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Combo delivers ‘impressive’ survival results in first-line RCC setting
Results from the phase 3 trial were reported at the 2021 Genitourinary Cancers Symposium (Abstract 269) and simultaneously published in the New England Journal of Medicine.
Early-phase trials have shown the promise of targeting RCC from two angles, with both antiangiogenic therapy and immunotherapy, said presenter Robert J. Motzer, MD, of Memorial Sloan Kettering Cancer Center, New York.
The CLEAR trial was designed to compare monotherapy with sunitinib to treatment with lenvatinib plus either pembrolizumab or everolimus.
The risk of progression-free survival events was 61% lower with lenvatinib-pembrolizumab and 35% lower with lenvatinib-everolimus, compared with sunitinib. However, only the first combination significantly reduced the risk of death.
Treatment-related adverse events were more common with both combinations but manageable with dose modifications.
“These results support lenvatinib plus pembrolizumab as a potential first-line treatment for patients with advanced RCC,” Dr. Motzer said.
Oncologists will likely soon have a handful of first-line options from which to choose, he acknowledged.
“It is a great situation, that we have made such progress in RCC with IO [immuno-oncology] therapy in the first line with ipilimumab-nivolumab, and now with the IO-TKI [tyrosine kinase inhibitor] combinations,” Dr. Motzer said.
The choice will probably come down to personal preference, experience with the various combinations, and side effect profiles, he speculated.
“I will say, however, that the data with lenvatinib-pembrolizumab is very impressive in terms of the long progression-free survival, in terms of the doubling of response rate to over 70%, in terms of the 16% complete response rate,” he said.
Trial details
The CLEAR investigators evenly randomized 1,069 patients with advanced clear-cell RCC who had not received prior systemic therapy to treatment with lenvatinib-pembrolizumab, lenvatinib-everolimus, or sunitinib.
The primary analysis was conducted at a median follow-up of 27 months.
The median progression-free survival was 9.2 months with sunitinib, 23.9 months with lenvatinib-pembrolizumab (hazard ratio, 0.39; P < .001), and 14.7 months with lenvatinib-everolimus (HR for events, 0.65; P < .001).
Findings were similar across key subgroups, including International Metastatic RCC Database Consortium risk groups.
An interim analysis of overall survival showed that patients lived significantly longer with lenvatinib-pembrolizumab versus sunitinib (HR, 0.66; P = .005), with similar benefit across subgroups, except for the favorable risk group.
In contrast, lenvatinib-everolimus did not significantly improve overall survival (HR, 1.15; P = .3). The median overall survival was not reached in any treatment arm.
“To me, this emphasizes the role of IO therapy combinations in the first line. I think you need the IO in the first line to get the dramatic efficacy results that we saw in the CLEAR study,” Dr. Motzer said.
The confirmed objective response rate was 36.1% with sunitinib, 71.0% with lenvatinib-pembrolizumab (relative risk, 1.97; P < .001), and 53.5% with lenvatinib-everolimus (RR, 1.48; P <.001). The median duration of response was 14.6 months, 25.8 months, and 16.6 months, respectively.
Grade 3 or higher treatment-related adverse events occurred in 58.8% of patients in the sunitinib group, 71.6% of the lenvatinib-pembrolizumab group, and 73.0% of the lenvatinib-everolimus group. The higher rates with the combinations likely reflected longer treatment durations, according to Dr. Motzer.
The most common grade 3 or higher events with lenvatinib-pembrolizumab were hypertension (25.3%), diarrhea (8.2%), and proteinuria (7.4%). The most common grade 3 or higher events with lenvatinib-everolimus were hypertension (20.8%), hypertriglyceridemia (10.1%), and diarrhea (9.6%).
“The relatively low rates of hepatic toxicity, lack of myelosuppression, and low rate of high-grade hand-foot syndrome is an attractive feature for lenvatinib in combination,” Dr. Motzer said.
Which combination, which sequence?
“Lenvatinib plus pembrolizumab is another novel combination to have in our armamentarium now for first-line clear-cell RCC,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
CLEAR is the fourth positive trial of combination tyrosine kinase inhibitor therapy and immunotherapy in this setting, although findings and study populations differ somewhat, and longer follow-up is needed, she said.
