention of HIV infection in the United States – 2014. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/PrEPguidelines2014.pdf. Accessed June 18, 2015.
28. Grant RM. Scale-up of preexposure prophylaxis in San Francisco to impact HIV incidence. Abstract 25. Paper presented at Conference on Retroviruses and Opportunistic Infections; February 23-26, 2015; Seattle, WA.
29. Cohen SE, Vittinghoff E, Bacon O, et al. High interest in preexposure prophylaxis among men who have sex with men at risk for HIV infection: baseline data from the US PrEP demonstration project. J Acquir Immune Defic Syndr. 2015;68:439-448.
30. Haberer JE, Baeten JM, Campbell J, et al. Adherence to antiretroviral prophylaxis for HIV prevention: a substudy cohort within a clinical trial of serodiscordant couples in East Africa. PLoS Med. 2013;10:e1001511.
31. Gilmore H, Koester K, Liu A, et al. To PrEP or not to PrEP: Perspectives from US iPrEx open label extension (OLE) participants. Abstract 440. Paper presented at 9th International Conference on HIV Treatment and Prevention Adherence; June 9, 2014; Miami Beach, FL.
32. Jain S, Gregor C, Krakower D, et al. Attitudes and interest toward HIV pre-exposure prophylaxis (PrEP) among participants using HIV non-occupational post-exposure prophylaxis (NPEP). Poster Abstract 1523. Poster presented at Infectious Disease Society of America Conference; October 8-12, 2014; Philadelphia, PA.
33. van der Straten A, Stadler J, Luecke E, et al; VOICE-C Study Team, Perspectives on use of oral and vaginal antiretrovirals for HIV prevention: the VOICE-C qualitative study in Johannesburg, South Africa. J Int AIDS Soc. 2014;17:19146.
34. Corneli AL, McKenna K, Headley J, et al; FEM-PrEP Study Group. A descriptive analysis of perceptions of HIV risk and worry about acquiring HIV among FEM-PrEP participants who seroconverted in Bondo, Kenya, and Pretoria, South Africa. J Int AIDS Soc. 2014;17:19152.
35. Krakower D, Ware N, Mitty JA, et al. HIV providers’ perceived barriers and facilitators to implementing pre-exposure prophylaxis in care settings: a qualitative study. AIDS Behav. 2014;18:1712-1721.
36. McCormack S, Dunn DT, Desai M, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2015. [Epub ahead of print].
37. Mugwanya KK, Donnell D, Celum C, et al. Sexual behaviour of heterosexual men and women receiving antiretroviral pre-exposure prophylaxis for HIV prevention: a longitudinal analysis. Lancet Infect Dis. 2013;13:1021-1028.
38. Volk JE, Marcus JL, Phengrasamy T, et al. No new HIV infections with increasing use of HIV preexposure prophylaxis in a clinical practice setting. Clin Infect Dis. 2015;61:1601-1603.
39. Lehman DA, Baeten JM, McCoy CO, et al. Risk of drug resistance among persons acquiring HIV within a randomized clinical trial of single- or dual-agent preexposure prophylaxis. J Infect Dis. 2015;211:1211-1218.
40. Supervie V, Garcia-Lerma JG, Heneine W, et al. HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis. Proc Natl Acad Sci U S A. 2010;107:12381-12386.
41. AIDSinfo. Cost considerations and antiretroviral therapy. AIDSinfo Web site. Available at: https://aidsinfo.nih.gov/guidelines/html/1/adult-and-adolescent-arv-guidelines/459/cost-considerations-and-antiretroviral-therapy. Accessed December 14, 2015.
42. Gomez GB, Borquez A, Case KK, et al. The cost and impact of scaling up pre-exposure prophylaxis for HIV prevention: a systematic review of cost-effectiveness modelling studies. PLoS Med. 2013;10:e1001401.
43. Oldenburg CE, Perez-Brumer AG, Hatzenbuehler ML, et al. State-level structural sexual stigma and HIV prevention in a national online sample of HIV-uninfected MSM in the United States. AIDS. 2015;29:837-845.
44. Hatzenbuehler ML, O’Cleirigh C, Mayer KH, et al. Prospective associations between HIV-related stigma, transmission risk behaviors, and adverse mental health outcomes in men who have sex with men. Ann Behav Med. 2011;42:227-234.
45. Hatzenbuehler ML, Bellatorre A, Lee Y, et al. Structural stigma and all-cause mortality in sexual minority populations. Soc Sci Med. 2014;103:33-41.
46. Arnold EA, Hazelton P, Lane T, et al. A qualitative study of provider thoughts on implementing pre-exposure prophylaxis (PrEP) in clinical settings to prevent HIV infection. PLoS One. 2012;7:e40603.
47. North Carolina AIDS Training and Education Center. For PrEP Providers. North Carolina AIDS Training and Education Center Web site. Available at: http://www.med.unc.edu/ncaidstraining/prep/for-providers/for-prep-prescribers. Accessed July 7, 2015.
48. Patel P, Borkowf CB, Brook JT, et al. Estimating per-act HIV transmission risk: a systematic review. AIDS. 2014;28:1509-1519.
49. Aspinall EJ, Nambiar D, Goldberg DJ, et al. Are needle and syringe programmes associated with a reduction in HIV transmission among people who inject drugs: a systematic review and metaanalysis. Int J Epidemiol. 2014;43:235-248.
50. MacArthur GJ, van Velzen E, Palmateer N, et al. Interventions to prevent HIV and Hepatitis C in people who inject drugs: a review of reviews to assess evidence of effectiveness. Int J Drug Policy. 2014;25:34-52.
51. MacArthur GJ, Minozzi S, Martin N, et al. Opiate substitution treatment and HIV transmission in people who inject drugs: systematic review and meta-analysis. BMJ. 2012;345:e5945.
52. Gowing L, Farrell MF, Bornemann R, et al. Oral substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev. 2011;(8):CD004145.
53. D’Aunno T, Pollack HA, Frimpong JA, et al. Evidence-based treatment for opioid disorders: a 23-year national study of methadone dose levels. J Subst Abuse Treat. 2014;47:245-250.
1. Hall HI, An Q, Tang T, et al; Centers for Disease Control and Prevention (CDC). Prevalence of diagnosed and undiagnosed HIV infection--United States, 2008-2012. MMWR Morb Mortal Wkly Rep. 2015;64:657-662.
2. Bradley H, Hall HI, Wolitski RJ, et al. Vital signs: HIV diagnosis, care, and treatment among persons living with HIV--United States, 2011. MMWR Morb Mortal Wkly Rep. 2014;63:1113-1117.
3. Maulsby C, Millet G, Lindsey K, et al. HIV among black men who have sex with men (MSM) in the United States: a review of the literature. AIDS Behav. 2014;18:10-25.
4. Centers for Disease Control and Prevention. Estimated HIV incidence among adults and adolescents in the United States, 2007-2010, HIV Surveillance Supplemental Report. 2012. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/statistics_hssr_vol_17_no_4.pdf. Accessed October 8, 2015.
5. Cleary PD, Van Devanter N, Rogers TF, et al. Behavior changes after notification of HIV infection. Am J Public Health. 1991;81:1586-1590.
6. Higgins DL, Galavotti C, O’Reilly KR, et al. Evidence for the effects of HIV antibody counseling and testing on risk behaviors. JAMA. 1991;266:2419-2429.
7. Murphy EL, Collier AC, Kalish LA, et al. Highly active antiretroviral therapy decreases mortality and morbidity in patients with advanced HIV disease. Ann Intern Med. 2001;135:17-26.
8. Palella FJ Jr, Deloria-Knoll M, Chmiel JS, et al. Survival benefit of initiating antiretroviral therapy in HIV-infected persons in different CD4 cell strata. Ann Intern Med. 2003;138:620-626.
9. INSIGHT START Study Group, Lundgren JD, Babiker AG, Gordin F, et al. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med. 2015;373:795-807.
10. Daar ES, Pilcher CD, Hecht FM. Clinical presentation and diagnosis of primary HIV-1 infection. Curr Opin HIV AIDS. 2008;3:10-15.
11. Tindall B, Barker S, Donovan B, et al. Characterization of the acute clinical illness associated with human immunodeficiency virus infection. Arch Intern Med. 1988;148:945-949.
12. Moyer V, US Preventative Services Task Force. Screening for HIV: US Preventive Services Task Force recommendation statement. Ann Intern Med. 2013;159:51-60.
13. Jenkins T, Gardner E, Thrun M, et al. Risk-based HIV testing fails to detect the majority of HIV-infected persons in medical care settings. Sex Transm Dis. 2006;33:329-333.
14. Klein D, Hurley LB, Merrill D, et al. Review of medical encounters in the 5 years before a diagnosis of HIV-1 infection: implications for early detection. J Acquir Immune Defic Syndr. 2003;32:143-152.
15. Pandori M, Hackett J Jr, Louie B, et al. Assessment of the ability of a fourth-generation immunoassay for human immunodeficiency virus (HIV) antibody and p24 antigen to detect both acute and recent HIV infections in a high-risk setting. J Clin Microbiol. 2009;47:2639-2642.
16. Branson BM. The future of HIV testing. J Acquir Imm Defic Syndr. 2010;55 Suppl 2:S102-S105.
17. Grant RM, Lama JR, Anderson PL, et al; iPrEx Study Team. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587-2599.
18. Baeten JM, Donnell D, Ndase P, et al; Partners PrEP Study Team. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367:399-410.
19. Thigpen MC, Kebaabetswe PM, Paxton LA, et al. Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in Botswana. N Engl J Med. 2012;367:423-434.
20. Choopanya K, Martin M, Suntharasamai P, et al. Antiretroviral prophylaxis for HIV infection in injecting drug users in Bangkok, Thailand (the Bangkok Tenofovir Study): a randomised, doubleblind, placebo-controlled phase 3 trial. Lancet. 2013;381:2083-2090.
21. Grant RM, Anderson PL, McMahan V, et al. Uptake of pre-exposure prophylaxis, sexual practices, and HIV incidence in men and transgender women who have sex with men: a cohort study. Lancet Infect Dis. 2014;14:820-829.
22. Anderson PL, Glidden DV, Liu A, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4:151ra125.
23. Henderson FL, Taylor AW, Chirwa LI, et al. Characteristics and oral PrEP adherence in the TDF2 open-label extension in Botswana. Paper presented at International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention; July 1922, 2015; Vancouver, Canada.
24. Murnane PM, Celum C, Mugo N, et al. Efficacy of preexposure prophylaxis for HIV-1 prevention among high-risk heterosexuals: subgroup analyses from a randomized trial. AIDS. 2013;27:2155-2160.
25. Heffron R, Mugo N, Were E, et al. Preexposure prophylaxis is efficacious for HIV-1 prevention among women using depot medroxyprogesterone acetate for contraception. AIDS. 2014;28:2771-2776.
26. Buchbinder SP, Glidden DV, Liu AY, et al. HIV pre-exposure prophylaxis in men who have sex with men and transgender women: a secondary analysis of a phase 3 randomised controlled efficacy trial. Lancet Infect Dis. 2014;14:468-475.
27. Center for Disease Control and Prevention. Preexposure prophylaxis for the prevention of HIV infection in the United States – 2014. Centers for Disease Control and Prevention Web site. Available at: http://www.cdc.gov/hiv/pdf/PrEPguidelines2014.pdf. Accessed June 18, 2015.
28. Grant RM. Scale-up of preexposure prophylaxis in San Francisco to impact HIV incidence. Abstract 25. Paper presented at Conference on Retroviruses and Opportunistic Infections; February 23-26, 2015; Seattle, WA.
29. Cohen SE, Vittinghoff E, Bacon O, et al. High interest in preexposure prophylaxis among men who have sex with men at risk for HIV infection: baseline data from the US PrEP demonstration project. J Acquir Immune Defic Syndr. 2015;68:439-448.
30. Haberer JE, Baeten JM, Campbell J, et al. Adherence to antiretroviral prophylaxis for HIV prevention: a substudy cohort within a clinical trial of serodiscordant couples in East Africa. PLoS Med. 2013;10:e1001511.
31. Gilmore H, Koester K, Liu A, et al. To PrEP or not to PrEP: Perspectives from US iPrEx open label extension (OLE) participants. Abstract 440. Paper presented at 9th International Conference on HIV Treatment and Prevention Adherence; June 9, 2014; Miami Beach, FL.
32. Jain S, Gregor C, Krakower D, et al. Attitudes and interest toward HIV pre-exposure prophylaxis (PrEP) among participants using HIV non-occupational post-exposure prophylaxis (NPEP). Poster Abstract 1523. Poster presented at Infectious Disease Society of America Conference; October 8-12, 2014; Philadelphia, PA.
33. van der Straten A, Stadler J, Luecke E, et al; VOICE-C Study Team, Perspectives on use of oral and vaginal antiretrovirals for HIV prevention: the VOICE-C qualitative study in Johannesburg, South Africa. J Int AIDS Soc. 2014;17:19146.
34. Corneli AL, McKenna K, Headley J, et al; FEM-PrEP Study Group. A descriptive analysis of perceptions of HIV risk and worry about acquiring HIV among FEM-PrEP participants who seroconverted in Bondo, Kenya, and Pretoria, South Africa. J Int AIDS Soc. 2014;17:19152.
35. Krakower D, Ware N, Mitty JA, et al. HIV providers’ perceived barriers and facilitators to implementing pre-exposure prophylaxis in care settings: a qualitative study. AIDS Behav. 2014;18:1712-1721.
36. McCormack S, Dunn DT, Desai M, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2015. [Epub ahead of print].
37. Mugwanya KK, Donnell D, Celum C, et al. Sexual behaviour of heterosexual men and women receiving antiretroviral pre-exposure prophylaxis for HIV prevention: a longitudinal analysis. Lancet Infect Dis. 2013;13:1021-1028.
