Federal Practitioner

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

Abdominal aortic aneurysm (AAA) is a public health threat, with a global prevalence of 4.8% and a prevalence in males that increases with age, from 1.3% between ages 45 and 54 years to 12.5% between ages 75 and 84 years.¹ AAA is often asymptomatic until it ruptures and can become life-threatening, with mortality rates near 90% in the event of rupture with survival rates of about 50% to 70% for individuals with rupture who require urgent surgical intervention.^2,3 Males experience AAA at 4 times the rate of females.⁴

Previous research has found that the awareness of having an AAA causes anxiety that some have described as “living with a ticking time bomb.”⁵ Others reported worries and concerns about life’s fragility and mortality due to an AAA diagnosis.⁶ However, the psychological impact on the individuals’ quality of life (QoL) remains unclear, especially for individuals with a small AAA (< 5.5 cm).⁷ Factors such as age, male sex, smoking, family history, hypertension, carotid artery disease, and hypercholesterolemia have been strongly associated with increased growth rate and the risk of small AAA ruptures.^8,9

Most patients with a small AAA enter surveillance awaiting future repair and not only have the anxiety of living with an AAA despite the low risk of rupture, but also a worse QoL than those who have undergone repair.^10,11 However, data are sparse regarding the effects on QoL of knowing they have an AAA, whether repaired or not. This study sought to examine the impact an AAA diagnosis had on male QoL at the initial investigation and after 12 months.

Methods

This prospective study was examined and approved by the Veterans Affairs Northern California Health Care System (NCHCS) Institutional Review Board. It was conducted at the Sacramento US Department of Veterans Affairs (VA) Medical Center from January 1, 2019, to February 28, 2022. Patients were identified through the vascular clinic. One hundred sixteen patients with AAA were eligible and agreed to participate. Of these, 91 (78%) completed the survey at baseline and 12 months later. Participation was voluntary; written informed consent was obtained from every patient before completing the survey. This study included only male patients due to their higher prevalence than female patients.⁴ Patients were also eligible if they were aged > 18 years and had a previously known AAA that was being followed with a recorded clinical imaging study in the NCHCS vascular clinic. Patients were excluded if they were unable to return for their 12-month follow-up investigation, were incapable of giving informed consent, were unable to complete the 12-item short form health survey version 2 (SF-12v2), had a documented history of psychiatric illness, or refused to participate. The SF-12v2, an abbreviated version of the 36-item short form health survey (SF-36), is a generic health-related quality-of-life survey that measures 8 domains of general health status: general health (GH), physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), vitality (VT), social functioning (SF), role emotional (RE), and mental health (MH). A higher number on the QoL scale indicates better QoL. The GH, PF, RP, and BP scales yield a physical component score (PCS), and the VT, SF, RE, and MH scales generate a mental component score (MCS). Although SF-12v2 has not been validated for patients with AAA, it has been widely used and validated to measure health-related QoL in cohorts of healthy and chronically ill individuals.^12,13

Analysis

Descriptive statistics, including means, SDs, frequency, percentages, 95% CIs, and correlations were calculated. The t test was used to analyze differences in mean scores. For continuous variables, such as SF-12v2 domains, PCS, and MCS, mean, SD, 95% CI, and range were determined. Comparisons were performed using X² or t test. P < .05 was considered statistically significant. Clinical risk factors, including age, race, body mass index (BMI), diabetes, hypertension, hyperlipidemia, coronary artery disease, cerebrovascular accident, myocardial infarction, and smoking status, were also recorded.

Results

Between January 1, 2019, and February 28, 2022, 91 patients were diagnosed with an AAA and completed the survey at the initial and 12-month investigations. Patients had a mean (SD) age of 76.0 (5.6) years (range, 64-93) and BMI of 29.7 (6.4). Comorbid diabetes was present in 31% of patients, hypertension in 75%, hyperlipidemia 66%, and coronary artery disease in 12% (Table 1). Most patients smoked tobacco: 71% indicated previous use and 22% were current users.

When comparing baseline vs 12-month follow-up, patients indicated a higher QoL in GH (3.2 vs 3.5, respectively; P < .05) and BP (3.1 vs 3.6, respectively; P < .05). No statistically significant difference was seen PF, RP, VT, SF, RE, MH, as well as PCS and MCS between baseline and follow-up with respect to QoL (P < .05). However, the 5 domains of SF-12v2: PF, RP, SF, RE, MH, and PCS had lower QoL scores at the 12-month follow-up when compared with baseline, but with no statistically significant difference between both investigations (Table 2).