“None of these combinations have been directly compared to one another, and I don’t believe they will be compared head to head,” Dr. Berg said. “But other characteristics – for example, health-related quality of life, familiarity of the agents for clinicians, and high tumor burden versus slow-growing disease – may become important to choose the best first-line option for our patients.”
The emerging first-line options also raise some questions about the optimal sequencing of agents, according to Dr. Berg.
“If one starts with combination immunotherapy, it becomes an automatic choice to use a VEGF tyrosine kinase inhibitor second line,” she elaborated. “These trials establish that immuno-oncology–tyrosine kinase inhibitor combination therapy is now standard of care, but our second-line choice is less clear. Therefore, data is needed on the most suitable order of therapy for the entire population, as well as specific groups in the future.”
The CLEAR trial was sponsored by Eisai Inc. and Merck Sharp & Dohme Corp. Dr. Motzer disclosed relationships with Eisai, Merck, and many other companies. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
Results from the phase 3 trial were reported at the 2021 Genitourinary Cancers Symposium (Abstract 269) and simultaneously published in the New England Journal of Medicine.
Early-phase trials have shown the promise of targeting RCC from two angles, with both antiangiogenic therapy and immunotherapy, said presenter Robert J. Motzer, MD, of Memorial Sloan Kettering Cancer Center, New York.
The CLEAR trial was designed to compare monotherapy with sunitinib to treatment with lenvatinib plus either pembrolizumab or everolimus.
The risk of progression-free survival events was 61% lower with lenvatinib-pembrolizumab and 35% lower with lenvatinib-everolimus, compared with sunitinib. However, only the first combination significantly reduced the risk of death.
Treatment-related adverse events were more common with both combinations but manageable with dose modifications.
“These results support lenvatinib plus pembrolizumab as a potential first-line treatment for patients with advanced RCC,” Dr. Motzer said.
Oncologists will likely soon have a handful of first-line options from which to choose, he acknowledged.
“It is a great situation, that we have made such progress in RCC with IO [immuno-oncology] therapy in the first line with ipilimumab-nivolumab, and now with the IO-TKI [tyrosine kinase inhibitor] combinations,” Dr. Motzer said.
The choice will probably come down to personal preference, experience with the various combinations, and side effect profiles, he speculated.
“I will say, however, that the data with lenvatinib-pembrolizumab is very impressive in terms of the long progression-free survival, in terms of the doubling of response rate to over 70%, in terms of the 16% complete response rate,” he said.
Trial details
The CLEAR investigators evenly randomized 1,069 patients with advanced clear-cell RCC who had not received prior systemic therapy to treatment with lenvatinib-pembrolizumab, lenvatinib-everolimus, or sunitinib.
The primary analysis was conducted at a median follow-up of 27 months.
The median progression-free survival was 9.2 months with sunitinib, 23.9 months with lenvatinib-pembrolizumab (hazard ratio, 0.39; P < .001), and 14.7 months with lenvatinib-everolimus (HR for events, 0.65; P < .001).
Findings were similar across key subgroups, including International Metastatic RCC Database Consortium risk groups.
An interim analysis of overall survival showed that patients lived significantly longer with lenvatinib-pembrolizumab versus sunitinib (HR, 0.66; P = .005), with similar benefit across subgroups, except for the favorable risk group.
In contrast, lenvatinib-everolimus did not significantly improve overall survival (HR, 1.15; P = .3). The median overall survival was not reached in any treatment arm.
“To me, this emphasizes the role of IO therapy combinations in the first line. I think you need the IO in the first line to get the dramatic efficacy results that we saw in the CLEAR study,” Dr. Motzer said.
The confirmed objective response rate was 36.1% with sunitinib, 71.0% with lenvatinib-pembrolizumab (relative risk, 1.97; P < .001), and 53.5% with lenvatinib-everolimus (RR, 1.48; P <.001). The median duration of response was 14.6 months, 25.8 months, and 16.6 months, respectively.
Grade 3 or higher treatment-related adverse events occurred in 58.8% of patients in the sunitinib group, 71.6% of the lenvatinib-pembrolizumab group, and 73.0% of the lenvatinib-everolimus group. The higher rates with the combinations likely reflected longer treatment durations, according to Dr. Motzer.