38. Volk JE, Marcus JL, Phengrasamy T, et al. No new HIV infections with increasing use of HIV preexposure prophylaxis in a clinical practice setting. Clin Infect Dis. 2015;61:1601-1603.
39. Lehman DA, Baeten JM, McCoy CO, et al. Risk of drug resistance among persons acquiring HIV within a randomized clinical trial of single- or dual-agent preexposure prophylaxis. J Infect Dis. 2015;211:1211-1218.
40. Supervie V, Garcia-Lerma JG, Heneine W, et al. HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis. Proc Natl Acad Sci U S A. 2010;107:12381-12386.
41. AIDSinfo. Cost considerations and antiretroviral therapy. AIDSinfo Web site. Available at: https://aidsinfo.nih.gov/guidelines/html/1/adult-and-adolescent-arv-guidelines/459/cost-considerations-and-antiretroviral-therapy. Accessed December 14, 2015.
42. Gomez GB, Borquez A, Case KK, et al. The cost and impact of scaling up pre-exposure prophylaxis for HIV prevention: a systematic review of cost-effectiveness modelling studies. PLoS Med. 2013;10:e1001401.
43. Oldenburg CE, Perez-Brumer AG, Hatzenbuehler ML, et al. State-level structural sexual stigma and HIV prevention in a national online sample of HIV-uninfected MSM in the United States. AIDS. 2015;29:837-845.
44. Hatzenbuehler ML, O’Cleirigh C, Mayer KH, et al. Prospective associations between HIV-related stigma, transmission risk behaviors, and adverse mental health outcomes in men who have sex with men. Ann Behav Med. 2011;42:227-234.
45. Hatzenbuehler ML, Bellatorre A, Lee Y, et al. Structural stigma and all-cause mortality in sexual minority populations. Soc Sci Med. 2014;103:33-41.
46. Arnold EA, Hazelton P, Lane T, et al. A qualitative study of provider thoughts on implementing pre-exposure prophylaxis (PrEP) in clinical settings to prevent HIV infection. PLoS One. 2012;7:e40603.
47. North Carolina AIDS Training and Education Center. For PrEP Providers. North Carolina AIDS Training and Education Center Web site. Available at: http://www.med.unc.edu/ncaidstraining/prep/for-providers/for-prep-prescribers. Accessed July 7, 2015.
48. Patel P, Borkowf CB, Brook JT, et al. Estimating per-act HIV transmission risk: a systematic review. AIDS. 2014;28:1509-1519.
49. Aspinall EJ, Nambiar D, Goldberg DJ, et al. Are needle and syringe programmes associated with a reduction in HIV transmission among people who inject drugs: a systematic review and metaanalysis. Int J Epidemiol. 2014;43:235-248.
50. MacArthur GJ, van Velzen E, Palmateer N, et al. Interventions to prevent HIV and Hepatitis C in people who inject drugs: a review of reviews to assess evidence of effectiveness. Int J Drug Policy. 2014;25:34-52.
51. MacArthur GJ, Minozzi S, Martin N, et al. Opiate substitution treatment and HIV transmission in people who inject drugs: systematic review and meta-analysis. BMJ. 2012;345:e5945.
52. Gowing L, Farrell MF, Bornemann R, et al. Oral substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev. 2011;(8):CD004145.
53. D’Aunno T, Pollack HA, Frimpong JA, et al. Evidence-based treatment for opioid disorders: a 23-year national study of methadone dose levels. J Subst Abuse Treat. 2014;47:245-250.
Finally, an extra set of hands
In September 2015, the Centers for Medicare & Medicaid Services (CMS) launched a promising 4-year program called the "Transforming Clinical Practice Initiative" to lighten the load for family physicians.1 The central figures in this program are skilled and trained quality improvement advisors (QIA) who will work directly with physicians and their staffs to assist with the heavy lifting of practice improvement. The Oklahoma Physicians Research and Resources Network has used QIAs, which it calls practice enhancement assistants (PEAs), for more than 20 years to help Oklahoma family physicians improve various aspects of their practices, including testing processes, diabetes care, and preventive services. The PEAs have been enormously helpful.2
For this new CMS program, the feds awarded $685 million to 39 national and regional collaborative health care transformation networks and supporting organizations to develop peer-based learning networks to facilitate practice improvements.1 The program is designed to help more than 140,000 primary care physicians improve their practices by providing an extra set of skilled hands.
The American Board of Family Medicine (ABFM) and the American Academy of Family Physicians (AAFP) have teamed up to assist with this national effort. ABFM will cover the cost for the first 6000 family physicians who enroll in one of the regional Practice Transformation Networks to use their newly developed chronic disease registry called PRIME. This registry will extract clinical quality data from diverse electronic health records and report back to practices. The registry will meet the new federal quality measures reporting requirements and will also be a path for maintenance of certification.
The CMS Transforming Clinical Practice Initiative is a great opportunity to get that extra set of skilled hands you need to help meet new quality mandates and make your office more efficient and enjoyable for you, your staff, and your patients. Contact the ABFM (www.theabfm.org) to find out which organization is running the Practice Transformation Network in your area.
1. Centers for Medicare & Medicaid Services (CMS). Transforming clinical practice initiative awards. CMS Web site. Available at: https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2015-Fact-sheets-items/2015-09-29.html. Accessed December 15, 2015.
2. Nagykaldi Z, Mold JW, Robinson A, et al. Practice facilitators and practice-based research networks. J Am Board Fam Med. 2006;19:506-510.
In September 2015, the Centers for Medicare & Medicaid Services (CMS) launched a promising 4-year program called the "Transforming Clinical Practice Initiative" to lighten the load for family physicians.1 The central figures in this program are skilled and trained quality improvement advisors (QIA) who will work directly with physicians and their staffs to assist with the heavy lifting of practice improvement. The Oklahoma Physicians Research and Resources Network has used QIAs, which it calls practice enhancement assistants (PEAs), for more than 20 years to help Oklahoma family physicians improve various aspects of their practices, including testing processes, diabetes care, and preventive services. The PEAs have been enormously helpful.2
For this new CMS program, the feds awarded $685 million to 39 national and regional collaborative health care transformation networks and supporting organizations to develop peer-based learning networks to facilitate practice improvements.1 The program is designed to help more than 140,000 primary care physicians improve their practices by providing an extra set of skilled hands.
The American Board of Family Medicine (ABFM) and the American Academy of Family Physicians (AAFP) have teamed up to assist with this national effort. ABFM will cover the cost for the first 6000 family physicians who enroll in one of the regional Practice Transformation Networks to use their newly developed chronic disease registry called PRIME. This registry will extract clinical quality data from diverse electronic health records and report back to practices. The registry will meet the new federal quality measures reporting requirements and will also be a path for maintenance of certification.
The CMS Transforming Clinical Practice Initiative is a great opportunity to get that extra set of skilled hands you need to help meet new quality mandates and make your office more efficient and enjoyable for you, your staff, and your patients. Contact the ABFM (www.theabfm.org) to find out which organization is running the Practice Transformation Network in your area.
In September 2015, the Centers for Medicare & Medicaid Services (CMS) launched a promising 4-year program called the "Transforming Clinical Practice Initiative" to lighten the load for family physicians.1 The central figures in this program are skilled and trained quality improvement advisors (QIA) who will work directly with physicians and their staffs to assist with the heavy lifting of practice improvement. The Oklahoma Physicians Research and Resources Network has used QIAs, which it calls practice enhancement assistants (PEAs), for more than 20 years to help Oklahoma family physicians improve various aspects of their practices, including testing processes, diabetes care, and preventive services. The PEAs have been enormously helpful.2
For this new CMS program, the feds awarded $685 million to 39 national and regional collaborative health care transformation networks and supporting organizations to develop peer-based learning networks to facilitate practice improvements.1 The program is designed to help more than 140,000 primary care physicians improve their practices by providing an extra set of skilled hands.
The American Board of Family Medicine (ABFM) and the American Academy of Family Physicians (AAFP) have teamed up to assist with this national effort. ABFM will cover the cost for the first 6000 family physicians who enroll in one of the regional Practice Transformation Networks to use their newly developed chronic disease registry called PRIME. This registry will extract clinical quality data from diverse electronic health records and report back to practices. The registry will meet the new federal quality measures reporting requirements and will also be a path for maintenance of certification.
The CMS Transforming Clinical Practice Initiative is a great opportunity to get that extra set of skilled hands you need to help meet new quality mandates and make your office more efficient and enjoyable for you, your staff, and your patients. Contact the ABFM (www.theabfm.org) to find out which organization is running the Practice Transformation Network in your area.
1. Centers for Medicare & Medicaid Services (CMS). Transforming clinical practice initiative awards. CMS Web site. Available at: https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2015-Fact-sheets-items/2015-09-29.html. Accessed December 15, 2015.
2. Nagykaldi Z, Mold JW, Robinson A, et al. Practice facilitators and practice-based research networks. J Am Board Fam Med. 2006;19:506-510.
1. Centers for Medicare & Medicaid Services (CMS). Transforming clinical practice initiative awards. CMS Web site. Available at: https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2015-Fact-sheets-items/2015-09-29.html. Accessed December 15, 2015.
2. Nagykaldi Z, Mold JW, Robinson A, et al. Practice facilitators and practice-based research networks. J Am Board Fam Med. 2006;19:506-510.
Severe anal pain • perianal swelling • no history of injury to the area • Dx?
THE CASE
An 80-year-old man sought medical advice over the phone because he’d had sharp anal pain for 4 days. The pain increased during sitting and defecation. He was told he most likely had an acute anal fissure and was instructed to treat it with sitz baths, a stool-bulking agent, and a topical anesthetic. Despite these treatments, he continued to have intense anal pain.
Two days later, he presented to our practice complaining of severe anal discomfort and perianal swelling that made it almost impossible to sit. The patient led an active lifestyle and was otherwise healthy. He did not recall any injury to the perianal area.
THE DIAGNOSIS
During examination, we noted tender, erythematous swelling over the right perianal region at the 9 o’clock position without fluctuance, discharge, or ulceration. A digital rectal examination revealed a foreign body lying transversely across the anus about 2.5 cm from the anal verge. A pelvic x-ray confirmed the presence of a foreign body—a pin (FIGURE 1).
DISCUSSION
Anal pain is a common symptom that is usually caused by hemorrhoids, fissures, fistulas, or abscesses.1 Anal pain is rarely reported to be secondary to the ingestion of sharp foreign bodies, which can produce problems in the lower gastrointestinal tract.
Foreign body ingestion is most common in children ages 6 months to 6 years.2 When it occurs in adults, it tends to involve those who are older, patients without teeth, prisoners, patients under the influence of drugs or alcohol, or those with intellectual disabilities or psychiatric disorders.2,3
The foreign bodies that adults most commonly unintentionally ingest are bones from fish or other animals.2,4 Most of these pass through the alimentary tract uneventfully within a week.2,5,6 Swallowed bones have been known to cause perianal abscesses and anal fistulae, which can cause extreme pain.7
The presence of foreign bodies is not always easy to spot
In our patient’s case, the diagnosis was made by a careful digital rectal examination; however, a foreign body in an abscess cavity can be missed during a digital exam.8 In our patient’s case, a pelvic x-ray confirmed the presence and location of the pin.
Radiography is recommended as an initial screening method and is especially useful for determining the location of radiodense foreign bodies.2 However, most swallowed foreign bodies, such as non-radiodense fish bones, wood, thorns, plastic, small aluminum objects, and glass, cannot be detected by this method.3 Non-radiodense foreign bodies can be identified using computed tomography scanning.9
Removal is typically straightforward
The best method of removing a foreign body in the perianal region is by dilating the anus and then cutting the object in half. Alternatively, the object can be carefully dislodged from the anal canal by freeing one of the impacted ends. Care must be taken while removing the object to avoid accidental injury.
This procedure can be performed in any primary care setting that is adequately equipped for minor surgical services. Consider referral to a secondary care specialist based on the level of risk involved and the physician’s skills and training.
Our patient. After a complete assessment, we prepared the patient for gentle anal dilatation under intravenous conscious sedation. We carefully transected the 3.5 cm pin using a nail splitter (FIGURE 2). Because there was no abscess cavity, no other procedure was needed. We prescribed oral amoxicillin/clavulanic acid 500/125 mg every 8 hours for 7 days to treat a local infection.
After the procedure, we asked the patient about the pin. He said he had no idea how he could have ingested it and didn’t recall any abdominal pain during the previous month. Follow-up was normal, and he recovered without any complications.
THE TAKEAWAY
Consider the possibility of ingested sharp foreign bodies as a cause of severe anal pain, and perform a local and digital rectal examination. Radiography is recommended as an initial screening method. Following anal dilatation, the object can be removed by cutting it in half or by freeing one of the impacted ends.
1. Villalba H, Villalba S, Abbas MA. Anal fissure: a common cause of anal pain. Perm J. 2007;11:62-65.
2. Ambe P, Weber SA, Schauer M, et al. Swallowed foreign bodies in adults. Dtsch Arztebl Int. 2012;109:869-875.
3. Erbil B, Karaca MA, Aslaner MA, et al. Emergency admissions due to swallowed foreign bodies in adults. World J Gastroenterol. 2013;19:6447-6452.
4. Kuo CC, Jen TK, Wen CH, et al. Medical treatment for a fish bone-induced ileal micro-perforation: a case report. World J Gastroenterol. 2012;18:5994-5998.
5. Low VHS, Killius JS. Animal, vegetable, or mineral: A collection of abdominal and alimentary foreign bodies. Appl Radiol. 2000;29:23-30.
6. McCanse DE, Kurchin A, Hinshaw JR. Gastrointestinal foreign bodies. Am J Surg. 1981;142:335-337.
7. Goligher JC, Nixon HH, Duthie HL. Surgery of the anus, rectum and colon. 3rd ed. London: Baillière Tindall;1975:205-255.