Discussion

Previous studies have characterized the results of QoL measures as subjective because they are based on patient perceptions of their physical and psychological condition.^14,15 However, SF-36 and SF-12v2 responses provide a multifaceted account that encompasses the physical, psychological, and social aspects of QoL. Despite being the most widely used generic instrument in many fields of medicine, SF-36 is time consuming for clinicians who may prefer simpler and more time-efficient instruments.^16-18 The SF-12v2 not only imposes less burden on respondents but also generates accurate summary scores for patients physical and mental health.¹⁹

The replicability of SF-12v2 PCS and MCS scores has been demonstrated. In the United Kingdom, Jenkinson and Layte constructed SF-12v2 summary measures from a large scale dataset by sending the SF-36 and other questions on health and lifestyles to 9332 individuals and compared the results of the SF-36 and SF-12v2 across diverse patient groups (eg, Parkinson disease, congestive heart failure, sleep apnea, benign prostatic hypertrophy). Results from SF-36 PCS, SF-36 MCS, and PCS-12v2 (ρ, 0.94; P < .001) and SF-12v2 MCS (ρ, 0.96; P < .001) were found to be highly correlated, and also produced similar results, both in the community sample and across a variety of disease-specific groups.²⁰

The aim of this longitudinal observational study was to measure the QoL of males with an AAA ≥ 3.0 cm at baseline and 12 months later. The mean age of participants was 76 years, which aligns with previous research that found the prevalence of AAAs increased with age.¹ Study participants had a mean BMI of 29.7, which also supports previous research that indicated that obesity is independently associated with an AAA.²¹ Patients with an AAA and a history of smoking (former or current), hypertension, or hyperlipidemia had lower mean scores for 3 of 8 SF-12v2 domains at the 12-month follow-up.

These findings support previous research that indicated smoking is not only a very strong risk factor for the presence of an AAA but also associated with increased rates of expansion and the risk of rupture in patients with an AAA.²² Bath et al found that patients with an AAA compared to patients without an AAA were older (age 72.6 vs 69.8 years; P < .001), had a higher BMI (28.1 vs 27.0; P < .001), were more likely to be a current smoker (15.1% vs 5.2%; P < .001), and were more likely to have diabetes (18.8% vs 10.0%; P < .001), ischemic heart disease (12.2% vs 4.4%; P < .001), high cholesterol (53.2% vs 30.8%; P <. 001), previous stroke (6.1% vs 2.9%; P < .001), and a previous myocardial infarction (21.1% vs 5.8%; P < .001).²³ Lesjak et al found that men with AAA reported significantly lower scores in the domains of social functioning, pain, and general health 6 months after ultrasound compared with men without AAA.²⁴

Previous research indicates that patients with an AAA have a higher risk of cardiovascular diseases and comorbidities that may impact their perceived QoL. In a study assessing cardiovascular risk in 2323 patients with a small AAA, Bath et al found a high prevalence of coronary artery disease (44.9%), myocardial infarction (26.8%), heart failure (4.4%) and cerebrovascular accident (14.0%) which may have contributed to the decreased level of self-perceived QoL in these patients.²⁵

This aligned with a study by Golledge et al, who found that participants diagnosed with an AAA and peripheral artery disease not only had significantly poorer QoL scores in 5 SF-36 domains (PF, RP, GH, VT, and PCS)when compared with participants diagnosed with an AAA alone. They also had significantly poorer QoL scores in 7 domains of the SF-36 (PF, RP, GH, VT, SF, RE, and PCS) when compared with controls without an AAA.²⁶

Our analysis found that males with an AAA had a rise in SF-12v2 QoL scores from baseline to 12-month follow-up in the GH and BP domains. There was no statistically significant difference in QoL in the other 6 domains (PF, RP, VT, SF, RE, and MH) between the initial and 12-month investigations. Bath et al also found that men with an AAA had a transient reduction in mental QoL during the first year after the initial screening but returned to baseline.²³

Strengths and Limitations

This study is notable for its sample of patients who previously had a diagnosed AAA that were followed with a recorded clinical imaging study and the use of a validated QoL measure (SF-12v2) that provided virtually identical summary scores (PCS and MCS) as the SF-36.27 However, this study was limited by the brevity of the SF-12v2 instrument which made it difficult to extract sufficient reliable information for the 8 domains.²⁸ Subjective perception of patients is another limitation inherent to any QoL study. QoL scores were not available before the initial investigation. Measuring QoL at baseline and 12 months later does not capture the potential fluctuations and changes in QoL that the patient may experience some months later. Another limitation arises from the fact that the AAA patient population in the study included patients under surveillance and patients who had undergone repair.

Fourteen patients (15%) had received AAA repair: 10 had endovascular reconstruction and 4 had open surgical repair. Including patients with a previous AAA repair may have influenced reported QoL levels. Suckow et al performed a 2-phase study on 1008 patients, 351 (35%) were under surveillance and 657 (65%) had undergone repair. In that study, patients under AAA surveillance had worse emotional impact scores compared with patients with repair (22 vs 13; P < .001).¹¹ Additionally, the size of the abdominal aorta at the time of survey was not addressed in the study, which could constitute explanatory variables.

Conclusions

This study found higher QoL at 12-month follow-up compared to baseline in both the GH and BP domains of the SF-12v2 health survey for male veterans with an AAA. Periodic QoL assessments for patients with an AAA may be helpful in tracking QoL course, minimizing their physical and psychological concerns, and improving overall care and support. However, further research is necessary to assess the QoL of patients with an AAA who are under surveillance compared with those who had an aneurysm repair to accurately measure the impact of an AAA on QoL.