The most common grade 3 or higher events with lenvatinib-pembrolizumab were hypertension (25.3%), diarrhea (8.2%), and proteinuria (7.4%). The most common grade 3 or higher events with lenvatinib-everolimus were hypertension (20.8%), hypertriglyceridemia (10.1%), and diarrhea (9.6%).
“The relatively low rates of hepatic toxicity, lack of myelosuppression, and low rate of high-grade hand-foot syndrome is an attractive feature for lenvatinib in combination,” Dr. Motzer said.
Which combination, which sequence?
“Lenvatinib plus pembrolizumab is another novel combination to have in our armamentarium now for first-line clear-cell RCC,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
CLEAR is the fourth positive trial of combination tyrosine kinase inhibitor therapy and immunotherapy in this setting, although findings and study populations differ somewhat, and longer follow-up is needed, she said.
“None of these combinations have been directly compared to one another, and I don’t believe they will be compared head to head,” Dr. Berg said. “But other characteristics – for example, health-related quality of life, familiarity of the agents for clinicians, and high tumor burden versus slow-growing disease – may become important to choose the best first-line option for our patients.”
The emerging first-line options also raise some questions about the optimal sequencing of agents, according to Dr. Berg.
“If one starts with combination immunotherapy, it becomes an automatic choice to use a VEGF tyrosine kinase inhibitor second line,” she elaborated. “These trials establish that immuno-oncology–tyrosine kinase inhibitor combination therapy is now standard of care, but our second-line choice is less clear. Therefore, data is needed on the most suitable order of therapy for the entire population, as well as specific groups in the future.”
The CLEAR trial was sponsored by Eisai Inc. and Merck Sharp & Dohme Corp. Dr. Motzer disclosed relationships with Eisai, Merck, and many other companies. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
Results from the phase 3 trial were reported at the 2021 Genitourinary Cancers Symposium (Abstract 269) and simultaneously published in the New England Journal of Medicine.
Early-phase trials have shown the promise of targeting RCC from two angles, with both antiangiogenic therapy and immunotherapy, said presenter Robert J. Motzer, MD, of Memorial Sloan Kettering Cancer Center, New York.
The CLEAR trial was designed to compare monotherapy with sunitinib to treatment with lenvatinib plus either pembrolizumab or everolimus.
The risk of progression-free survival events was 61% lower with lenvatinib-pembrolizumab and 35% lower with lenvatinib-everolimus, compared with sunitinib. However, only the first combination significantly reduced the risk of death.
Treatment-related adverse events were more common with both combinations but manageable with dose modifications.
“These results support lenvatinib plus pembrolizumab as a potential first-line treatment for patients with advanced RCC,” Dr. Motzer said.
Oncologists will likely soon have a handful of first-line options from which to choose, he acknowledged.
“It is a great situation, that we have made such progress in RCC with IO [immuno-oncology] therapy in the first line with ipilimumab-nivolumab, and now with the IO-TKI [tyrosine kinase inhibitor] combinations,” Dr. Motzer said.
The choice will probably come down to personal preference, experience with the various combinations, and side effect profiles, he speculated.
“I will say, however, that the data with lenvatinib-pembrolizumab is very impressive in terms of the long progression-free survival, in terms of the doubling of response rate to over 70%, in terms of the 16% complete response rate,” he said.
Trial details
The CLEAR investigators evenly randomized 1,069 patients with advanced clear-cell RCC who had not received prior systemic therapy to treatment with lenvatinib-pembrolizumab, lenvatinib-everolimus, or sunitinib.
The primary analysis was conducted at a median follow-up of 27 months.
The median progression-free survival was 9.2 months with sunitinib, 23.9 months with lenvatinib-pembrolizumab (hazard ratio, 0.39; P < .001), and 14.7 months with lenvatinib-everolimus (HR for events, 0.65; P < .001).
Findings were similar across key subgroups, including International Metastatic RCC Database Consortium risk groups.
An interim analysis of overall survival showed that patients lived significantly longer with lenvatinib-pembrolizumab versus sunitinib (HR, 0.66; P = .005), with similar benefit across subgroups, except for the favorable risk group.
In contrast, lenvatinib-everolimus did not significantly improve overall survival (HR, 1.15; P = .3). The median overall survival was not reached in any treatment arm.
“To me, this emphasizes the role of IO therapy combinations in the first line. I think you need the IO in the first line to get the dramatic efficacy results that we saw in the CLEAR study,” Dr. Motzer said.