8. Doublali M, Chouaib A, Elfassi MJ, et al. Perianal abscesses due to ingested foreign bodies. J Emerg Trauma Shock. 2010;3:395-397.
9. Coulier B, Tancredi MH, Ramboux A. Spiral CT and multidetector-row CT diagnosis of perforation of the small intestine caused by ingested foreign bodies. Eur Radiol. 2004;14:1918-1925.
THE CASE
An 80-year-old man sought medical advice over the phone because he’d had sharp anal pain for 4 days. The pain increased during sitting and defecation. He was told he most likely had an acute anal fissure and was instructed to treat it with sitz baths, a stool-bulking agent, and a topical anesthetic. Despite these treatments, he continued to have intense anal pain.
Two days later, he presented to our practice complaining of severe anal discomfort and perianal swelling that made it almost impossible to sit. The patient led an active lifestyle and was otherwise healthy. He did not recall any injury to the perianal area.
THE DIAGNOSIS
During examination, we noted tender, erythematous swelling over the right perianal region at the 9 o’clock position without fluctuance, discharge, or ulceration. A digital rectal examination revealed a foreign body lying transversely across the anus about 2.5 cm from the anal verge. A pelvic x-ray confirmed the presence of a foreign body—a pin (FIGURE 1).
DISCUSSION
Anal pain is a common symptom that is usually caused by hemorrhoids, fissures, fistulas, or abscesses.1 Anal pain is rarely reported to be secondary to the ingestion of sharp foreign bodies, which can produce problems in the lower gastrointestinal tract.
Foreign body ingestion is most common in children ages 6 months to 6 years.2 When it occurs in adults, it tends to involve those who are older, patients without teeth, prisoners, patients under the influence of drugs or alcohol, or those with intellectual disabilities or psychiatric disorders.2,3
The foreign bodies that adults most commonly unintentionally ingest are bones from fish or other animals.2,4 Most of these pass through the alimentary tract uneventfully within a week.2,5,6 Swallowed bones have been known to cause perianal abscesses and anal fistulae, which can cause extreme pain.7
The presence of foreign bodies is not always easy to spot
In our patient’s case, the diagnosis was made by a careful digital rectal examination; however, a foreign body in an abscess cavity can be missed during a digital exam.8 In our patient’s case, a pelvic x-ray confirmed the presence and location of the pin.
Radiography is recommended as an initial screening method and is especially useful for determining the location of radiodense foreign bodies.2 However, most swallowed foreign bodies, such as non-radiodense fish bones, wood, thorns, plastic, small aluminum objects, and glass, cannot be detected by this method.3 Non-radiodense foreign bodies can be identified using computed tomography scanning.9
Removal is typically straightforward
The best method of removing a foreign body in the perianal region is by dilating the anus and then cutting the object in half. Alternatively, the object can be carefully dislodged from the anal canal by freeing one of the impacted ends. Care must be taken while removing the object to avoid accidental injury.
This procedure can be performed in any primary care setting that is adequately equipped for minor surgical services. Consider referral to a secondary care specialist based on the level of risk involved and the physician’s skills and training.
Our patient. After a complete assessment, we prepared the patient for gentle anal dilatation under intravenous conscious sedation. We carefully transected the 3.5 cm pin using a nail splitter (FIGURE 2). Because there was no abscess cavity, no other procedure was needed. We prescribed oral amoxicillin/clavulanic acid 500/125 mg every 8 hours for 7 days to treat a local infection.
After the procedure, we asked the patient about the pin. He said he had no idea how he could have ingested it and didn’t recall any abdominal pain during the previous month. Follow-up was normal, and he recovered without any complications.
THE TAKEAWAY
Consider the possibility of ingested sharp foreign bodies as a cause of severe anal pain, and perform a local and digital rectal examination. Radiography is recommended as an initial screening method. Following anal dilatation, the object can be removed by cutting it in half or by freeing one of the impacted ends.
THE CASE
An 80-year-old man sought medical advice over the phone because he’d had sharp anal pain for 4 days. The pain increased during sitting and defecation. He was told he most likely had an acute anal fissure and was instructed to treat it with sitz baths, a stool-bulking agent, and a topical anesthetic. Despite these treatments, he continued to have intense anal pain.
Two days later, he presented to our practice complaining of severe anal discomfort and perianal swelling that made it almost impossible to sit. The patient led an active lifestyle and was otherwise healthy. He did not recall any injury to the perianal area.
THE DIAGNOSIS
During examination, we noted tender, erythematous swelling over the right perianal region at the 9 o’clock position without fluctuance, discharge, or ulceration. A digital rectal examination revealed a foreign body lying transversely across the anus about 2.5 cm from the anal verge. A pelvic x-ray confirmed the presence of a foreign body—a pin (FIGURE 1).
DISCUSSION
Anal pain is a common symptom that is usually caused by hemorrhoids, fissures, fistulas, or abscesses.1 Anal pain is rarely reported to be secondary to the ingestion of sharp foreign bodies, which can produce problems in the lower gastrointestinal tract.
Foreign body ingestion is most common in children ages 6 months to 6 years.2 When it occurs in adults, it tends to involve those who are older, patients without teeth, prisoners, patients under the influence of drugs or alcohol, or those with intellectual disabilities or psychiatric disorders.2,3
The foreign bodies that adults most commonly unintentionally ingest are bones from fish or other animals.2,4 Most of these pass through the alimentary tract uneventfully within a week.2,5,6 Swallowed bones have been known to cause perianal abscesses and anal fistulae, which can cause extreme pain.7
The presence of foreign bodies is not always easy to spot
In our patient’s case, the diagnosis was made by a careful digital rectal examination; however, a foreign body in an abscess cavity can be missed during a digital exam.8 In our patient’s case, a pelvic x-ray confirmed the presence and location of the pin.
Radiography is recommended as an initial screening method and is especially useful for determining the location of radiodense foreign bodies.2 However, most swallowed foreign bodies, such as non-radiodense fish bones, wood, thorns, plastic, small aluminum objects, and glass, cannot be detected by this method.3 Non-radiodense foreign bodies can be identified using computed tomography scanning.9
Removal is typically straightforward
The best method of removing a foreign body in the perianal region is by dilating the anus and then cutting the object in half. Alternatively, the object can be carefully dislodged from the anal canal by freeing one of the impacted ends. Care must be taken while removing the object to avoid accidental injury.
This procedure can be performed in any primary care setting that is adequately equipped for minor surgical services. Consider referral to a secondary care specialist based on the level of risk involved and the physician’s skills and training.
Our patient. After a complete assessment, we prepared the patient for gentle anal dilatation under intravenous conscious sedation. We carefully transected the 3.5 cm pin using a nail splitter (FIGURE 2). Because there was no abscess cavity, no other procedure was needed. We prescribed oral amoxicillin/clavulanic acid 500/125 mg every 8 hours for 7 days to treat a local infection.
After the procedure, we asked the patient about the pin. He said he had no idea how he could have ingested it and didn’t recall any abdominal pain during the previous month. Follow-up was normal, and he recovered without any complications.
THE TAKEAWAY
Consider the possibility of ingested sharp foreign bodies as a cause of severe anal pain, and perform a local and digital rectal examination. Radiography is recommended as an initial screening method. Following anal dilatation, the object can be removed by cutting it in half or by freeing one of the impacted ends.
1. Villalba H, Villalba S, Abbas MA. Anal fissure: a common cause of anal pain. Perm J. 2007;11:62-65.
2. Ambe P, Weber SA, Schauer M, et al. Swallowed foreign bodies in adults. Dtsch Arztebl Int. 2012;109:869-875.
3. Erbil B, Karaca MA, Aslaner MA, et al. Emergency admissions due to swallowed foreign bodies in adults. World J Gastroenterol. 2013;19:6447-6452.
4. Kuo CC, Jen TK, Wen CH, et al. Medical treatment for a fish bone-induced ileal micro-perforation: a case report. World J Gastroenterol. 2012;18:5994-5998.
5. Low VHS, Killius JS. Animal, vegetable, or mineral: A collection of abdominal and alimentary foreign bodies. Appl Radiol. 2000;29:23-30.
6. McCanse DE, Kurchin A, Hinshaw JR. Gastrointestinal foreign bodies. Am J Surg. 1981;142:335-337.
7. Goligher JC, Nixon HH, Duthie HL. Surgery of the anus, rectum and colon. 3rd ed. London: Baillière Tindall;1975:205-255.
8. Doublali M, Chouaib A, Elfassi MJ, et al. Perianal abscesses due to ingested foreign bodies. J Emerg Trauma Shock. 2010;3:395-397.
9. Coulier B, Tancredi MH, Ramboux A. Spiral CT and multidetector-row CT diagnosis of perforation of the small intestine caused by ingested foreign bodies. Eur Radiol. 2004;14:1918-1925.
1. Villalba H, Villalba S, Abbas MA. Anal fissure: a common cause of anal pain. Perm J. 2007;11:62-65.
2. Ambe P, Weber SA, Schauer M, et al. Swallowed foreign bodies in adults. Dtsch Arztebl Int. 2012;109:869-875.
3. Erbil B, Karaca MA, Aslaner MA, et al. Emergency admissions due to swallowed foreign bodies in adults. World J Gastroenterol. 2013;19:6447-6452.
4. Kuo CC, Jen TK, Wen CH, et al. Medical treatment for a fish bone-induced ileal micro-perforation: a case report. World J Gastroenterol. 2012;18:5994-5998.
5. Low VHS, Killius JS. Animal, vegetable, or mineral: A collection of abdominal and alimentary foreign bodies. Appl Radiol. 2000;29:23-30.
6. McCanse DE, Kurchin A, Hinshaw JR. Gastrointestinal foreign bodies. Am J Surg. 1981;142:335-337.
7. Goligher JC, Nixon HH, Duthie HL. Surgery of the anus, rectum and colon. 3rd ed. London: Baillière Tindall;1975:205-255.
8. Doublali M, Chouaib A, Elfassi MJ, et al. Perianal abscesses due to ingested foreign bodies. J Emerg Trauma Shock. 2010;3:395-397.
9. Coulier B, Tancredi MH, Ramboux A. Spiral CT and multidetector-row CT diagnosis of perforation of the small intestine caused by ingested foreign bodies. Eur Radiol. 2004;14:1918-1925.
Smoking cessation: What should you recommend?
› Prescribe varenicline, bupropion, or nicotine replacement as first-line single pharmacotherapy for smoking cessation. A
› Provide counseling along with medication, as the combination has proven to be more effective than either option alone. A
› Refer patients to their state Quit Line—a toll-free tobacco cessation coaching service that has been shown to be an effective form of counseling. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
In its 2014 report, “The Health Consequences of Smoking—50 Years of Progress,”1 the US Surgeon General concluded that, while significant improvements have been made since the publication of its landmark 1964 report, cigarette smoking remains a major public health problem. It is the leading cause of preventable death, increasing the risks of such common causes of mortality as cardiovascular disease, pulmonary disease, and malignancy. Cigarette smoking is responsible for an estimated 443,000 deaths annually.2
Overall, 42 million US adults and about 3 million middle and high school students smoke, despite the availability of an array of pharmacologic interventions to help them quit.1 Half of those who continue to smoke will die from a tobacco-related cause. Stopping before the age of 50 years cuts the risk in half, and quitting before age 30 almost completely negates it.3
The most recent comprehensive smoking cessation guideline, sponsored by the US Public Health Service, was published in 2008.4 The US Preventive Services Task Force (USPSTF) recommendation that “clinicians ask all adults about tobacco use and provide tobacco cessation interventions” for those who smoke was issued one year later.5 Since then, multiple studies have assessed the merits of the various medications, forms of nicotine replacement therapy (NRT), and counseling aimed at helping smokers maintain abstinence from tobacco.
This article reviews the guideline and provides family physicians with an evidence-based update.
The guideline: Treating tobacco use and dependence
Prescribing a first-line medication (bupropion SR, varenicline, nicotine gum, nicotine inhaler, nicotine lozenge, nicotine nasal spray, or nicotine patch) for every patient who seeks to quit smoking is a key component of the 2008 guideline (See TABLE W1).4 The only exceptions: patients for whom such agents are medically contraindicated and groups for which there is insufficient evidence of effectiveness, such as pregnant women and adolescents.
The use of any of these medications as a single agent nearly doubles the likelihood of success compared with placebo, with an average cessation rate of 25% (TABLE 1).4
Combination therapy (pairing a nicotine patch and an additional agent) was found to be even more effective, with some combinations attaining success rates as high as 65%.4
Second-line therapies, including clonidine and nortriptyline, were also cited as effective, with an average cessation rate of 24%.4 Although the meta-analyses that these averages were based on did not include head-to-head comparisons, subsequent studies that also showed efficacy did include such comparisons.
Counseling is an essential component
In one of the meta-analyses on which the guideline was based, the combination of counseling and medication proved to be more effective than either intervention alone. Individual, group, and telephone counseling were all effective (odds ratio [OR]=1.7 [1.4-2.0], 1.3 [1.1-1.6], and 1.2 [1.1-1.4], respectively), provided they included practical help that emphasized problem solving and skills training, as well as social support. The benefits of a team-based approach were evident from the finding that counseling provided by more than one type of clinician had higher effect sizes (OR=2.5 [1.9-3.4] when 2 different clinical disciplines were involved and 2.4 [2.1-2.9] for 3 or more disciplines).4
The guideline also found state-sponsored quit lines, accessible at no charge via 800-QUIT-NOW, are an effective option. (For more information about this and other resources, see TABLE W2.)
For patients who aren’t ready to stop smoking, the guideline recommends motivational interviewing4—a direct, patient-centered technique used to explore and work through ambivalence. Further information about this method is available at motivational interviewing.org/.