Abdominal aortic aneurysm (AAA) is a public health threat, with a global prevalence of 4.8% and a prevalence in males that increases with age, from 1.3% between ages 45 and 54 years to 12.5% between ages 75 and 84 years.¹ AAA is often asymptomatic until it ruptures and can become life-threatening, with mortality rates near 90% in the event of rupture with survival rates of about 50% to 70% for individuals with rupture who require urgent surgical intervention.^2,3 Males experience AAA at 4 times the rate of females.⁴

Previous research has found that the awareness of having an AAA causes anxiety that some have described as “living with a ticking time bomb.”⁵ Others reported worries and concerns about life’s fragility and mortality due to an AAA diagnosis.⁶ However, the psychological impact on the individuals’ quality of life (QoL) remains unclear, especially for individuals with a small AAA (< 5.5 cm).⁷ Factors such as age, male sex, smoking, family history, hypertension, carotid artery disease, and hypercholesterolemia have been strongly associated with increased growth rate and the risk of small AAA ruptures.^8,9

Most patients with a small AAA enter surveillance awaiting future repair and not only have the anxiety of living with an AAA despite the low risk of rupture, but also a worse QoL than those who have undergone repair.^10,11 However, data are sparse regarding the effects on QoL of knowing they have an AAA, whether repaired or not. This study sought to examine the impact an AAA diagnosis had on male QoL at the initial investigation and after 12 months.

Methods

This prospective study was examined and approved by the Veterans Affairs Northern California Health Care System (NCHCS) Institutional Review Board. It was conducted at the Sacramento US Department of Veterans Affairs (VA) Medical Center from January 1, 2019, to February 28, 2022. Patients were identified through the vascular clinic. One hundred sixteen patients with AAA were eligible and agreed to participate. Of these, 91 (78%) completed the survey at baseline and 12 months later. Participation was voluntary; written informed consent was obtained from every patient before completing the survey. This study included only male patients due to their higher prevalence than female patients.⁴ Patients were also eligible if they were aged > 18 years and had a previously known AAA that was being followed with a recorded clinical imaging study in the NCHCS vascular clinic. Patients were excluded if they were unable to return for their 12-month follow-up investigation, were incapable of giving informed consent, were unable to complete the 12-item short form health survey version 2 (SF-12v2), had a documented history of psychiatric illness, or refused to participate. The SF-12v2, an abbreviated version of the 36-item short form health survey (SF-36), is a generic health-related quality-of-life survey that measures 8 domains of general health status: general health (GH), physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), vitality (VT), social functioning (SF), role emotional (RE), and mental health (MH). A higher number on the QoL scale indicates better QoL. The GH, PF, RP, and BP scales yield a physical component score (PCS), and the VT, SF, RE, and MH scales generate a mental component score (MCS). Although SF-12v2 has not been validated for patients with AAA, it has been widely used and validated to measure health-related QoL in cohorts of healthy and chronically ill individuals.^12,13

Analysis

Descriptive statistics, including means, SDs, frequency, percentages, 95% CIs, and correlations were calculated. The t test was used to analyze differences in mean scores. For continuous variables, such as SF-12v2 domains, PCS, and MCS, mean, SD, 95% CI, and range were determined. Comparisons were performed using X² or t test. P < .05 was considered statistically significant. Clinical risk factors, including age, race, body mass index (BMI), diabetes, hypertension, hyperlipidemia, coronary artery disease, cerebrovascular accident, myocardial infarction, and smoking status, were also recorded.

Results

Between January 1, 2019, and February 28, 2022, 91 patients were diagnosed with an AAA and completed the survey at the initial and 12-month investigations. Patients had a mean (SD) age of 76.0 (5.6) years (range, 64-93) and BMI of 29.7 (6.4). Comorbid diabetes was present in 31% of patients, hypertension in 75%, hyperlipidemia 66%, and coronary artery disease in 12% (Table 1). Most patients smoked tobacco: 71% indicated previous use and 22% were current users.

When comparing baseline vs 12-month follow-up, patients indicated a higher QoL in GH (3.2 vs 3.5, respectively; P < .05) and BP (3.1 vs 3.6, respectively; P < .05). No statistically significant difference was seen PF, RP, VT, SF, RE, MH, as well as PCS and MCS between baseline and follow-up with respect to QoL (P < .05). However, the 5 domains of SF-12v2: PF, RP, SF, RE, MH, and PCS had lower QoL scores at the 12-month follow-up when compared with baseline, but with no statistically significant difference between both investigations (Table 2).

Discussion

Previous studies have characterized the results of QoL measures as subjective because they are based on patient perceptions of their physical and psychological condition.^14,15 However, SF-36 and SF-12v2 responses provide a multifaceted account that encompasses the physical, psychological, and social aspects of QoL. Despite being the most widely used generic instrument in many fields of medicine, SF-36 is time consuming for clinicians who may prefer simpler and more time-efficient instruments.^16-18 The SF-12v2 not only imposes less burden on respondents but also generates accurate summary scores for patients physical and mental health.¹⁹

The replicability of SF-12v2 PCS and MCS scores has been demonstrated. In the United Kingdom, Jenkinson and Layte constructed SF-12v2 summary measures from a large scale dataset by sending the SF-36 and other questions on health and lifestyles to 9332 individuals and compared the results of the SF-36 and SF-12v2 across diverse patient groups (eg, Parkinson disease, congestive heart failure, sleep apnea, benign prostatic hypertrophy). Results from SF-36 PCS, SF-36 MCS, and PCS-12v2 (ρ, 0.94; P < .001) and SF-12v2 MCS (ρ, 0.96; P < .001) were found to be highly correlated, and also produced similar results, both in the community sample and across a variety of disease-specific groups.²⁰

The aim of this longitudinal observational study was to measure the QoL of males with an AAA ≥ 3.0 cm at baseline and 12 months later. The mean age of participants was 76 years, which aligns with previous research that found the prevalence of AAAs increased with age.¹ Study participants had a mean BMI of 29.7, which also supports previous research that indicated that obesity is independently associated with an AAA.²¹ Patients with an AAA and a history of smoking (former or current), hypertension, or hyperlipidemia had lower mean scores for 3 of 8 SF-12v2 domains at the 12-month follow-up.