The confirmed objective response rate was 36.1% with sunitinib, 71.0% with lenvatinib-pembrolizumab (relative risk, 1.97; P < .001), and 53.5% with lenvatinib-everolimus (RR, 1.48; P <.001). The median duration of response was 14.6 months, 25.8 months, and 16.6 months, respectively.
Grade 3 or higher treatment-related adverse events occurred in 58.8% of patients in the sunitinib group, 71.6% of the lenvatinib-pembrolizumab group, and 73.0% of the lenvatinib-everolimus group. The higher rates with the combinations likely reflected longer treatment durations, according to Dr. Motzer.
The most common grade 3 or higher events with lenvatinib-pembrolizumab were hypertension (25.3%), diarrhea (8.2%), and proteinuria (7.4%). The most common grade 3 or higher events with lenvatinib-everolimus were hypertension (20.8%), hypertriglyceridemia (10.1%), and diarrhea (9.6%).
“The relatively low rates of hepatic toxicity, lack of myelosuppression, and low rate of high-grade hand-foot syndrome is an attractive feature for lenvatinib in combination,” Dr. Motzer said.
Which combination, which sequence?
“Lenvatinib plus pembrolizumab is another novel combination to have in our armamentarium now for first-line clear-cell RCC,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
CLEAR is the fourth positive trial of combination tyrosine kinase inhibitor therapy and immunotherapy in this setting, although findings and study populations differ somewhat, and longer follow-up is needed, she said.
“None of these combinations have been directly compared to one another, and I don’t believe they will be compared head to head,” Dr. Berg said. “But other characteristics – for example, health-related quality of life, familiarity of the agents for clinicians, and high tumor burden versus slow-growing disease – may become important to choose the best first-line option for our patients.”
The emerging first-line options also raise some questions about the optimal sequencing of agents, according to Dr. Berg.
“If one starts with combination immunotherapy, it becomes an automatic choice to use a VEGF tyrosine kinase inhibitor second line,” she elaborated. “These trials establish that immuno-oncology–tyrosine kinase inhibitor combination therapy is now standard of care, but our second-line choice is less clear. Therefore, data is needed on the most suitable order of therapy for the entire population, as well as specific groups in the future.”
The CLEAR trial was sponsored by Eisai Inc. and Merck Sharp & Dohme Corp. Dr. Motzer disclosed relationships with Eisai, Merck, and many other companies. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
FROM GUCS 2021
Cabozantinib could be new standard for papillary RCC
Compared with the VEGFR-2 inhibitor sunitinib, the MET inhibitor cabozantinib improved both response rate and progression-free survival. Two other MET inhibitors, crizotinib and savolitinib, were not more efficacious than sunitinib.
“To date, there have been no randomized data specifically in papillary RCC showing an advantage of one systemic therapy over another,” said Sumanta K. Pal, MD, of City of Hope National Medical Center, Duarte, Calif., when presenting results from SWOG 1500.
Dr. Pal presented the results at the 2021 Genitourinary Cancers Symposium (Abstract 270), and they were published simultaneously in The Lancet.
The SWOG 1500 trial, also known as the PAPMET trial, was undertaken given evidence that signaling in the MET pathway is a driver in a sizable proportion of papillary RCCs, Dr. Pal explained.
Compared with sunitinib, cabozantinib reduced the risk of progression-free survival events by 40% and netted a response rate that was almost six times higher. On the other hand, the crizotinib and savolitinib arms of the trial were stopped early because of futility.
“Cabozantinib should be considered the new reference standard for systemic therapy in patients with metastatic papillary RCC,” Dr. Pal recommended. At present, VEGF-directed therapy is used as standard of care.
Dr. Pal noted that current evidence supports only monotherapy in papillary disease.
“There may be a temptation to put a patient on a combination of cabozantinib with immunotherapy, and certainly there is data in the context of clear-cell disease to support that. But we have to stop and think. We don’t know yet if that actually results in benefit for our patients, and obviously, it could extend the spectrum of toxicities that they incur,” he added.
Dr. Pal therefore encouraged oncologists and their patients with papillary RCC to consider the planned PAPMET-2 trial, which will explore the benefits and risks of adding immunotherapy to cabozantinib for this patient population.