In counseling patients considering a quit attempt, it is important to present all options. A smoking history is needed, too, because factors such as the number of cigarettes smoked per day, how long a patient is typically awake before smoking the first cigarette of the day, and level of dependence are important factors in determining medication and dosage. Consider the advantages and disadvantages of the various medications (TABLE 2)4,6,7 or methods used for prior quit attempts and reasons for relapse, if appropriate; and patient preference.
Evidence update: What's best?
Since 2009, many clinical trials have examined the best way to help smokers quit. Here’s a closer look at the latest evidence.
NRT boosts long-term cessation
A 2012 Cochrane review examined 150 trials and found that every type of NRT—gum, lozenge, patch, inhaler, and nasal spray—was associated with long-term cessation (relative risk [RR]=1.60; 95% CI, 1.53-1.68).8 This effect was essentially unchanged regardless of the duration, setting, or intensity of supportive therapy offered, and no single type of NRT was more effective than any other. However, combining a short-acting form like a lozenge with a long-acting patch was found to be more effective than either one alone (RR=1.34; 95% CI, 1.18-1.51).
Starting the NRT before the patient quit did not improve cessation rates over traditional start times (RR=1.18; 95% CI 0.98-1.41). Neither was there an added benefit to using NRT beyond the recommended 24-week prescription period,9 although doing so was found to be safe. Another 2012 Cochrane review looked specifically at the use of pharmacologic smoking cessation interventions during pregnancy and concluded that there was still not sufficient data to document efficacy for this patient population.10
Adherence. In deciding on which type of NRT to prescribe, it is important to consider not only patient preference and previous efforts, but also the latest evidence. A study comparing various NRT formulations found patient adherence to be highest with the patch, followed by nicotine gum, which had a higher compliance rate than either the nicotine inhaler or nasal spray.11
Varenicline is still a first-line agent
Since the 2008 guideline recommended this partial nicotinic receptor agonist/antagonist as a first-line pharmacologic agent, additional meta-analyses have confirmed its long-term efficacy in smokers who are ready to quit.12,13 A 2012 Cochrane review found varenicline to increase long-term cessation compared with placebo (RR=2.27; 95% CI, 2.02-2.55).13 It also showed varenicline to be more effective than bupropion SR (RR=1.52; 95% CI, 1.22-1.88), but about as effective as NRT (RR=1.13; 95% CI, 0.94-1.35).
Newer data suggest that varenicline may also be effective for those who are willing to cut down on smoking but not yet ready to give up cigarettes completely. Used for 24 weeks by those who were initially resistant to quitting, researchers found varenicline nearly tripled the cessation rate at 52 weeks compared with placebo (RR=2.7; 95% CI, 2.1-3.5).14
Latest evidence on safety. Additional concerns about the safety of varenicline have been raised, however, since the 2008 guideline was published. In 2009, the US Food and Drug Administration (FDA) required that black box warnings be added to the labels of both varenicline and bupropion SR based on post-marketing safety reports showing the risk of neuropsychiatric symptoms, including suicidality.15 In 2011, a large case control study by the FDA Adverse Event Reporting System also showed an increased risk of suicidality in patients taking these drugs.16
Follow-up studies, however, including a large prospective cohort study and a large meta-analysis, failed to show an increased association with neuropsychiatric adverse effects.17,18 A smaller randomized controlled trial (RCT) showed that in smokers diagnosed with schizophrenia and bipolar disorder, maintenance therapy with varenicline was effective in preventing smoking relapse for up to 52 weeks. Abstinence rates were 60% for those in the varenicline group vs 19% for those in the placebo group (OR=6.2; 95% CI, 2.2-19.2). Although no increased risk of adverse psychiatric events was found in this study, it was not powered to detect them.19 Also of note: a meta-analysis of 14 RCTs showed an increased rate of cardiovascular events associated with varenicline.20 There are concerns about methodologic flaws in this meta-analysis, however, and 2 subsequent meta-analyses failed to find a cardiovascular risk.21,22
The higher quality studies that have been published since the original concerns about varenicline's safety are reassuring, but it is still essential to carefully weigh the risks and benefits of varenicline. Review cardiac and psychiatric history and conduct a suicidality assessment before prescribing it as a smoking cessation aid, and provide close follow-up.
A closer look at antidepressants
Bupropion SR, an atypical antidepressant, was also listed as a first-line treatment in the 2008 guideline. A 2014 Cochrane review of 90 studies confirmed the evidence for this recommendation.6 Monotherapy with this agent was found to significantly increase rates of long-term cessation (RR=1.62; 95% CI, 1.49-1.76). No increased risk of serious adverse events was identified compared with placebo. As already noted, associations with neuropsychiatric symptoms were found, but this risk must be considered with any antidepressant.
Bupropion’s efficacy was not significantly different from that of NRT, but moderate evidence suggests that it is less effective than varenicline, (RR=0.68; 95% CI, 0.56-0.83). Other classes of antidepressants, including selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors, and monoamine oxidase inhibitors, were found to be ineffective for smoking cessation.6
Nortriptyline, a tricyclic antidepressant, was not significantly different from bupropion SR (RR, 1.30; 95% CI, 0.93-1.82) in efficacy for smoking cessation, but it lacks FDA approval for this purpose and is not considered a first-line agent.6
Second-line agents
Clonidine is an alpha-2 adrenergic receptor agonist that was originally used to treat hypertension but found to be effective for smoking cessation in a meta-analysis performed for the 2008 guideline.4 Like nortriptyline, however, clonidine is not FDA-approved for this purpose and is not considered a first-line agent.5 A 2013 Cochrane meta-analysis further showed that clonidine is effective for smoking cessation vs placebo (RR=1.63; 95% CI, 1.22-2.18),7 but suggested that its significant dose-related adverse effects, including postural hypotension and sedation, could limit its usefulness.
Combination therapies are highly effective
Evidence for various combinations of smoking cessation pharmacotherapy continues to mount.23-26 Perhaps the most compelling evidence comes from a comparative effectiveness trial that randomized 1346 patients in 12 primary care clinics to nicotine patches, nicotine lozenges, bupropion SR, a combination of patch plus lozenge, and bupropion SR plus lozenge. The 6-month abstinence rate was 30% for the bupropion SR plus lozenge combination, the most effective option. The combination was superior to either patch or bupropion SR monotherapy (OR, 0.56 and 0.54, respectively).23 Based on data from the 2008 guideline, similar combinations (eg, nicotine patch plus nicotine gum or bupropion SR plus the patch) are likely to be equally effective. The 2008 guideline also supports a nicotine patch and nicotine inhaler combination.
Another study found varenicline combined with the patch to be highly effective, with a 65% abstinence rate at 24 weeks vs 47% for varenicline alone (number needed to treat [NNT]=6; 95% CI, 4-11).24
In heavy smokers—defined as those who smoke ≥20 cigarettes daily—a varenicline and bupropion SR combination was more effective than varenicline alone (NNT= 9; 95% CI, 4.6-71.6), but the combination can lead to increased anxiety and depression.25 A smaller study found triple therapy using nicotine patch plus inhaler plus bupropion SR to be more effective than the nicotine patch alone (35% abstinence vs 19% abstinence at 26 weeks; NNT=6).26 Consider using these combinations in patients who have high nicotine dependency levels or have been unable to quit using a single first-line agent.
What role do e-cigarettes play?
The use of electronic cigarettes or “vapes”—battery-operated devices that deliver nicotine to the user through vapor—has increased significantly since their US introduction in 2007. A recent study found that “ever use” of e-cigarettes increased from 1.8% in 2010 to 13% in 2013; current use increased from 0.3% to 6.8% in the same time frame.27 “Vaping,” as inhaling on an e-cigarette is sometimes known, causes a sensor to detect airflow and initiate the heating element to vaporize the liquid solution within the cartridge, which contains propylene glycol, flavoring, and nicotine.
There is limited evidence of the efficacy of e-cigarettes for smoking cessation, but there is support for their role in reducing the quantity of conventional cigarettes smoked. A 2014 Cochrane review of 2 RCTs evaluating e-cigarette efficacy for smoking cessation or reduction found evidence of increased abstinence at 6 months in users of e-cigarettes containing nicotine compared with placebo e-cigarettes (9% vs 4%; RR=2.29; 95% CI, 1.05-4.96). Additionally, e-cigarette use was associated with >50% decrease in cigarette smoking vs placebo (36% vs 27%; RR=1.31; 95% CI, 1.02-1.68) or patch (61% vs 44%; RR=1.41; 95% CI, 1.20-1.67).28
A survey published after the review also showed a correlation between cigarette reduction (but not cessation) after one year of e-cigarette use.29 A subsequent RCT conducted in a controlled laboratory setting found that e-cigarettes were highly effective in reducing cessation-related cravings.30 And at 8-month follow-up, 44% of those using e-cigarettes were found to have at least a 50% reduction in the use of conventional cigarettes—and complete cessation in some cases.
Concerns about health effects
E-cigarettes have generally been thought to be safer than conventional cigarettes, given that they mainly deliver nicotine and propylene glycol instead of the more toxic chemicals—eg, benzene, carbon monoxide, and formaldehyde—released by conventional cigarettes.31 Carcinogens have also been found in e-cigarettes, but at significantly lower levels.31 However, a systematic review found wide variation in the toxin content of e-cigarettes.32 In addition, recent reports have detailed incidents in which e-cigarette devices were alleged to have exploded, causing severe bodily harm.33
Adverse effects of e-cigarettes include minor irritation of the throat, mouth, and lungs. Among cigarette-naive patients, light-headedness, throat irritation, dizziness, and cough were most commonly reported. No serious adverse events have been reported, but the lack of long-term safety data is a source of concern.32
Additionally, minimal regulatory oversight of the e-cigarette industry exists. Currently, the FDA only has authority to regulate e-cigarettes that are marketed for therapeutic purposes, although the agency is seeking to extend its oversight to all e-cigarettes.
The bottom line: More data on safety and regulatory oversight are needed before recommendations on the use of e-cigarettes as a smoking cessation tool can be made.
Looking ahead
Several novel pharmacotherapies have been evaluated for smoking cessation in recent years. Among them is a nicotine vaccine that several drug companies have been pursuing. In theory, such a vaccine would create an immunologic reaction to nicotine in a smoker, thereby preventing the substance from reaching the brain and providing rewarding stimuli. A 2008 Cochrane review of 4 trials assessing the efficacy of nicotine vaccines for tobacco cessation found that none showed efficacy.34
Naltrexone, an opioid antagonist, has shown efficacy in helping those with opioid or alcohol dependence achieve abstinence from these substances, raising the possibility that it might aid in smoking cessation, as well. A 2013 Cochrane review of 8 trials found that this was not the case: Compared with placebo, naltrexone was not beneficial when used alone (RR=1.00; 95% CI, 0.66-1.51) or as an adjunct to NRT compared with NRT alone (RR=0.95; 95% CI, 0.70-1.30).35
Cytisine, an extract from plants in the Faboideae family, has been used in Eastern Europe for decades for smoking cessation. It appears to work as a nicotine receptor partial agonist similar to varenicline. The extract does not have FDA approval, but the National Institutes of Health’s Center for Complementary and Integrative Health is sponsoring early-stage safety trials that could lead to its approval in the United States.36
A 2012 Cochrane review identified 2 recent RCTs evaluating cytisine and found it to be effective in increasing smoking cessation rates vs placebo (RR=3.98; 95% CI, 2.01-7.87).13
CORRESPONDENCE
Paul Bornemann, MD, 3209 Colonial Drive, Columbia, SC 29203; [email protected].
ACKNOWLEDGEMENT
The authors thank Matt Orr, PhD, and Kathryn E. Bornemann for their help with this manuscript.
1. National Center for Chronic Disease Prevention and Health Promotion Office on Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. 2014. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24455788. Accessed October 21, 2015.
2. Smoking-attributable mortality, years of potential life lost, and productivity losses—United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2008;57:1226-1228.
3. Doll R, Peto R, Boreham J, et al. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ. 2004;328:1519.
4. US Public Health Service. A clinical practice guideline for treating tobacco use and dependence: 2008 update. A US Public Health Service Report. Am J Prev Med. 2008;35:158-176.
5. US Preventive Services Task Force. Tobacco use in adults and pregnant women: Counseling and interventions. April 2009. Available at: http://www.uspreventiveservicestaskforce.org/Page/Topic/recommendation-summary/tobacco-use-in-adults-and-pregnant-women-counseling-and-interventions. Accessed October 21, 2015.
6. Hughes JR, Stead LF, Hartmann-Boyce J, et al. Antidepressants for smoking cessation. Cochrane Database Syst Rev. 2014;(1):CD000031.
7. Cahill K, Stevens S, Perera R, et al. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;(5):CD009329.
8. Stead LF, Perera R, Bullen C, et al. Nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev. 2012;(11):CD000146.
9. Schnoll RA, Goelz PM, Veluz-Wilkins A, et al. Long-term nicotine replacement therapy: a randomized clinical trial. JAMA Intern Med. 2015;175:504-511.
10. Coleman T, Chamberlain C, Davey MA, et al. Pharmacological interventions for promoting smoking cessation during pregnancy. Cochrane Database Syst Rev. 2012;(9):CD010078.
11. Hajek P, West R, Foulds J, et al. Randomized comparative trial of nicotine polacrilex, a transdermal patch, nasal spray, and an inhaler. Arch Intern Med. 1999;159:2033-2038.
12. Eisenberg MJ, Filion KB, Yavin D, et al. Pharmacotherapies for smoking cessation: a meta-analysis of randomized controlled trials. CMAJ. 2008;179:135-144.