These findings support previous research that indicated smoking is not only a very strong risk factor for the presence of an AAA but also associated with increased rates of expansion and the risk of rupture in patients with an AAA.²² Bath et al found that patients with an AAA compared to patients without an AAA were older (age 72.6 vs 69.8 years; P < .001), had a higher BMI (28.1 vs 27.0; P < .001), were more likely to be a current smoker (15.1% vs 5.2%; P < .001), and were more likely to have diabetes (18.8% vs 10.0%; P < .001), ischemic heart disease (12.2% vs 4.4%; P < .001), high cholesterol (53.2% vs 30.8%; P <. 001), previous stroke (6.1% vs 2.9%; P < .001), and a previous myocardial infarction (21.1% vs 5.8%; P < .001).²³ Lesjak et al found that men with AAA reported significantly lower scores in the domains of social functioning, pain, and general health 6 months after ultrasound compared with men without AAA.²⁴

Previous research indicates that patients with an AAA have a higher risk of cardiovascular diseases and comorbidities that may impact their perceived QoL. In a study assessing cardiovascular risk in 2323 patients with a small AAA, Bath et al found a high prevalence of coronary artery disease (44.9%), myocardial infarction (26.8%), heart failure (4.4%) and cerebrovascular accident (14.0%) which may have contributed to the decreased level of self-perceived QoL in these patients.²⁵

This aligned with a study by Golledge et al, who found that participants diagnosed with an AAA and peripheral artery disease not only had significantly poorer QoL scores in 5 SF-36 domains (PF, RP, GH, VT, and PCS)when compared with participants diagnosed with an AAA alone. They also had significantly poorer QoL scores in 7 domains of the SF-36 (PF, RP, GH, VT, SF, RE, and PCS) when compared with controls without an AAA.²⁶

Our analysis found that males with an AAA had a rise in SF-12v2 QoL scores from baseline to 12-month follow-up in the GH and BP domains. There was no statistically significant difference in QoL in the other 6 domains (PF, RP, VT, SF, RE, and MH) between the initial and 12-month investigations. Bath et al also found that men with an AAA had a transient reduction in mental QoL during the first year after the initial screening but returned to baseline.²³

Strengths and Limitations

This study is notable for its sample of patients who previously had a diagnosed AAA that were followed with a recorded clinical imaging study and the use of a validated QoL measure (SF-12v2) that provided virtually identical summary scores (PCS and MCS) as the SF-36.27 However, this study was limited by the brevity of the SF-12v2 instrument which made it difficult to extract sufficient reliable information for the 8 domains.²⁸ Subjective perception of patients is another limitation inherent to any QoL study. QoL scores were not available before the initial investigation. Measuring QoL at baseline and 12 months later does not capture the potential fluctuations and changes in QoL that the patient may experience some months later. Another limitation arises from the fact that the AAA patient population in the study included patients under surveillance and patients who had undergone repair.

Fourteen patients (15%) had received AAA repair: 10 had endovascular reconstruction and 4 had open surgical repair. Including patients with a previous AAA repair may have influenced reported QoL levels. Suckow et al performed a 2-phase study on 1008 patients, 351 (35%) were under surveillance and 657 (65%) had undergone repair. In that study, patients under AAA surveillance had worse emotional impact scores compared with patients with repair (22 vs 13; P < .001).¹¹ Additionally, the size of the abdominal aorta at the time of survey was not addressed in the study, which could constitute explanatory variables.

Conclusions

This study found higher QoL at 12-month follow-up compared to baseline in both the GH and BP domains of the SF-12v2 health survey for male veterans with an AAA. Periodic QoL assessments for patients with an AAA may be helpful in tracking QoL course, minimizing their physical and psychological concerns, and improving overall care and support. However, further research is necessary to assess the QoL of patients with an AAA who are under surveillance compared with those who had an aneurysm repair to accurately measure the impact of an AAA on QoL.

Abdominal aortic aneurysm (AAA) is a public health threat, with a global prevalence of 4.8% and a prevalence in males that increases with age, from 1.3% between ages 45 and 54 years to 12.5% between ages 75 and 84 years.¹ AAA is often asymptomatic until it ruptures and can become life-threatening, with mortality rates near 90% in the event of rupture with survival rates of about 50% to 70% for individuals with rupture who require urgent surgical intervention.^2,3 Males experience AAA at 4 times the rate of females.⁴

Previous research has found that the awareness of having an AAA causes anxiety that some have described as “living with a ticking time bomb.”⁵ Others reported worries and concerns about life’s fragility and mortality due to an AAA diagnosis.⁶ However, the psychological impact on the individuals’ quality of life (QoL) remains unclear, especially for individuals with a small AAA (< 5.5 cm).⁷ Factors such as age, male sex, smoking, family history, hypertension, carotid artery disease, and hypercholesterolemia have been strongly associated with increased growth rate and the risk of small AAA ruptures.^8,9

Most patients with a small AAA enter surveillance awaiting future repair and not only have the anxiety of living with an AAA despite the low risk of rupture, but also a worse QoL than those who have undergone repair.^10,11 However, data are sparse regarding the effects on QoL of knowing they have an AAA, whether repaired or not. This study sought to examine the impact an AAA diagnosis had on male QoL at the initial investigation and after 12 months.