SWOG 1500 details
The phase 2 SWOG 1500 trial was conducted in 65 U.S. and Canadian centers. It enrolled 152 patients with metastatic papillary RCC who had received up to one prior systemic therapy, excluding sunitinib. The trial is the first exclusively in this patient population to complete accrual, Dr. Pal noted.
Patients were randomized evenly to sunitinib, cabozantinib, crizotinib, or savolitinib.
The investigators stopped accrual to the savolitinib and crizotinib arms early based on a prespecified futility analysis showing that the hazard ratios for progression-free survival, compared with sunitinib, exceeded 1.
For the remaining arms, the median progression-free survival was 9.0 months with cabozantinib and 5.6 months with sunitinib (hazard ratio for events, 0.60; one-sided P = .019), meeting the trial’s primary endpoint. Subgroup analyses numerically favored cabozantinib in both type I and type II disease.
The confirmed overall response rate was 23% with cabozantinib and 4% with sunitinib (two-sided P = .010). Respective rates of complete response were 5% and 0%.
The median overall survival was 20.0 months with cabozantinib and 16.4 months with sunitinib, a nonsignificant difference.
The investigators are conducting exploratory analyses of MET mutational status and MET expression, and their associations with outcomes, according to Dr. Pal. Findings of other studies are suggesting that MET-altered papillary RCC may be a distinct entity, which would support genomically driven studies, he noted.
The rate of grade 3-4 toxicity was 68% in the sunitinib group, 74% in the cabozantinib group, 37% in the crizotinib group, and 39% in the savolitinib group. The types of toxicities seen were similar to those observed with each agent in larger trials, Dr. Pal observed.
There was a single grade 5 event, a death secondary to thromboembolism in the cabozantinib arm.
MET alterations may be key
“We should consider cabozantinib as another first-line option for papillary kidney cancer,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
Dr. Berg noted that the phase 3 SAVOIR trial, recently published in JAMA Oncology, compared savolitinib against sunitinib in MET-driven papillary RCC and stopped recruitment early. Although the trial did not meet its primary endpoint of progression-free survival, it did show numerically better results with the MET inhibitor.
“I question if the savolitinib arm in SWOG 1500 may have fared better if tumors were exclusively MET driven, especially as type II papillary patients represented almost half of the total patient population, and typically, 40% express alterations in MET,” Dr. Berg commented. “We will have to wait for further exploratory analysis regarding MET mutational status to tease out these differences.”
SWOG 1500 was sponsored by the National Cancer Institute. Dr. Pal disclosed a consulting or advisory role with Astellas Pharma, Aveo, Bristol-Myers Squibb, Eisai, Exelixis, Genentech, Ipsen, Myriad Pharmaceuticals, Novartis, and Pfizer. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
Compared with the VEGFR-2 inhibitor sunitinib, the MET inhibitor cabozantinib improved both response rate and progression-free survival. Two other MET inhibitors, crizotinib and savolitinib, were not more efficacious than sunitinib.
“To date, there have been no randomized data specifically in papillary RCC showing an advantage of one systemic therapy over another,” said Sumanta K. Pal, MD, of City of Hope National Medical Center, Duarte, Calif., when presenting results from SWOG 1500.
Dr. Pal presented the results at the 2021 Genitourinary Cancers Symposium (Abstract 270), and they were published simultaneously in The Lancet.
The SWOG 1500 trial, also known as the PAPMET trial, was undertaken given evidence that signaling in the MET pathway is a driver in a sizable proportion of papillary RCCs, Dr. Pal explained.
Compared with sunitinib, cabozantinib reduced the risk of progression-free survival events by 40% and netted a response rate that was almost six times higher. On the other hand, the crizotinib and savolitinib arms of the trial were stopped early because of futility.
“Cabozantinib should be considered the new reference standard for systemic therapy in patients with metastatic papillary RCC,” Dr. Pal recommended. At present, VEGF-directed therapy is used as standard of care.
Dr. Pal noted that current evidence supports only monotherapy in papillary disease.
“There may be a temptation to put a patient on a combination of cabozantinib with immunotherapy, and certainly there is data in the context of clear-cell disease to support that. But we have to stop and think. We don’t know yet if that actually results in benefit for our patients, and obviously, it could extend the spectrum of toxicities that they incur,” he added.