13. Cahill K, Stead LF, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev. 2012;(4):CD006103.
14. Ebbert JO, Hughes JR, West RJ, et al. Effect of varenicline on smoking cessation through smoking reduction: a randomized clinical trial. JAMA. 2015;313:687-694.
15. US Food and Drug Administration. Reports of suicidality associated with use of varenicline (marketed as CHANTIX) and bupropion (marketed as ZYBAN and GENERICS). FDA Drug Safety News. 2009.
16. Moore TJ, Furberg CD, Glenmullen J, et al. Suicidal behavior and depression in smoking cessation treatments. PLoS One. 2011;6:e27016.
17. Thomas KH, Martin RM, Davies NM, et al. Smoking cessation treatment and risk of depression, suicide, and self harm in the Clinical Practice Research Datalink: prospective cohort study. BMJ. 2013;347:f5704.
18. Thomas KH, Martin RM, Knipe DW, et al. Risk of neuropsychiatric adverse events associated with varenicline: systematic review and meta-analysis. BMJ. 2015;350:h1109.
19. Evins AE, Cather C, Pratt SA, et al. Maintenance treatment with varenicline for smoking cessation in patients with schizophrenia and bipolar disorder: a randomized clinical trial. JAMA. 2014;311:145-154.
20. Singh S, Loke YK, Spangler JG, et al. Risk of serious adverse cardiovascular events associated with varenicline: a systematic review and meta-analysis. CMAJ. 2011;183:1359-1366.
21. Prochaska JJ, Hilton JF. Risk of cardiovascular serious adverse events associated with varenicline use for tobacco cessation: systematic review and meta-analysis. BMJ. 2012;344:e2856.
22. Svanström H, Pasternak B, Hviid A. Use of varenicline for smoking cessation and risk of serious cardiovascular events: nationwide cohort study. BMJ. 2012;345:e7176.
23. Smith SS, McCarthy DE, Japuntich SJ, et al. Comparative effectiveness of five smoking cessation pharmacotherapies in primary care clinics. Arch Intern Med. 2009;169:2148–2155.
24. Koegelenberg CFN, Noor F, Bateman ED, et al. Efficacy of varenicline combined with nicotine replacement therapy vs varenicline alone for smoking cessation. JAMA. 2014;312:155-161.
25. Ebbert JO, Hatsukami DK, Croghan IT, et al. Combination varenicline and bupropion SR for tobacco-dependence treatment in cigarette smokers: a randomized trial. JAMA. 2014;311:155-163.
26. Steinberg MB, Greenhaus S, Schmelzer AC, et al. Triple-combination pharmacotherapy for medically ill smokers: A randomized trial. Ann Intern Med. 2009;150:447-454.
27. McMillen RC, Gottlieb MA, Shaefer RMW, et al. Trends in electronic cigarette use among US. adults: use is increasing in both smokers and nonsmokers. Nicotine Tob Res. 2015;17:1195-1202.
28. McRobbie H, Bullen C, Hartmann-Boyce J, et al. Electronic cigarettes for smoking cessation and reduction. Cochrane Database Syst Rev. 2014;(12):CD010216.
29. Brose LS, Hitchman SC, Brown J, et al. Is the use of electronic cigarettes while smoking associated with smoking cessation attempts, cessation and reduced cigarette consumption? A survey with a 1-year follow-up. Addiction. 2015;110:1160-1168.
30. Adriaens K, Van Gucht D, Declerck P, et al. Effectiveness of the electronic cigarette: an eight-week Flemish study with six-month follow-up on smoking reduction, craving and experienced benefits and complaints. Int J Environ Res Public Health. 2014;11:11220-11248.
31. Goniewicz ML, Knysak J, Gawron M, et al. Levels of selected carcinogens and toxicants in vapour from electronic cigarettes. Tob Control. 2014;23:133-139.
32. Pisinger C, Døssing M. A systematic review of health effects of electronic cigarettes. Prev Med (Baltim). 2014;69C:248-260.
33. Bowerman M. Fla. man hospitalized after e-cigarette explodes in face. USA Today Network. October 29, 2015. Available at: http:// www.usatoday.com/story/news/nation-now/2015/10/29/fla-man-hospitalized-e-cigarette-explodes-face/74791722/. Accessed December 2, 2015.
34. Hatsukami D, Cahill K, Stead LF. Nicotine vaccines for smoking cessation. Cochrane Database Syst Rev. 2008;(2):CD007072.
35. David SP, Lancaster T, Stead LF, et al. Opioid antagonists for smoking cessation. Cochrane Database Syst Rev. 2013;(6):CD003086.
36. Frankel T. Pill that quashes tobacco urge found in plain sight. Washington Post. May 15, 2015. Available at: http://www.washingtonpost.com/business/economy/pill-promises-a-safercheaper-way-than-chantix-to-quit-smoking/2015/05/15/8ce5590c-f830-11e4-9030-b4732caefe81_story.html. Accessed August 3, 2015.
› Prescribe varenicline, bupropion, or nicotine replacement as first-line single pharmacotherapy for smoking cessation. A
› Provide counseling along with medication, as the combination has proven to be more effective than either option alone. A
› Refer patients to their state Quit Line—a toll-free tobacco cessation coaching service that has been shown to be an effective form of counseling. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
In its 2014 report, “The Health Consequences of Smoking—50 Years of Progress,”1 the US Surgeon General concluded that, while significant improvements have been made since the publication of its landmark 1964 report, cigarette smoking remains a major public health problem. It is the leading cause of preventable death, increasing the risks of such common causes of mortality as cardiovascular disease, pulmonary disease, and malignancy. Cigarette smoking is responsible for an estimated 443,000 deaths annually.2
Overall, 42 million US adults and about 3 million middle and high school students smoke, despite the availability of an array of pharmacologic interventions to help them quit.1 Half of those who continue to smoke will die from a tobacco-related cause. Stopping before the age of 50 years cuts the risk in half, and quitting before age 30 almost completely negates it.3
The most recent comprehensive smoking cessation guideline, sponsored by the US Public Health Service, was published in 2008.4 The US Preventive Services Task Force (USPSTF) recommendation that “clinicians ask all adults about tobacco use and provide tobacco cessation interventions” for those who smoke was issued one year later.5 Since then, multiple studies have assessed the merits of the various medications, forms of nicotine replacement therapy (NRT), and counseling aimed at helping smokers maintain abstinence from tobacco.
This article reviews the guideline and provides family physicians with an evidence-based update.
The guideline: Treating tobacco use and dependence
Prescribing a first-line medication (bupropion SR, varenicline, nicotine gum, nicotine inhaler, nicotine lozenge, nicotine nasal spray, or nicotine patch) for every patient who seeks to quit smoking is a key component of the 2008 guideline (See TABLE W1).4 The only exceptions: patients for whom such agents are medically contraindicated and groups for which there is insufficient evidence of effectiveness, such as pregnant women and adolescents.
The use of any of these medications as a single agent nearly doubles the likelihood of success compared with placebo, with an average cessation rate of 25% (TABLE 1).4
Combination therapy (pairing a nicotine patch and an additional agent) was found to be even more effective, with some combinations attaining success rates as high as 65%.4
Second-line therapies, including clonidine and nortriptyline, were also cited as effective, with an average cessation rate of 24%.4 Although the meta-analyses that these averages were based on did not include head-to-head comparisons, subsequent studies that also showed efficacy did include such comparisons.
Counseling is an essential component
In one of the meta-analyses on which the guideline was based, the combination of counseling and medication proved to be more effective than either intervention alone. Individual, group, and telephone counseling were all effective (odds ratio [OR]=1.7 [1.4-2.0], 1.3 [1.1-1.6], and 1.2 [1.1-1.4], respectively), provided they included practical help that emphasized problem solving and skills training, as well as social support. The benefits of a team-based approach were evident from the finding that counseling provided by more than one type of clinician had higher effect sizes (OR=2.5 [1.9-3.4] when 2 different clinical disciplines were involved and 2.4 [2.1-2.9] for 3 or more disciplines).4
The guideline also found state-sponsored quit lines, accessible at no charge via 800-QUIT-NOW, are an effective option. (For more information about this and other resources, see TABLE W2.)
For patients who aren’t ready to stop smoking, the guideline recommends motivational interviewing4—a direct, patient-centered technique used to explore and work through ambivalence. Further information about this method is available at motivational interviewing.org/.
In counseling patients considering a quit attempt, it is important to present all options. A smoking history is needed, too, because factors such as the number of cigarettes smoked per day, how long a patient is typically awake before smoking the first cigarette of the day, and level of dependence are important factors in determining medication and dosage. Consider the advantages and disadvantages of the various medications (TABLE 2)4,6,7 or methods used for prior quit attempts and reasons for relapse, if appropriate; and patient preference.
Evidence update: What's best?
Since 2009, many clinical trials have examined the best way to help smokers quit. Here’s a closer look at the latest evidence.
NRT boosts long-term cessation
A 2012 Cochrane review examined 150 trials and found that every type of NRT—gum, lozenge, patch, inhaler, and nasal spray—was associated with long-term cessation (relative risk [RR]=1.60; 95% CI, 1.53-1.68).8 This effect was essentially unchanged regardless of the duration, setting, or intensity of supportive therapy offered, and no single type of NRT was more effective than any other. However, combining a short-acting form like a lozenge with a long-acting patch was found to be more effective than either one alone (RR=1.34; 95% CI, 1.18-1.51).
Starting the NRT before the patient quit did not improve cessation rates over traditional start times (RR=1.18; 95% CI 0.98-1.41). Neither was there an added benefit to using NRT beyond the recommended 24-week prescription period,9 although doing so was found to be safe. Another 2012 Cochrane review looked specifically at the use of pharmacologic smoking cessation interventions during pregnancy and concluded that there was still not sufficient data to document efficacy for this patient population.10
Adherence. In deciding on which type of NRT to prescribe, it is important to consider not only patient preference and previous efforts, but also the latest evidence. A study comparing various NRT formulations found patient adherence to be highest with the patch, followed by nicotine gum, which had a higher compliance rate than either the nicotine inhaler or nasal spray.11
Varenicline is still a first-line agent
Since the 2008 guideline recommended this partial nicotinic receptor agonist/antagonist as a first-line pharmacologic agent, additional meta-analyses have confirmed its long-term efficacy in smokers who are ready to quit.12,13 A 2012 Cochrane review found varenicline to increase long-term cessation compared with placebo (RR=2.27; 95% CI, 2.02-2.55).13 It also showed varenicline to be more effective than bupropion SR (RR=1.52; 95% CI, 1.22-1.88), but about as effective as NRT (RR=1.13; 95% CI, 0.94-1.35).
Newer data suggest that varenicline may also be effective for those who are willing to cut down on smoking but not yet ready to give up cigarettes completely. Used for 24 weeks by those who were initially resistant to quitting, researchers found varenicline nearly tripled the cessation rate at 52 weeks compared with placebo (RR=2.7; 95% CI, 2.1-3.5).14
Latest evidence on safety. Additional concerns about the safety of varenicline have been raised, however, since the 2008 guideline was published. In 2009, the US Food and Drug Administration (FDA) required that black box warnings be added to the labels of both varenicline and bupropion SR based on post-marketing safety reports showing the risk of neuropsychiatric symptoms, including suicidality.15 In 2011, a large case control study by the FDA Adverse Event Reporting System also showed an increased risk of suicidality in patients taking these drugs.16
Follow-up studies, however, including a large prospective cohort study and a large meta-analysis, failed to show an increased association with neuropsychiatric adverse effects.17,18 A smaller randomized controlled trial (RCT) showed that in smokers diagnosed with schizophrenia and bipolar disorder, maintenance therapy with varenicline was effective in preventing smoking relapse for up to 52 weeks. Abstinence rates were 60% for those in the varenicline group vs 19% for those in the placebo group (OR=6.2; 95% CI, 2.2-19.2). Although no increased risk of adverse psychiatric events was found in this study, it was not powered to detect them.19 Also of note: a meta-analysis of 14 RCTs showed an increased rate of cardiovascular events associated with varenicline.20 There are concerns about methodologic flaws in this meta-analysis, however, and 2 subsequent meta-analyses failed to find a cardiovascular risk.21,22
The higher quality studies that have been published since the original concerns about varenicline's safety are reassuring, but it is still essential to carefully weigh the risks and benefits of varenicline. Review cardiac and psychiatric history and conduct a suicidality assessment before prescribing it as a smoking cessation aid, and provide close follow-up.
A closer look at antidepressants
Bupropion SR, an atypical antidepressant, was also listed as a first-line treatment in the 2008 guideline. A 2014 Cochrane review of 90 studies confirmed the evidence for this recommendation.6 Monotherapy with this agent was found to significantly increase rates of long-term cessation (RR=1.62; 95% CI, 1.49-1.76). No increased risk of serious adverse events was identified compared with placebo. As already noted, associations with neuropsychiatric symptoms were found, but this risk must be considered with any antidepressant.
Bupropion’s efficacy was not significantly different from that of NRT, but moderate evidence suggests that it is less effective than varenicline, (RR=0.68; 95% CI, 0.56-0.83). Other classes of antidepressants, including selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors, and monoamine oxidase inhibitors, were found to be ineffective for smoking cessation.6
Nortriptyline, a tricyclic antidepressant, was not significantly different from bupropion SR (RR, 1.30; 95% CI, 0.93-1.82) in efficacy for smoking cessation, but it lacks FDA approval for this purpose and is not considered a first-line agent.6
Second-line agents
Clonidine is an alpha-2 adrenergic receptor agonist that was originally used to treat hypertension but found to be effective for smoking cessation in a meta-analysis performed for the 2008 guideline.4 Like nortriptyline, however, clonidine is not FDA-approved for this purpose and is not considered a first-line agent.5 A 2013 Cochrane meta-analysis further showed that clonidine is effective for smoking cessation vs placebo (RR=1.63; 95% CI, 1.22-2.18),7 but suggested that its significant dose-related adverse effects, including postural hypotension and sedation, could limit its usefulness.