Methods

This prospective study was examined and approved by the Veterans Affairs Northern California Health Care System (NCHCS) Institutional Review Board. It was conducted at the Sacramento US Department of Veterans Affairs (VA) Medical Center from January 1, 2019, to February 28, 2022. Patients were identified through the vascular clinic. One hundred sixteen patients with AAA were eligible and agreed to participate. Of these, 91 (78%) completed the survey at baseline and 12 months later. Participation was voluntary; written informed consent was obtained from every patient before completing the survey. This study included only male patients due to their higher prevalence than female patients.⁴ Patients were also eligible if they were aged > 18 years and had a previously known AAA that was being followed with a recorded clinical imaging study in the NCHCS vascular clinic. Patients were excluded if they were unable to return for their 12-month follow-up investigation, were incapable of giving informed consent, were unable to complete the 12-item short form health survey version 2 (SF-12v2), had a documented history of psychiatric illness, or refused to participate. The SF-12v2, an abbreviated version of the 36-item short form health survey (SF-36), is a generic health-related quality-of-life survey that measures 8 domains of general health status: general health (GH), physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), vitality (VT), social functioning (SF), role emotional (RE), and mental health (MH). A higher number on the QoL scale indicates better QoL. The GH, PF, RP, and BP scales yield a physical component score (PCS), and the VT, SF, RE, and MH scales generate a mental component score (MCS). Although SF-12v2 has not been validated for patients with AAA, it has been widely used and validated to measure health-related QoL in cohorts of healthy and chronically ill individuals.^12,13

Analysis

Descriptive statistics, including means, SDs, frequency, percentages, 95% CIs, and correlations were calculated. The t test was used to analyze differences in mean scores. For continuous variables, such as SF-12v2 domains, PCS, and MCS, mean, SD, 95% CI, and range were determined. Comparisons were performed using X² or t test. P < .05 was considered statistically significant. Clinical risk factors, including age, race, body mass index (BMI), diabetes, hypertension, hyperlipidemia, coronary artery disease, cerebrovascular accident, myocardial infarction, and smoking status, were also recorded.

Results

Between January 1, 2019, and February 28, 2022, 91 patients were diagnosed with an AAA and completed the survey at the initial and 12-month investigations. Patients had a mean (SD) age of 76.0 (5.6) years (range, 64-93) and BMI of 29.7 (6.4). Comorbid diabetes was present in 31% of patients, hypertension in 75%, hyperlipidemia 66%, and coronary artery disease in 12% (Table 1). Most patients smoked tobacco: 71% indicated previous use and 22% were current users.

When comparing baseline vs 12-month follow-up, patients indicated a higher QoL in GH (3.2 vs 3.5, respectively; P < .05) and BP (3.1 vs 3.6, respectively; P < .05). No statistically significant difference was seen PF, RP, VT, SF, RE, MH, as well as PCS and MCS between baseline and follow-up with respect to QoL (P < .05). However, the 5 domains of SF-12v2: PF, RP, SF, RE, MH, and PCS had lower QoL scores at the 12-month follow-up when compared with baseline, but with no statistically significant difference between both investigations (Table 2).

Discussion

Previous studies have characterized the results of QoL measures as subjective because they are based on patient perceptions of their physical and psychological condition.^14,15 However, SF-36 and SF-12v2 responses provide a multifaceted account that encompasses the physical, psychological, and social aspects of QoL. Despite being the most widely used generic instrument in many fields of medicine, SF-36 is time consuming for clinicians who may prefer simpler and more time-efficient instruments.^16-18 The SF-12v2 not only imposes less burden on respondents but also generates accurate summary scores for patients physical and mental health.¹⁹

The replicability of SF-12v2 PCS and MCS scores has been demonstrated. In the United Kingdom, Jenkinson and Layte constructed SF-12v2 summary measures from a large scale dataset by sending the SF-36 and other questions on health and lifestyles to 9332 individuals and compared the results of the SF-36 and SF-12v2 across diverse patient groups (eg, Parkinson disease, congestive heart failure, sleep apnea, benign prostatic hypertrophy). Results from SF-36 PCS, SF-36 MCS, and PCS-12v2 (ρ, 0.94; P < .001) and SF-12v2 MCS (ρ, 0.96; P < .001) were found to be highly correlated, and also produced similar results, both in the community sample and across a variety of disease-specific groups.²⁰

The aim of this longitudinal observational study was to measure the QoL of males with an AAA ≥ 3.0 cm at baseline and 12 months later. The mean age of participants was 76 years, which aligns with previous research that found the prevalence of AAAs increased with age.¹ Study participants had a mean BMI of 29.7, which also supports previous research that indicated that obesity is independently associated with an AAA.²¹ Patients with an AAA and a history of smoking (former or current), hypertension, or hyperlipidemia had lower mean scores for 3 of 8 SF-12v2 domains at the 12-month follow-up.