Dr. Pal therefore encouraged oncologists and their patients with papillary RCC to consider the planned PAPMET-2 trial, which will explore the benefits and risks of adding immunotherapy to cabozantinib for this patient population.
SWOG 1500 details
The phase 2 SWOG 1500 trial was conducted in 65 U.S. and Canadian centers. It enrolled 152 patients with metastatic papillary RCC who had received up to one prior systemic therapy, excluding sunitinib. The trial is the first exclusively in this patient population to complete accrual, Dr. Pal noted.
Patients were randomized evenly to sunitinib, cabozantinib, crizotinib, or savolitinib.
The investigators stopped accrual to the savolitinib and crizotinib arms early based on a prespecified futility analysis showing that the hazard ratios for progression-free survival, compared with sunitinib, exceeded 1.
For the remaining arms, the median progression-free survival was 9.0 months with cabozantinib and 5.6 months with sunitinib (hazard ratio for events, 0.60; one-sided P = .019), meeting the trial’s primary endpoint. Subgroup analyses numerically favored cabozantinib in both type I and type II disease.
The confirmed overall response rate was 23% with cabozantinib and 4% with sunitinib (two-sided P = .010). Respective rates of complete response were 5% and 0%.
The median overall survival was 20.0 months with cabozantinib and 16.4 months with sunitinib, a nonsignificant difference.
The investigators are conducting exploratory analyses of MET mutational status and MET expression, and their associations with outcomes, according to Dr. Pal. Findings of other studies are suggesting that MET-altered papillary RCC may be a distinct entity, which would support genomically driven studies, he noted.
The rate of grade 3-4 toxicity was 68% in the sunitinib group, 74% in the cabozantinib group, 37% in the crizotinib group, and 39% in the savolitinib group. The types of toxicities seen were similar to those observed with each agent in larger trials, Dr. Pal observed.
There was a single grade 5 event, a death secondary to thromboembolism in the cabozantinib arm.
MET alterations may be key
“We should consider cabozantinib as another first-line option for papillary kidney cancer,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
Dr. Berg noted that the phase 3 SAVOIR trial, recently published in JAMA Oncology, compared savolitinib against sunitinib in MET-driven papillary RCC and stopped recruitment early. Although the trial did not meet its primary endpoint of progression-free survival, it did show numerically better results with the MET inhibitor.
“I question if the savolitinib arm in SWOG 1500 may have fared better if tumors were exclusively MET driven, especially as type II papillary patients represented almost half of the total patient population, and typically, 40% express alterations in MET,” Dr. Berg commented. “We will have to wait for further exploratory analysis regarding MET mutational status to tease out these differences.”
SWOG 1500 was sponsored by the National Cancer Institute. Dr. Pal disclosed a consulting or advisory role with Astellas Pharma, Aveo, Bristol-Myers Squibb, Eisai, Exelixis, Genentech, Ipsen, Myriad Pharmaceuticals, Novartis, and Pfizer. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
Compared with the VEGFR-2 inhibitor sunitinib, the MET inhibitor cabozantinib improved both response rate and progression-free survival. Two other MET inhibitors, crizotinib and savolitinib, were not more efficacious than sunitinib.
“To date, there have been no randomized data specifically in papillary RCC showing an advantage of one systemic therapy over another,” said Sumanta K. Pal, MD, of City of Hope National Medical Center, Duarte, Calif., when presenting results from SWOG 1500.
Dr. Pal presented the results at the 2021 Genitourinary Cancers Symposium (Abstract 270), and they were published simultaneously in The Lancet.
The SWOG 1500 trial, also known as the PAPMET trial, was undertaken given evidence that signaling in the MET pathway is a driver in a sizable proportion of papillary RCCs, Dr. Pal explained.
Compared with sunitinib, cabozantinib reduced the risk of progression-free survival events by 40% and netted a response rate that was almost six times higher. On the other hand, the crizotinib and savolitinib arms of the trial were stopped early because of futility.
“Cabozantinib should be considered the new reference standard for systemic therapy in patients with metastatic papillary RCC,” Dr. Pal recommended. At present, VEGF-directed therapy is used as standard of care.
Dr. Pal noted that current evidence supports only monotherapy in papillary disease.
“There may be a temptation to put a patient on a combination of cabozantinib with immunotherapy, and certainly there is data in the context of clear-cell disease to support that. But we have to stop and think. We don’t know yet if that actually results in benefit for our patients, and obviously, it could extend the spectrum of toxicities that they incur,” he added.