Combination therapies are highly effective
Evidence for various combinations of smoking cessation pharmacotherapy continues to mount.23-26 Perhaps the most compelling evidence comes from a comparative effectiveness trial that randomized 1346 patients in 12 primary care clinics to nicotine patches, nicotine lozenges, bupropion SR, a combination of patch plus lozenge, and bupropion SR plus lozenge. The 6-month abstinence rate was 30% for the bupropion SR plus lozenge combination, the most effective option. The combination was superior to either patch or bupropion SR monotherapy (OR, 0.56 and 0.54, respectively).23 Based on data from the 2008 guideline, similar combinations (eg, nicotine patch plus nicotine gum or bupropion SR plus the patch) are likely to be equally effective. The 2008 guideline also supports a nicotine patch and nicotine inhaler combination.
Another study found varenicline combined with the patch to be highly effective, with a 65% abstinence rate at 24 weeks vs 47% for varenicline alone (number needed to treat [NNT]=6; 95% CI, 4-11).24
In heavy smokers—defined as those who smoke ≥20 cigarettes daily—a varenicline and bupropion SR combination was more effective than varenicline alone (NNT= 9; 95% CI, 4.6-71.6), but the combination can lead to increased anxiety and depression.25 A smaller study found triple therapy using nicotine patch plus inhaler plus bupropion SR to be more effective than the nicotine patch alone (35% abstinence vs 19% abstinence at 26 weeks; NNT=6).26 Consider using these combinations in patients who have high nicotine dependency levels or have been unable to quit using a single first-line agent.
What role do e-cigarettes play?
The use of electronic cigarettes or “vapes”—battery-operated devices that deliver nicotine to the user through vapor—has increased significantly since their US introduction in 2007. A recent study found that “ever use” of e-cigarettes increased from 1.8% in 2010 to 13% in 2013; current use increased from 0.3% to 6.8% in the same time frame.27 “Vaping,” as inhaling on an e-cigarette is sometimes known, causes a sensor to detect airflow and initiate the heating element to vaporize the liquid solution within the cartridge, which contains propylene glycol, flavoring, and nicotine.
There is limited evidence of the efficacy of e-cigarettes for smoking cessation, but there is support for their role in reducing the quantity of conventional cigarettes smoked. A 2014 Cochrane review of 2 RCTs evaluating e-cigarette efficacy for smoking cessation or reduction found evidence of increased abstinence at 6 months in users of e-cigarettes containing nicotine compared with placebo e-cigarettes (9% vs 4%; RR=2.29; 95% CI, 1.05-4.96). Additionally, e-cigarette use was associated with >50% decrease in cigarette smoking vs placebo (36% vs 27%; RR=1.31; 95% CI, 1.02-1.68) or patch (61% vs 44%; RR=1.41; 95% CI, 1.20-1.67).28
A survey published after the review also showed a correlation between cigarette reduction (but not cessation) after one year of e-cigarette use.29 A subsequent RCT conducted in a controlled laboratory setting found that e-cigarettes were highly effective in reducing cessation-related cravings.30 And at 8-month follow-up, 44% of those using e-cigarettes were found to have at least a 50% reduction in the use of conventional cigarettes—and complete cessation in some cases.
Concerns about health effects
E-cigarettes have generally been thought to be safer than conventional cigarettes, given that they mainly deliver nicotine and propylene glycol instead of the more toxic chemicals—eg, benzene, carbon monoxide, and formaldehyde—released by conventional cigarettes.31 Carcinogens have also been found in e-cigarettes, but at significantly lower levels.31 However, a systematic review found wide variation in the toxin content of e-cigarettes.32 In addition, recent reports have detailed incidents in which e-cigarette devices were alleged to have exploded, causing severe bodily harm.33
Adverse effects of e-cigarettes include minor irritation of the throat, mouth, and lungs. Among cigarette-naive patients, light-headedness, throat irritation, dizziness, and cough were most commonly reported. No serious adverse events have been reported, but the lack of long-term safety data is a source of concern.32
Additionally, minimal regulatory oversight of the e-cigarette industry exists. Currently, the FDA only has authority to regulate e-cigarettes that are marketed for therapeutic purposes, although the agency is seeking to extend its oversight to all e-cigarettes.
The bottom line: More data on safety and regulatory oversight are needed before recommendations on the use of e-cigarettes as a smoking cessation tool can be made.
Looking ahead
Several novel pharmacotherapies have been evaluated for smoking cessation in recent years. Among them is a nicotine vaccine that several drug companies have been pursuing. In theory, such a vaccine would create an immunologic reaction to nicotine in a smoker, thereby preventing the substance from reaching the brain and providing rewarding stimuli. A 2008 Cochrane review of 4 trials assessing the efficacy of nicotine vaccines for tobacco cessation found that none showed efficacy.34
Naltrexone, an opioid antagonist, has shown efficacy in helping those with opioid or alcohol dependence achieve abstinence from these substances, raising the possibility that it might aid in smoking cessation, as well. A 2013 Cochrane review of 8 trials found that this was not the case: Compared with placebo, naltrexone was not beneficial when used alone (RR=1.00; 95% CI, 0.66-1.51) or as an adjunct to NRT compared with NRT alone (RR=0.95; 95% CI, 0.70-1.30).35
Cytisine, an extract from plants in the Faboideae family, has been used in Eastern Europe for decades for smoking cessation. It appears to work as a nicotine receptor partial agonist similar to varenicline. The extract does not have FDA approval, but the National Institutes of Health’s Center for Complementary and Integrative Health is sponsoring early-stage safety trials that could lead to its approval in the United States.36
A 2012 Cochrane review identified 2 recent RCTs evaluating cytisine and found it to be effective in increasing smoking cessation rates vs placebo (RR=3.98; 95% CI, 2.01-7.87).13
CORRESPONDENCE
Paul Bornemann, MD, 3209 Colonial Drive, Columbia, SC 29203; [email protected].
ACKNOWLEDGEMENT
The authors thank Matt Orr, PhD, and Kathryn E. Bornemann for their help with this manuscript.
› Prescribe varenicline, bupropion, or nicotine replacement as first-line single pharmacotherapy for smoking cessation. A
› Provide counseling along with medication, as the combination has proven to be more effective than either option alone. A
› Refer patients to their state Quit Line—a toll-free tobacco cessation coaching service that has been shown to be an effective form of counseling. A
Strength of recommendation (SOR)
A Good-quality patient-oriented evidence
B Inconsistent or limited-quality patient-oriented evidence
C Consensus, usual practice, opinion, disease-oriented evidence, case series
In its 2014 report, “The Health Consequences of Smoking—50 Years of Progress,”1 the US Surgeon General concluded that, while significant improvements have been made since the publication of its landmark 1964 report, cigarette smoking remains a major public health problem. It is the leading cause of preventable death, increasing the risks of such common causes of mortality as cardiovascular disease, pulmonary disease, and malignancy. Cigarette smoking is responsible for an estimated 443,000 deaths annually.2
Overall, 42 million US adults and about 3 million middle and high school students smoke, despite the availability of an array of pharmacologic interventions to help them quit.1 Half of those who continue to smoke will die from a tobacco-related cause. Stopping before the age of 50 years cuts the risk in half, and quitting before age 30 almost completely negates it.3
The most recent comprehensive smoking cessation guideline, sponsored by the US Public Health Service, was published in 2008.4 The US Preventive Services Task Force (USPSTF) recommendation that “clinicians ask all adults about tobacco use and provide tobacco cessation interventions” for those who smoke was issued one year later.5 Since then, multiple studies have assessed the merits of the various medications, forms of nicotine replacement therapy (NRT), and counseling aimed at helping smokers maintain abstinence from tobacco.
This article reviews the guideline and provides family physicians with an evidence-based update.
The guideline: Treating tobacco use and dependence
Prescribing a first-line medication (bupropion SR, varenicline, nicotine gum, nicotine inhaler, nicotine lozenge, nicotine nasal spray, or nicotine patch) for every patient who seeks to quit smoking is a key component of the 2008 guideline (See TABLE W1).4 The only exceptions: patients for whom such agents are medically contraindicated and groups for which there is insufficient evidence of effectiveness, such as pregnant women and adolescents.
The use of any of these medications as a single agent nearly doubles the likelihood of success compared with placebo, with an average cessation rate of 25% (TABLE 1).4
Combination therapy (pairing a nicotine patch and an additional agent) was found to be even more effective, with some combinations attaining success rates as high as 65%.4
Second-line therapies, including clonidine and nortriptyline, were also cited as effective, with an average cessation rate of 24%.4 Although the meta-analyses that these averages were based on did not include head-to-head comparisons, subsequent studies that also showed efficacy did include such comparisons.
Counseling is an essential component
In one of the meta-analyses on which the guideline was based, the combination of counseling and medication proved to be more effective than either intervention alone. Individual, group, and telephone counseling were all effective (odds ratio [OR]=1.7 [1.4-2.0], 1.3 [1.1-1.6], and 1.2 [1.1-1.4], respectively), provided they included practical help that emphasized problem solving and skills training, as well as social support. The benefits of a team-based approach were evident from the finding that counseling provided by more than one type of clinician had higher effect sizes (OR=2.5 [1.9-3.4] when 2 different clinical disciplines were involved and 2.4 [2.1-2.9] for 3 or more disciplines).4
The guideline also found state-sponsored quit lines, accessible at no charge via 800-QUIT-NOW, are an effective option. (For more information about this and other resources, see TABLE W2.)
For patients who aren’t ready to stop smoking, the guideline recommends motivational interviewing4—a direct, patient-centered technique used to explore and work through ambivalence. Further information about this method is available at motivational interviewing.org/.
In counseling patients considering a quit attempt, it is important to present all options. A smoking history is needed, too, because factors such as the number of cigarettes smoked per day, how long a patient is typically awake before smoking the first cigarette of the day, and level of dependence are important factors in determining medication and dosage. Consider the advantages and disadvantages of the various medications (TABLE 2)4,6,7 or methods used for prior quit attempts and reasons for relapse, if appropriate; and patient preference.
Evidence update: What's best?
Since 2009, many clinical trials have examined the best way to help smokers quit. Here’s a closer look at the latest evidence.
NRT boosts long-term cessation
A 2012 Cochrane review examined 150 trials and found that every type of NRT—gum, lozenge, patch, inhaler, and nasal spray—was associated with long-term cessation (relative risk [RR]=1.60; 95% CI, 1.53-1.68).8 This effect was essentially unchanged regardless of the duration, setting, or intensity of supportive therapy offered, and no single type of NRT was more effective than any other. However, combining a short-acting form like a lozenge with a long-acting patch was found to be more effective than either one alone (RR=1.34; 95% CI, 1.18-1.51).
Starting the NRT before the patient quit did not improve cessation rates over traditional start times (RR=1.18; 95% CI 0.98-1.41). Neither was there an added benefit to using NRT beyond the recommended 24-week prescription period,9 although doing so was found to be safe. Another 2012 Cochrane review looked specifically at the use of pharmacologic smoking cessation interventions during pregnancy and concluded that there was still not sufficient data to document efficacy for this patient population.10
Adherence. In deciding on which type of NRT to prescribe, it is important to consider not only patient preference and previous efforts, but also the latest evidence. A study comparing various NRT formulations found patient adherence to be highest with the patch, followed by nicotine gum, which had a higher compliance rate than either the nicotine inhaler or nasal spray.11
Varenicline is still a first-line agent
Since the 2008 guideline recommended this partial nicotinic receptor agonist/antagonist as a first-line pharmacologic agent, additional meta-analyses have confirmed its long-term efficacy in smokers who are ready to quit.12,13 A 2012 Cochrane review found varenicline to increase long-term cessation compared with placebo (RR=2.27; 95% CI, 2.02-2.55).13 It also showed varenicline to be more effective than bupropion SR (RR=1.52; 95% CI, 1.22-1.88), but about as effective as NRT (RR=1.13; 95% CI, 0.94-1.35).
Newer data suggest that varenicline may also be effective for those who are willing to cut down on smoking but not yet ready to give up cigarettes completely. Used for 24 weeks by those who were initially resistant to quitting, researchers found varenicline nearly tripled the cessation rate at 52 weeks compared with placebo (RR=2.7; 95% CI, 2.1-3.5).14
Latest evidence on safety. Additional concerns about the safety of varenicline have been raised, however, since the 2008 guideline was published. In 2009, the US Food and Drug Administration (FDA) required that black box warnings be added to the labels of both varenicline and bupropion SR based on post-marketing safety reports showing the risk of neuropsychiatric symptoms, including suicidality.15 In 2011, a large case control study by the FDA Adverse Event Reporting System also showed an increased risk of suicidality in patients taking these drugs.16
Follow-up studies, however, including a large prospective cohort study and a large meta-analysis, failed to show an increased association with neuropsychiatric adverse effects.17,18 A smaller randomized controlled trial (RCT) showed that in smokers diagnosed with schizophrenia and bipolar disorder, maintenance therapy with varenicline was effective in preventing smoking relapse for up to 52 weeks. Abstinence rates were 60% for those in the varenicline group vs 19% for those in the placebo group (OR=6.2; 95% CI, 2.2-19.2). Although no increased risk of adverse psychiatric events was found in this study, it was not powered to detect them.19 Also of note: a meta-analysis of 14 RCTs showed an increased rate of cardiovascular events associated with varenicline.20 There are concerns about methodologic flaws in this meta-analysis, however, and 2 subsequent meta-analyses failed to find a cardiovascular risk.21,22
The higher quality studies that have been published since the original concerns about varenicline's safety are reassuring, but it is still essential to carefully weigh the risks and benefits of varenicline. Review cardiac and psychiatric history and conduct a suicidality assessment before prescribing it as a smoking cessation aid, and provide close follow-up.