These findings support previous research that indicated smoking is not only a very strong risk factor for the presence of an AAA but also associated with increased rates of expansion and the risk of rupture in patients with an AAA.²² Bath et al found that patients with an AAA compared to patients without an AAA were older (age 72.6 vs 69.8 years; P < .001), had a higher BMI (28.1 vs 27.0; P < .001), were more likely to be a current smoker (15.1% vs 5.2%; P < .001), and were more likely to have diabetes (18.8% vs 10.0%; P < .001), ischemic heart disease (12.2% vs 4.4%; P < .001), high cholesterol (53.2% vs 30.8%; P <. 001), previous stroke (6.1% vs 2.9%; P < .001), and a previous myocardial infarction (21.1% vs 5.8%; P < .001).²³ Lesjak et al found that men with AAA reported significantly lower scores in the domains of social functioning, pain, and general health 6 months after ultrasound compared with men without AAA.²⁴

Previous research indicates that patients with an AAA have a higher risk of cardiovascular diseases and comorbidities that may impact their perceived QoL. In a study assessing cardiovascular risk in 2323 patients with a small AAA, Bath et al found a high prevalence of coronary artery disease (44.9%), myocardial infarction (26.8%), heart failure (4.4%) and cerebrovascular accident (14.0%) which may have contributed to the decreased level of self-perceived QoL in these patients.²⁵

This aligned with a study by Golledge et al, who found that participants diagnosed with an AAA and peripheral artery disease not only had significantly poorer QoL scores in 5 SF-36 domains (PF, RP, GH, VT, and PCS)when compared with participants diagnosed with an AAA alone. They also had significantly poorer QoL scores in 7 domains of the SF-36 (PF, RP, GH, VT, SF, RE, and PCS) when compared with controls without an AAA.²⁶

Our analysis found that males with an AAA had a rise in SF-12v2 QoL scores from baseline to 12-month follow-up in the GH and BP domains. There was no statistically significant difference in QoL in the other 6 domains (PF, RP, VT, SF, RE, and MH) between the initial and 12-month investigations. Bath et al also found that men with an AAA had a transient reduction in mental QoL during the first year after the initial screening but returned to baseline.²³

Strengths and Limitations

This study is notable for its sample of patients who previously had a diagnosed AAA that were followed with a recorded clinical imaging study and the use of a validated QoL measure (SF-12v2) that provided virtually identical summary scores (PCS and MCS) as the SF-36.27 However, this study was limited by the brevity of the SF-12v2 instrument which made it difficult to extract sufficient reliable information for the 8 domains.²⁸ Subjective perception of patients is another limitation inherent to any QoL study. QoL scores were not available before the initial investigation. Measuring QoL at baseline and 12 months later does not capture the potential fluctuations and changes in QoL that the patient may experience some months later. Another limitation arises from the fact that the AAA patient population in the study included patients under surveillance and patients who had undergone repair.

Fourteen patients (15%) had received AAA repair: 10 had endovascular reconstruction and 4 had open surgical repair. Including patients with a previous AAA repair may have influenced reported QoL levels. Suckow et al performed a 2-phase study on 1008 patients, 351 (35%) were under surveillance and 657 (65%) had undergone repair. In that study, patients under AAA surveillance had worse emotional impact scores compared with patients with repair (22 vs 13; P < .001).¹¹ Additionally, the size of the abdominal aorta at the time of survey was not addressed in the study, which could constitute explanatory variables.

Conclusions

This study found higher QoL at 12-month follow-up compared to baseline in both the GH and BP domains of the SF-12v2 health survey for male veterans with an AAA. Periodic QoL assessments for patients with an AAA may be helpful in tracking QoL course, minimizing their physical and psychological concerns, and improving overall care and support. However, further research is necessary to assess the QoL of patients with an AAA who are under surveillance compared with those who had an aneurysm repair to accurately measure the impact of an AAA on QoL.

The number of US Department of Veterans Affairs (VA) hospitals receiving high scores in the Centers for Medicare & Medicaid Services (CMS) annual survey of quality measures is on the rise.

In 2023, VA hospitals became eligible to receive Overall Hospital Quality Star Ratings from the survey. In 2025, the survey covered 4609 hospitals (VA and non-VA). CMS analyzed 45 hospital quality measures across 5 different groups: mortality, safety of care, readmission, patient experience, and timely and effective care. The better the performance in these areas, the higher the star rating.

In the current ratings, 77% of surveyed VA hospitals earned 4- or 5-star ratings, a double digit increase over the previous 2 years (67% in 2023 and 58% in 2024). No VA hospitals received a 1-star rating, and > 90% of VA hospitals that received ratings maintained or improved on their 2024 mark. 

“These ratings highlight the excellent care VA hospitals provide,” VA Secretary Doug Collins said. “Our job is to continue raising the bar for customer service and convenience throughout the department, so VA works better for the Veterans, families, caregivers and survivors we are charged with serving.”