Dr. Pal therefore encouraged oncologists and their patients with papillary RCC to consider the planned PAPMET-2 trial, which will explore the benefits and risks of adding immunotherapy to cabozantinib for this patient population.
SWOG 1500 details
The phase 2 SWOG 1500 trial was conducted in 65 U.S. and Canadian centers. It enrolled 152 patients with metastatic papillary RCC who had received up to one prior systemic therapy, excluding sunitinib. The trial is the first exclusively in this patient population to complete accrual, Dr. Pal noted.
Patients were randomized evenly to sunitinib, cabozantinib, crizotinib, or savolitinib.
The investigators stopped accrual to the savolitinib and crizotinib arms early based on a prespecified futility analysis showing that the hazard ratios for progression-free survival, compared with sunitinib, exceeded 1.
For the remaining arms, the median progression-free survival was 9.0 months with cabozantinib and 5.6 months with sunitinib (hazard ratio for events, 0.60; one-sided P = .019), meeting the trial’s primary endpoint. Subgroup analyses numerically favored cabozantinib in both type I and type II disease.
The confirmed overall response rate was 23% with cabozantinib and 4% with sunitinib (two-sided P = .010). Respective rates of complete response were 5% and 0%.
The median overall survival was 20.0 months with cabozantinib and 16.4 months with sunitinib, a nonsignificant difference.
The investigators are conducting exploratory analyses of MET mutational status and MET expression, and their associations with outcomes, according to Dr. Pal. Findings of other studies are suggesting that MET-altered papillary RCC may be a distinct entity, which would support genomically driven studies, he noted.
The rate of grade 3-4 toxicity was 68% in the sunitinib group, 74% in the cabozantinib group, 37% in the crizotinib group, and 39% in the savolitinib group. The types of toxicities seen were similar to those observed with each agent in larger trials, Dr. Pal observed.
There was a single grade 5 event, a death secondary to thromboembolism in the cabozantinib arm.
MET alterations may be key
“We should consider cabozantinib as another first-line option for papillary kidney cancer,” said invited discussant Stephanie A. Berg, DO, of Loyola University Medical Center in Maywood, Ill.
Dr. Berg noted that the phase 3 SAVOIR trial, recently published in JAMA Oncology, compared savolitinib against sunitinib in MET-driven papillary RCC and stopped recruitment early. Although the trial did not meet its primary endpoint of progression-free survival, it did show numerically better results with the MET inhibitor.
“I question if the savolitinib arm in SWOG 1500 may have fared better if tumors were exclusively MET driven, especially as type II papillary patients represented almost half of the total patient population, and typically, 40% express alterations in MET,” Dr. Berg commented. “We will have to wait for further exploratory analysis regarding MET mutational status to tease out these differences.”
SWOG 1500 was sponsored by the National Cancer Institute. Dr. Pal disclosed a consulting or advisory role with Astellas Pharma, Aveo, Bristol-Myers Squibb, Eisai, Exelixis, Genentech, Ipsen, Myriad Pharmaceuticals, Novartis, and Pfizer. Dr. Berg disclosed a consulting or advisory role with Bristol-Myers Squibb.
FROM GUCS 2021
CXR-Net: An AI-based diagnostic tool for COVID-19
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
FROM AACR: COVID-19 AND CANCER 2021
Asymptomatic screening for COVID-19 in cancer patients still debated
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
FROM AACR: COVID-19 AND CANCER 2021
Managing cancer outpatients during the pandemic: Tips from MSKCC
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
FROM AACR: COVID-19 AND CANCER 2021
COVID-19 vaccination in cancer patients: NCCN outlines priorities
Vaccination timing considerations vary based on factors such as cancer and treatment type, and reasons for delaying vaccination in the general public also apply to cancer patients (recent COVID-19 exposure, for example).
In general, however, patients with cancer should be assigned to Centers for Disease Control and Prevention priority group 1 b/c and immunized when vaccination is available to them, the guidelines state. Exceptions to this recommendation include:
- Patients undergoing hematopoietic stem cell transplant or receiving engineered cellular therapy such as chimeric antigen receptor T-cell therapy. Vaccination should be delayed for at least 3 months in these patients to maximize vaccine efficacy. Caregivers of these patients, however, should be immunized when possible.