A closer look at antidepressants
Bupropion SR, an atypical antidepressant, was also listed as a first-line treatment in the 2008 guideline. A 2014 Cochrane review of 90 studies confirmed the evidence for this recommendation.6 Monotherapy with this agent was found to significantly increase rates of long-term cessation (RR=1.62; 95% CI, 1.49-1.76). No increased risk of serious adverse events was identified compared with placebo. As already noted, associations with neuropsychiatric symptoms were found, but this risk must be considered with any antidepressant.
Bupropion’s efficacy was not significantly different from that of NRT, but moderate evidence suggests that it is less effective than varenicline, (RR=0.68; 95% CI, 0.56-0.83). Other classes of antidepressants, including selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors, and monoamine oxidase inhibitors, were found to be ineffective for smoking cessation.6
Nortriptyline, a tricyclic antidepressant, was not significantly different from bupropion SR (RR, 1.30; 95% CI, 0.93-1.82) in efficacy for smoking cessation, but it lacks FDA approval for this purpose and is not considered a first-line agent.6
Second-line agents
Clonidine is an alpha-2 adrenergic receptor agonist that was originally used to treat hypertension but found to be effective for smoking cessation in a meta-analysis performed for the 2008 guideline.4 Like nortriptyline, however, clonidine is not FDA-approved for this purpose and is not considered a first-line agent.5 A 2013 Cochrane meta-analysis further showed that clonidine is effective for smoking cessation vs placebo (RR=1.63; 95% CI, 1.22-2.18),7 but suggested that its significant dose-related adverse effects, including postural hypotension and sedation, could limit its usefulness.
Combination therapies are highly effective
Evidence for various combinations of smoking cessation pharmacotherapy continues to mount.23-26 Perhaps the most compelling evidence comes from a comparative effectiveness trial that randomized 1346 patients in 12 primary care clinics to nicotine patches, nicotine lozenges, bupropion SR, a combination of patch plus lozenge, and bupropion SR plus lozenge. The 6-month abstinence rate was 30% for the bupropion SR plus lozenge combination, the most effective option. The combination was superior to either patch or bupropion SR monotherapy (OR, 0.56 and 0.54, respectively).23 Based on data from the 2008 guideline, similar combinations (eg, nicotine patch plus nicotine gum or bupropion SR plus the patch) are likely to be equally effective. The 2008 guideline also supports a nicotine patch and nicotine inhaler combination.
Another study found varenicline combined with the patch to be highly effective, with a 65% abstinence rate at 24 weeks vs 47% for varenicline alone (number needed to treat [NNT]=6; 95% CI, 4-11).24
In heavy smokers—defined as those who smoke ≥20 cigarettes daily—a varenicline and bupropion SR combination was more effective than varenicline alone (NNT= 9; 95% CI, 4.6-71.6), but the combination can lead to increased anxiety and depression.25 A smaller study found triple therapy using nicotine patch plus inhaler plus bupropion SR to be more effective than the nicotine patch alone (35% abstinence vs 19% abstinence at 26 weeks; NNT=6).26 Consider using these combinations in patients who have high nicotine dependency levels or have been unable to quit using a single first-line agent.
What role do e-cigarettes play?
The use of electronic cigarettes or “vapes”—battery-operated devices that deliver nicotine to the user through vapor—has increased significantly since their US introduction in 2007. A recent study found that “ever use” of e-cigarettes increased from 1.8% in 2010 to 13% in 2013; current use increased from 0.3% to 6.8% in the same time frame.27 “Vaping,” as inhaling on an e-cigarette is sometimes known, causes a sensor to detect airflow and initiate the heating element to vaporize the liquid solution within the cartridge, which contains propylene glycol, flavoring, and nicotine.
There is limited evidence of the efficacy of e-cigarettes for smoking cessation, but there is support for their role in reducing the quantity of conventional cigarettes smoked. A 2014 Cochrane review of 2 RCTs evaluating e-cigarette efficacy for smoking cessation or reduction found evidence of increased abstinence at 6 months in users of e-cigarettes containing nicotine compared with placebo e-cigarettes (9% vs 4%; RR=2.29; 95% CI, 1.05-4.96). Additionally, e-cigarette use was associated with >50% decrease in cigarette smoking vs placebo (36% vs 27%; RR=1.31; 95% CI, 1.02-1.68) or patch (61% vs 44%; RR=1.41; 95% CI, 1.20-1.67).28
A survey published after the review also showed a correlation between cigarette reduction (but not cessation) after one year of e-cigarette use.29 A subsequent RCT conducted in a controlled laboratory setting found that e-cigarettes were highly effective in reducing cessation-related cravings.30 And at 8-month follow-up, 44% of those using e-cigarettes were found to have at least a 50% reduction in the use of conventional cigarettes—and complete cessation in some cases.
Concerns about health effects
E-cigarettes have generally been thought to be safer than conventional cigarettes, given that they mainly deliver nicotine and propylene glycol instead of the more toxic chemicals—eg, benzene, carbon monoxide, and formaldehyde—released by conventional cigarettes.31 Carcinogens have also been found in e-cigarettes, but at significantly lower levels.31 However, a systematic review found wide variation in the toxin content of e-cigarettes.32 In addition, recent reports have detailed incidents in which e-cigarette devices were alleged to have exploded, causing severe bodily harm.33
Adverse effects of e-cigarettes include minor irritation of the throat, mouth, and lungs. Among cigarette-naive patients, light-headedness, throat irritation, dizziness, and cough were most commonly reported. No serious adverse events have been reported, but the lack of long-term safety data is a source of concern.32
Additionally, minimal regulatory oversight of the e-cigarette industry exists. Currently, the FDA only has authority to regulate e-cigarettes that are marketed for therapeutic purposes, although the agency is seeking to extend its oversight to all e-cigarettes.
The bottom line: More data on safety and regulatory oversight are needed before recommendations on the use of e-cigarettes as a smoking cessation tool can be made.
Looking ahead
Several novel pharmacotherapies have been evaluated for smoking cessation in recent years. Among them is a nicotine vaccine that several drug companies have been pursuing. In theory, such a vaccine would create an immunologic reaction to nicotine in a smoker, thereby preventing the substance from reaching the brain and providing rewarding stimuli. A 2008 Cochrane review of 4 trials assessing the efficacy of nicotine vaccines for tobacco cessation found that none showed efficacy.34
Naltrexone, an opioid antagonist, has shown efficacy in helping those with opioid or alcohol dependence achieve abstinence from these substances, raising the possibility that it might aid in smoking cessation, as well. A 2013 Cochrane review of 8 trials found that this was not the case: Compared with placebo, naltrexone was not beneficial when used alone (RR=1.00; 95% CI, 0.66-1.51) or as an adjunct to NRT compared with NRT alone (RR=0.95; 95% CI, 0.70-1.30).35
Cytisine, an extract from plants in the Faboideae family, has been used in Eastern Europe for decades for smoking cessation. It appears to work as a nicotine receptor partial agonist similar to varenicline. The extract does not have FDA approval, but the National Institutes of Health’s Center for Complementary and Integrative Health is sponsoring early-stage safety trials that could lead to its approval in the United States.36
A 2012 Cochrane review identified 2 recent RCTs evaluating cytisine and found it to be effective in increasing smoking cessation rates vs placebo (RR=3.98; 95% CI, 2.01-7.87).13
CORRESPONDENCE
Paul Bornemann, MD, 3209 Colonial Drive, Columbia, SC 29203; [email protected].
ACKNOWLEDGEMENT
The authors thank Matt Orr, PhD, and Kathryn E. Bornemann for their help with this manuscript.
1. National Center for Chronic Disease Prevention and Health Promotion Office on Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. 2014. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24455788. Accessed October 21, 2015.
2. Smoking-attributable mortality, years of potential life lost, and productivity losses—United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2008;57:1226-1228.
3. Doll R, Peto R, Boreham J, et al. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ. 2004;328:1519.
4. US Public Health Service. A clinical practice guideline for treating tobacco use and dependence: 2008 update. A US Public Health Service Report. Am J Prev Med. 2008;35:158-176.
5. US Preventive Services Task Force. Tobacco use in adults and pregnant women: Counseling and interventions. April 2009. Available at: http://www.uspreventiveservicestaskforce.org/Page/Topic/recommendation-summary/tobacco-use-in-adults-and-pregnant-women-counseling-and-interventions. Accessed October 21, 2015.
6. Hughes JR, Stead LF, Hartmann-Boyce J, et al. Antidepressants for smoking cessation. Cochrane Database Syst Rev. 2014;(1):CD000031.
7. Cahill K, Stevens S, Perera R, et al. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;(5):CD009329.
8. Stead LF, Perera R, Bullen C, et al. Nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev. 2012;(11):CD000146.
9. Schnoll RA, Goelz PM, Veluz-Wilkins A, et al. Long-term nicotine replacement therapy: a randomized clinical trial. JAMA Intern Med. 2015;175:504-511.
10. Coleman T, Chamberlain C, Davey MA, et al. Pharmacological interventions for promoting smoking cessation during pregnancy. Cochrane Database Syst Rev. 2012;(9):CD010078.
11. Hajek P, West R, Foulds J, et al. Randomized comparative trial of nicotine polacrilex, a transdermal patch, nasal spray, and an inhaler. Arch Intern Med. 1999;159:2033-2038.
12. Eisenberg MJ, Filion KB, Yavin D, et al. Pharmacotherapies for smoking cessation: a meta-analysis of randomized controlled trials. CMAJ. 2008;179:135-144.
13. Cahill K, Stead LF, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev. 2012;(4):CD006103.
14. Ebbert JO, Hughes JR, West RJ, et al. Effect of varenicline on smoking cessation through smoking reduction: a randomized clinical trial. JAMA. 2015;313:687-694.
15. US Food and Drug Administration. Reports of suicidality associated with use of varenicline (marketed as CHANTIX) and bupropion (marketed as ZYBAN and GENERICS). FDA Drug Safety News. 2009.
16. Moore TJ, Furberg CD, Glenmullen J, et al. Suicidal behavior and depression in smoking cessation treatments. PLoS One. 2011;6:e27016.
17. Thomas KH, Martin RM, Davies NM, et al. Smoking cessation treatment and risk of depression, suicide, and self harm in the Clinical Practice Research Datalink: prospective cohort study. BMJ. 2013;347:f5704.
18. Thomas KH, Martin RM, Knipe DW, et al. Risk of neuropsychiatric adverse events associated with varenicline: systematic review and meta-analysis. BMJ. 2015;350:h1109.
19. Evins AE, Cather C, Pratt SA, et al. Maintenance treatment with varenicline for smoking cessation in patients with schizophrenia and bipolar disorder: a randomized clinical trial. JAMA. 2014;311:145-154.
20. Singh S, Loke YK, Spangler JG, et al. Risk of serious adverse cardiovascular events associated with varenicline: a systematic review and meta-analysis. CMAJ. 2011;183:1359-1366.
21. Prochaska JJ, Hilton JF. Risk of cardiovascular serious adverse events associated with varenicline use for tobacco cessation: systematic review and meta-analysis. BMJ. 2012;344:e2856.
22. Svanström H, Pasternak B, Hviid A. Use of varenicline for smoking cessation and risk of serious cardiovascular events: nationwide cohort study. BMJ. 2012;345:e7176.
23. Smith SS, McCarthy DE, Japuntich SJ, et al. Comparative effectiveness of five smoking cessation pharmacotherapies in primary care clinics. Arch Intern Med. 2009;169:2148–2155.
24. Koegelenberg CFN, Noor F, Bateman ED, et al. Efficacy of varenicline combined with nicotine replacement therapy vs varenicline alone for smoking cessation. JAMA. 2014;312:155-161.
25. Ebbert JO, Hatsukami DK, Croghan IT, et al. Combination varenicline and bupropion SR for tobacco-dependence treatment in cigarette smokers: a randomized trial. JAMA. 2014;311:155-163.
26. Steinberg MB, Greenhaus S, Schmelzer AC, et al. Triple-combination pharmacotherapy for medically ill smokers: A randomized trial. Ann Intern Med. 2009;150:447-454.
27. McMillen RC, Gottlieb MA, Shaefer RMW, et al. Trends in electronic cigarette use among US. adults: use is increasing in both smokers and nonsmokers. Nicotine Tob Res. 2015;17:1195-1202.
28. McRobbie H, Bullen C, Hartmann-Boyce J, et al. Electronic cigarettes for smoking cessation and reduction. Cochrane Database Syst Rev. 2014;(12):CD010216.
29. Brose LS, Hitchman SC, Brown J, et al. Is the use of electronic cigarettes while smoking associated with smoking cessation attempts, cessation and reduced cigarette consumption? A survey with a 1-year follow-up. Addiction. 2015;110:1160-1168.
30. Adriaens K, Van Gucht D, Declerck P, et al. Effectiveness of the electronic cigarette: an eight-week Flemish study with six-month follow-up on smoking reduction, craving and experienced benefits and complaints. Int J Environ Res Public Health. 2014;11:11220-11248.
31. Goniewicz ML, Knysak J, Gawron M, et al. Levels of selected carcinogens and toxicants in vapour from electronic cigarettes. Tob Control. 2014;23:133-139.
32. Pisinger C, Døssing M. A systematic review of health effects of electronic cigarettes. Prev Med (Baltim). 2014;69C:248-260.
33. Bowerman M. Fla. man hospitalized after e-cigarette explodes in face. USA Today Network. October 29, 2015. Available at: http:// www.usatoday.com/story/news/nation-now/2015/10/29/fla-man-hospitalized-e-cigarette-explodes-face/74791722/. Accessed December 2, 2015.