According to a report from the Advisory Board, fewer hospitals are receiving 5-star ratings than ever, possibly due to the COVID-19 pandemic. According to CMS, of all the hospitals that received a rating, 291 earned 5 stars, 90 fewer than in 2024. At the same time, the number of hospitals with 1-star ratings dropped slightly, from 277 in 2024 to 233 in 2025.

The VA publishes its own data on its medical centers. VA Core Hospital Measures have been available from the Joint Commission since 2005. Additional performance measures, including safety, effectiveness, efficiency, timeliness, patient centeredness, and equity, have been published by the VA since 2008. In 2010, the VA began reporting on Hospital Compare, which has information about the quality of care at > 4000 Medicare-certified hospitals, including > 130 VA medical centers and > 50 military hospitals.

The number of US Department of Veterans Affairs (VA) hospitals receiving high scores in the Centers for Medicare & Medicaid Services (CMS) annual survey of quality measures is on the rise.

In 2023, VA hospitals became eligible to receive Overall Hospital Quality Star Ratings from the survey. In 2025, the survey covered 4609 hospitals (VA and non-VA). CMS analyzed 45 hospital quality measures across 5 different groups: mortality, safety of care, readmission, patient experience, and timely and effective care. The better the performance in these areas, the higher the star rating.

In the current ratings, 77% of surveyed VA hospitals earned 4- or 5-star ratings, a double digit increase over the previous 2 years (67% in 2023 and 58% in 2024). No VA hospitals received a 1-star rating, and > 90% of VA hospitals that received ratings maintained or improved on their 2024 mark. 

“These ratings highlight the excellent care VA hospitals provide,” VA Secretary Doug Collins said. “Our job is to continue raising the bar for customer service and convenience throughout the department, so VA works better for the Veterans, families, caregivers and survivors we are charged with serving.”

According to a report from the Advisory Board, fewer hospitals are receiving 5-star ratings than ever, possibly due to the COVID-19 pandemic. According to CMS, of all the hospitals that received a rating, 291 earned 5 stars, 90 fewer than in 2024. At the same time, the number of hospitals with 1-star ratings dropped slightly, from 277 in 2024 to 233 in 2025.

The VA publishes its own data on its medical centers. VA Core Hospital Measures have been available from the Joint Commission since 2005. Additional performance measures, including safety, effectiveness, efficiency, timeliness, patient centeredness, and equity, have been published by the VA since 2008. In 2010, the VA began reporting on Hospital Compare, which has information about the quality of care at > 4000 Medicare-certified hospitals, including > 130 VA medical centers and > 50 military hospitals.

The number of US Department of Veterans Affairs (VA) hospitals receiving high scores in the Centers for Medicare & Medicaid Services (CMS) annual survey of quality measures is on the rise.

In 2023, VA hospitals became eligible to receive Overall Hospital Quality Star Ratings from the survey. In 2025, the survey covered 4609 hospitals (VA and non-VA). CMS analyzed 45 hospital quality measures across 5 different groups: mortality, safety of care, readmission, patient experience, and timely and effective care. The better the performance in these areas, the higher the star rating.

In the current ratings, 77% of surveyed VA hospitals earned 4- or 5-star ratings, a double digit increase over the previous 2 years (67% in 2023 and 58% in 2024). No VA hospitals received a 1-star rating, and > 90% of VA hospitals that received ratings maintained or improved on their 2024 mark. 

“These ratings highlight the excellent care VA hospitals provide,” VA Secretary Doug Collins said. “Our job is to continue raising the bar for customer service and convenience throughout the department, so VA works better for the Veterans, families, caregivers and survivors we are charged with serving.”

According to a report from the Advisory Board, fewer hospitals are receiving 5-star ratings than ever, possibly due to the COVID-19 pandemic. According to CMS, of all the hospitals that received a rating, 291 earned 5 stars, 90 fewer than in 2024. At the same time, the number of hospitals with 1-star ratings dropped slightly, from 277 in 2024 to 233 in 2025.

The VA publishes its own data on its medical centers. VA Core Hospital Measures have been available from the Joint Commission since 2005. Additional performance measures, including safety, effectiveness, efficiency, timeliness, patient centeredness, and equity, have been published by the VA since 2008. In 2010, the VA began reporting on Hospital Compare, which has information about the quality of care at > 4000 Medicare-certified hospitals, including > 130 VA medical centers and > 50 military hospitals.

The size of the Veterans Health Administration (VHA) workforce continues to contract according to the latest data released by the US Department of Veterans Affairs (VA). Applications for employment are down 44% in fiscal year (FY) 2025 with just 14,485 cumulative new hires and 28,969 losses. In 2024, the VHA had 416,667 workers—it now has 401,224. 

The reductions align with VA Secretary Doug Collins’ goal of downsizing the VA’s workforce by 30,000 employees by the end of 2025. In August, Collins outlined how a federal hiring freeze, deferred resignations, retirements, and normal attrition have eliminated the need for the "large-scale" reduction-in-force he proposed earlier this year.

Compared with July’s numbers, the VHA now employs 139 fewer medical officers/physicians, 418 fewer registered nurses, 107 fewer social workers, and 65 fewer psychologists. Staffing of licensed practical nurses, medical support assistants, and nursing assistants is also down (reduced by 77, 129, and 29, respectively). 

Retention rates for the first 2 years of onboarding hover around 80% for physicians and nurses. However, retention incentives have dropped from 19,484 to 8982 and recruitment incentives from 6069 to 1299.