34. Hatsukami D, Cahill K, Stead LF. Nicotine vaccines for smoking cessation. Cochrane Database Syst Rev. 2008;(2):CD007072.
35. David SP, Lancaster T, Stead LF, et al. Opioid antagonists for smoking cessation. Cochrane Database Syst Rev. 2013;(6):CD003086.
36. Frankel T. Pill that quashes tobacco urge found in plain sight. Washington Post. May 15, 2015. Available at: http://www.washingtonpost.com/business/economy/pill-promises-a-safercheaper-way-than-chantix-to-quit-smoking/2015/05/15/8ce5590c-f830-11e4-9030-b4732caefe81_story.html. Accessed August 3, 2015.
1. National Center for Chronic Disease Prevention and Health Promotion Office on Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. 2014. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24455788. Accessed October 21, 2015.
2. Smoking-attributable mortality, years of potential life lost, and productivity losses—United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2008;57:1226-1228.
3. Doll R, Peto R, Boreham J, et al. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ. 2004;328:1519.
4. US Public Health Service. A clinical practice guideline for treating tobacco use and dependence: 2008 update. A US Public Health Service Report. Am J Prev Med. 2008;35:158-176.
5. US Preventive Services Task Force. Tobacco use in adults and pregnant women: Counseling and interventions. April 2009. Available at: http://www.uspreventiveservicestaskforce.org/Page/Topic/recommendation-summary/tobacco-use-in-adults-and-pregnant-women-counseling-and-interventions. Accessed October 21, 2015.
6. Hughes JR, Stead LF, Hartmann-Boyce J, et al. Antidepressants for smoking cessation. Cochrane Database Syst Rev. 2014;(1):CD000031.
7. Cahill K, Stevens S, Perera R, et al. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;(5):CD009329.
8. Stead LF, Perera R, Bullen C, et al. Nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev. 2012;(11):CD000146.
9. Schnoll RA, Goelz PM, Veluz-Wilkins A, et al. Long-term nicotine replacement therapy: a randomized clinical trial. JAMA Intern Med. 2015;175:504-511.
10. Coleman T, Chamberlain C, Davey MA, et al. Pharmacological interventions for promoting smoking cessation during pregnancy. Cochrane Database Syst Rev. 2012;(9):CD010078.
11. Hajek P, West R, Foulds J, et al. Randomized comparative trial of nicotine polacrilex, a transdermal patch, nasal spray, and an inhaler. Arch Intern Med. 1999;159:2033-2038.
12. Eisenberg MJ, Filion KB, Yavin D, et al. Pharmacotherapies for smoking cessation: a meta-analysis of randomized controlled trials. CMAJ. 2008;179:135-144.
13. Cahill K, Stead LF, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev. 2012;(4):CD006103.
14. Ebbert JO, Hughes JR, West RJ, et al. Effect of varenicline on smoking cessation through smoking reduction: a randomized clinical trial. JAMA. 2015;313:687-694.
15. US Food and Drug Administration. Reports of suicidality associated with use of varenicline (marketed as CHANTIX) and bupropion (marketed as ZYBAN and GENERICS). FDA Drug Safety News. 2009.
16. Moore TJ, Furberg CD, Glenmullen J, et al. Suicidal behavior and depression in smoking cessation treatments. PLoS One. 2011;6:e27016.
17. Thomas KH, Martin RM, Davies NM, et al. Smoking cessation treatment and risk of depression, suicide, and self harm in the Clinical Practice Research Datalink: prospective cohort study. BMJ. 2013;347:f5704.
18. Thomas KH, Martin RM, Knipe DW, et al. Risk of neuropsychiatric adverse events associated with varenicline: systematic review and meta-analysis. BMJ. 2015;350:h1109.
19. Evins AE, Cather C, Pratt SA, et al. Maintenance treatment with varenicline for smoking cessation in patients with schizophrenia and bipolar disorder: a randomized clinical trial. JAMA. 2014;311:145-154.
20. Singh S, Loke YK, Spangler JG, et al. Risk of serious adverse cardiovascular events associated with varenicline: a systematic review and meta-analysis. CMAJ. 2011;183:1359-1366.
21. Prochaska JJ, Hilton JF. Risk of cardiovascular serious adverse events associated with varenicline use for tobacco cessation: systematic review and meta-analysis. BMJ. 2012;344:e2856.
22. Svanström H, Pasternak B, Hviid A. Use of varenicline for smoking cessation and risk of serious cardiovascular events: nationwide cohort study. BMJ. 2012;345:e7176.
23. Smith SS, McCarthy DE, Japuntich SJ, et al. Comparative effectiveness of five smoking cessation pharmacotherapies in primary care clinics. Arch Intern Med. 2009;169:2148–2155.
24. Koegelenberg CFN, Noor F, Bateman ED, et al. Efficacy of varenicline combined with nicotine replacement therapy vs varenicline alone for smoking cessation. JAMA. 2014;312:155-161.
25. Ebbert JO, Hatsukami DK, Croghan IT, et al. Combination varenicline and bupropion SR for tobacco-dependence treatment in cigarette smokers: a randomized trial. JAMA. 2014;311:155-163.
26. Steinberg MB, Greenhaus S, Schmelzer AC, et al. Triple-combination pharmacotherapy for medically ill smokers: A randomized trial. Ann Intern Med. 2009;150:447-454.
27. McMillen RC, Gottlieb MA, Shaefer RMW, et al. Trends in electronic cigarette use among US. adults: use is increasing in both smokers and nonsmokers. Nicotine Tob Res. 2015;17:1195-1202.
28. McRobbie H, Bullen C, Hartmann-Boyce J, et al. Electronic cigarettes for smoking cessation and reduction. Cochrane Database Syst Rev. 2014;(12):CD010216.
29. Brose LS, Hitchman SC, Brown J, et al. Is the use of electronic cigarettes while smoking associated with smoking cessation attempts, cessation and reduced cigarette consumption? A survey with a 1-year follow-up. Addiction. 2015;110:1160-1168.
30. Adriaens K, Van Gucht D, Declerck P, et al. Effectiveness of the electronic cigarette: an eight-week Flemish study with six-month follow-up on smoking reduction, craving and experienced benefits and complaints. Int J Environ Res Public Health. 2014;11:11220-11248.
31. Goniewicz ML, Knysak J, Gawron M, et al. Levels of selected carcinogens and toxicants in vapour from electronic cigarettes. Tob Control. 2014;23:133-139.
32. Pisinger C, Døssing M. A systematic review of health effects of electronic cigarettes. Prev Med (Baltim). 2014;69C:248-260.
33. Bowerman M. Fla. man hospitalized after e-cigarette explodes in face. USA Today Network. October 29, 2015. Available at: http:// www.usatoday.com/story/news/nation-now/2015/10/29/fla-man-hospitalized-e-cigarette-explodes-face/74791722/. Accessed December 2, 2015.
34. Hatsukami D, Cahill K, Stead LF. Nicotine vaccines for smoking cessation. Cochrane Database Syst Rev. 2008;(2):CD007072.
35. David SP, Lancaster T, Stead LF, et al. Opioid antagonists for smoking cessation. Cochrane Database Syst Rev. 2013;(6):CD003086.
36. Frankel T. Pill that quashes tobacco urge found in plain sight. Washington Post. May 15, 2015. Available at: http://www.washingtonpost.com/business/economy/pill-promises-a-safercheaper-way-than-chantix-to-quit-smoking/2015/05/15/8ce5590c-f830-11e4-9030-b4732caefe81_story.html. Accessed August 3, 2015.
Botanical over-the-counter regimen reduces acne lesions
An over-the-counter botanical acne regimen outperformed a conventional acne regimen, with improved skin appearance and fewer lesions after 12 weeks of treatment, in a double-blind randomized controlled trial.
Eighty individuals aged 12 years and older with mild to moderate acne were randomized either to a three-step botanical-based acne treatment regimen (Receutics) consisting of a skin cleanser, breakout treatment, and tone and complexion corrector twice daily, or the currently marketed acne treatment kit, Proactiv (Guthy-Renker).
The botanical-based acne treatment contains a range of botanical ingredients, including algae and lentil seed extracts; cranberry seed, grape seed, and pumpkin seed oils; and allantoin; with 3.4% benzoyl peroxide as the active ingredient. The active ingredient in the cleanser is 2% salicylic acid, and niacinamide is the active ingredient in the tone and complexion corrector; both also contain botanical ingredients.
In the study, published in December, the investigator, Dr. Zoe Diana Draelos, reported that the botanical regimen achieved a significantly greater reduction in lesion count, in terms of closed comedones and inflammatory lesions, by week four, compared with the control treatment (J Drugs Dermatol. 2015 Dec; 14 [12]:1418-21).
This effect persisted at 12 weeks, with fewer closed comedones (P = .006). The botanical regimen also achieved greater reductions in pus, erythema, lesion height, and inflammation at weeks 2 and 4; although this difference disappeared by week 12. By week four and onwards, the botanical regimen also outperformed the conventional treatment on all blinded, investigator-assessed cosmetic appearance parameters, including skin tone, blemishes, erythema, and overall appearance.
While both treatments were effective at improving acne, Dr. Draelos, of Dermatology Consulting Services, High Point, N.C., said the botanical three-step regimen had the advantage of cosmetic ingredients such as emollients, anti-inflammatory/antioxidants, and “sensitive skin modulators.”
“This study demonstrates the value of combining monographed acne ingredients with advanced cosmeceutical technology,” she wrote.
The author received a grant from manufacturer Receutics to conduct the study.
An over-the-counter botanical acne regimen outperformed a conventional acne regimen, with improved skin appearance and fewer lesions after 12 weeks of treatment, in a double-blind randomized controlled trial.
Eighty individuals aged 12 years and older with mild to moderate acne were randomized either to a three-step botanical-based acne treatment regimen (Receutics) consisting of a skin cleanser, breakout treatment, and tone and complexion corrector twice daily, or the currently marketed acne treatment kit, Proactiv (Guthy-Renker).
The botanical-based acne treatment contains a range of botanical ingredients, including algae and lentil seed extracts; cranberry seed, grape seed, and pumpkin seed oils; and allantoin; with 3.4% benzoyl peroxide as the active ingredient. The active ingredient in the cleanser is 2% salicylic acid, and niacinamide is the active ingredient in the tone and complexion corrector; both also contain botanical ingredients.
In the study, published in December, the investigator, Dr. Zoe Diana Draelos, reported that the botanical regimen achieved a significantly greater reduction in lesion count, in terms of closed comedones and inflammatory lesions, by week four, compared with the control treatment (J Drugs Dermatol. 2015 Dec; 14 [12]:1418-21).
This effect persisted at 12 weeks, with fewer closed comedones (P = .006). The botanical regimen also achieved greater reductions in pus, erythema, lesion height, and inflammation at weeks 2 and 4; although this difference disappeared by week 12. By week four and onwards, the botanical regimen also outperformed the conventional treatment on all blinded, investigator-assessed cosmetic appearance parameters, including skin tone, blemishes, erythema, and overall appearance.
While both treatments were effective at improving acne, Dr. Draelos, of Dermatology Consulting Services, High Point, N.C., said the botanical three-step regimen had the advantage of cosmetic ingredients such as emollients, anti-inflammatory/antioxidants, and “sensitive skin modulators.”
“This study demonstrates the value of combining monographed acne ingredients with advanced cosmeceutical technology,” she wrote.
The author received a grant from manufacturer Receutics to conduct the study.
An over-the-counter botanical acne regimen outperformed a conventional acne regimen, with improved skin appearance and fewer lesions after 12 weeks of treatment, in a double-blind randomized controlled trial.
Eighty individuals aged 12 years and older with mild to moderate acne were randomized either to a three-step botanical-based acne treatment regimen (Receutics) consisting of a skin cleanser, breakout treatment, and tone and complexion corrector twice daily, or the currently marketed acne treatment kit, Proactiv (Guthy-Renker).
The botanical-based acne treatment contains a range of botanical ingredients, including algae and lentil seed extracts; cranberry seed, grape seed, and pumpkin seed oils; and allantoin; with 3.4% benzoyl peroxide as the active ingredient. The active ingredient in the cleanser is 2% salicylic acid, and niacinamide is the active ingredient in the tone and complexion corrector; both also contain botanical ingredients.
In the study, published in December, the investigator, Dr. Zoe Diana Draelos, reported that the botanical regimen achieved a significantly greater reduction in lesion count, in terms of closed comedones and inflammatory lesions, by week four, compared with the control treatment (J Drugs Dermatol. 2015 Dec; 14 [12]:1418-21).
This effect persisted at 12 weeks, with fewer closed comedones (P = .006). The botanical regimen also achieved greater reductions in pus, erythema, lesion height, and inflammation at weeks 2 and 4; although this difference disappeared by week 12. By week four and onwards, the botanical regimen also outperformed the conventional treatment on all blinded, investigator-assessed cosmetic appearance parameters, including skin tone, blemishes, erythema, and overall appearance.
While both treatments were effective at improving acne, Dr. Draelos, of Dermatology Consulting Services, High Point, N.C., said the botanical three-step regimen had the advantage of cosmetic ingredients such as emollients, anti-inflammatory/antioxidants, and “sensitive skin modulators.”
“This study demonstrates the value of combining monographed acne ingredients with advanced cosmeceutical technology,” she wrote.
The author received a grant from manufacturer Receutics to conduct the study.
FROM THE JOURNAL OF DRUGS IN DERMATOLOGY
Key clinical point: A botanical over-the-counter acne regimen achieved greater reductions in lesions than a currently marketed acne treatment.
Major finding: A three-step botanical-based acne regimen achieved significantly greater reduction in lesion counts and improvements in skin appearance than a conventional acne treatment.
Data source: A randomized, double-blind, controlled trial of 80 patients with mild to moderate acne.
Disclosures: The author received a grant from treatment manufacturer Receutics to conduct the study.