In voluntary exit surveys, 78% of 6762 medical and dental staff who left said they would work again for the VA, while 79% said they would recommend the VA as an employer. These rates are down from a similar survey in May 2023 when 81% noted that they would work again for the VA and 82% would recommend the VA to others. Personal matters, geographic relocation, and poor working relationships with supervisors or colleagues were among the reasons cited for leaving in August 2025. 

Of 435 psychologists, 69% said they would work again for the VA, and 62% said they would recommend the VA as an employer (71% and 67%, respectively in May 2023). Their reasons for leaving in August 2025 included a lack of trust in senior leaders and policy or technology barriers to getting the work done.

An August survey from the Office of the Inspector General found that VHA facilities reported 4434 staffing shortages this fiscal year—a 50% increase from fiscal year 2024. Most (94%) of the 139 facilities reported severe shortages for medical officers, and 79% of facilities reported severe shortages for nurses. Due to the timing of the questionnaire, the responses did not yet reflect the full impact from workforce reshaping efforts.

The size of the Veterans Health Administration (VHA) workforce continues to contract according to the latest data released by the US Department of Veterans Affairs (VA). Applications for employment are down 44% in fiscal year (FY) 2025 with just 14,485 cumulative new hires and 28,969 losses. In 2024, the VHA had 416,667 workers—it now has 401,224. 

The reductions align with VA Secretary Doug Collins’ goal of downsizing the VA’s workforce by 30,000 employees by the end of 2025. In August, Collins outlined how a federal hiring freeze, deferred resignations, retirements, and normal attrition have eliminated the need for the "large-scale" reduction-in-force he proposed earlier this year.

Compared with July’s numbers, the VHA now employs 139 fewer medical officers/physicians, 418 fewer registered nurses, 107 fewer social workers, and 65 fewer psychologists. Staffing of licensed practical nurses, medical support assistants, and nursing assistants is also down (reduced by 77, 129, and 29, respectively). 

Retention rates for the first 2 years of onboarding hover around 80% for physicians and nurses. However, retention incentives have dropped from 19,484 to 8982 and recruitment incentives from 6069 to 1299.

In voluntary exit surveys, 78% of 6762 medical and dental staff who left said they would work again for the VA, while 79% said they would recommend the VA as an employer. These rates are down from a similar survey in May 2023 when 81% noted that they would work again for the VA and 82% would recommend the VA to others. Personal matters, geographic relocation, and poor working relationships with supervisors or colleagues were among the reasons cited for leaving in August 2025. 

Of 435 psychologists, 69% said they would work again for the VA, and 62% said they would recommend the VA as an employer (71% and 67%, respectively in May 2023). Their reasons for leaving in August 2025 included a lack of trust in senior leaders and policy or technology barriers to getting the work done.

An August survey from the Office of the Inspector General found that VHA facilities reported 4434 staffing shortages this fiscal year—a 50% increase from fiscal year 2024. Most (94%) of the 139 facilities reported severe shortages for medical officers, and 79% of facilities reported severe shortages for nurses. Due to the timing of the questionnaire, the responses did not yet reflect the full impact from workforce reshaping efforts.

The size of the Veterans Health Administration (VHA) workforce continues to contract according to the latest data released by the US Department of Veterans Affairs (VA). Applications for employment are down 44% in fiscal year (FY) 2025 with just 14,485 cumulative new hires and 28,969 losses. In 2024, the VHA had 416,667 workers—it now has 401,224. 

The reductions align with VA Secretary Doug Collins’ goal of downsizing the VA’s workforce by 30,000 employees by the end of 2025. In August, Collins outlined how a federal hiring freeze, deferred resignations, retirements, and normal attrition have eliminated the need for the "large-scale" reduction-in-force he proposed earlier this year.

Compared with July’s numbers, the VHA now employs 139 fewer medical officers/physicians, 418 fewer registered nurses, 107 fewer social workers, and 65 fewer psychologists. Staffing of licensed practical nurses, medical support assistants, and nursing assistants is also down (reduced by 77, 129, and 29, respectively). 

Retention rates for the first 2 years of onboarding hover around 80% for physicians and nurses. However, retention incentives have dropped from 19,484 to 8982 and recruitment incentives from 6069 to 1299.

In voluntary exit surveys, 78% of 6762 medical and dental staff who left said they would work again for the VA, while 79% said they would recommend the VA as an employer. These rates are down from a similar survey in May 2023 when 81% noted that they would work again for the VA and 82% would recommend the VA to others. Personal matters, geographic relocation, and poor working relationships with supervisors or colleagues were among the reasons cited for leaving in August 2025. 

Of 435 psychologists, 69% said they would work again for the VA, and 62% said they would recommend the VA as an employer (71% and 67%, respectively in May 2023). Their reasons for leaving in August 2025 included a lack of trust in senior leaders and policy or technology barriers to getting the work done.

An August survey from the Office of the Inspector General found that VHA facilities reported 4434 staffing shortages this fiscal year—a 50% increase from fiscal year 2024. Most (94%) of the 139 facilities reported severe shortages for medical officers, and 79% of facilities reported severe shortages for nurses. Due to the timing of the questionnaire, the responses did not yet reflect the full impact from workforce reshaping efforts.