- Patients with hematologic malignancies who are receiving intensive cytotoxic chemotherapy, such as cytarabine- or anthracycline-based regimens for acute myeloid leukemia. Vaccination in these patients should be delayed until absolute neutrophil count recovery.
- Patients undergoing major surgery. Vaccination should occur at least a few days before or after surgery.
- Patients who have experienced a severe or immediate adverse reaction to any of the ingredients in the mRNA COVID-19 vaccines.
Conversely, vaccination should occur when available in patients with hematologic malignancies and marrow failure who are expected to have limited or no recovery, patients with hematologic malignancies who are on long-term maintenance therapy, and patients with solid tumors who are receiving cytotoxic chemotherapy, targeted therapy, checkpoint inhibitors and other immunotherapy, or radiotherapy.
Caregivers, household contacts, and other close contacts who are 16 years of age and older should be vaccinated whenever they are eligible.
Unique concerns in patients with cancer
The NCCN recommendations were developed to address the unique issues and concerns with respect to patients with cancer, who have an increased risk of severe illness from SARS-CoV-2 infection. But the guidelines come with a caveat: “[t]here are limited safety and efficacy data in these patients,” the NCCN emphasized in a press statement.
“Right now, there is urgent need and limited data,” Steven Pergam, MD, co-leader of the NCCN COVID-19 Vaccination Committee, said in the statement.
“Our number one goal is helping to get the vaccine to as many people as we can,” Dr. Pergam said. “That means following existing national and regional directions for prioritizing people who are more likely to face death or severe illness from COVID-19.”
Dr. Pergam, associate professor at Fred Hutchinson Cancer Research Center in Seattle, further explained that “people receiving active cancer treatment are at greater risk for worse outcomes from COVID-19, particularly if they are older and have additional comorbidities, like immunosuppression.”
NCCN’s recommendations couldn’t have come at a better time for patients with cancer, according to Nora Disis, MD, a professor at the University of Washington in Seattle.
“The NCCN’s recommendations to prioritize COVID vaccinations for cancer patients on active treatment is an important step forward in protecting our patients from the infection,” Dr. Disis said in an interview.
“Cancer patients may be at higher risk for the complications seen with infection. In addition, cancer is a disease of older people, and a good number of our patients have the comorbidities that would predict a poorer outcome if they should become sick,” Dr. Disis added. “With the correct treatment, many patients with cancer will be long-term survivors. It is important that they be protected from infection with COVID to realize their best outcome.”
Additional vaccine considerations
The NCCN recommendations also address several other issues of importance for cancer patients, including:
- Deprioritizing other vaccines. COVID-19 vaccines should take precedence over other vaccines because data on dual vaccination are lacking. The NCCN recommends waiting 14 days after COVID-19 vaccination to deliver other vaccines.
- Vaccinating clinical trial participants. Trial leads should be consulted to prevent protocol violations or exclusions.
- Decision-making in the setting of limited vaccine availability. The NCCN noted that decisions on allocation must be made in accordance with state and local vaccine guidance but suggests prioritizing appropriate patients on active treatment, those planning to start treatment, and those who have just completed treatment. Additional risk factors for these patients, as well as other factors associated with risk for adverse COVID-19 outcomes, should also be considered. These include advanced age, comorbidities, and adverse social and demographic factors such as poverty and limited health care access.
- The need for ongoing prevention measures. Vaccines have been shown to decrease the incidence of COVID-19 and related complications, but it remains unclear whether vaccines prevent infection and subsequent transmission. This means everyone should continue following prevention recommendations, such as wearing masks and avoiding crowds.
The NCCN stressed that these recommendations are “intended to be a living document that is constantly evolving – it will be updated rapidly whenever new data comes out, as well as any potential new vaccines that may get approved in the future.” The NCCN also noted that the advisory committee will meet regularly to refine the recommendations as needed.
Dr. Pergam disclosed relationships with Chimerix Inc., Merck & Co., Global Life Technologies Inc., and Sanofi-Aventis. Dr. Disis disclosed grants from Pfizer, Bavarian Nordisk, Janssen, and Precigen. She is the founder of EpiThany and editor-in-chief of JAMA Oncology.
Vaccination timing considerations vary based on factors such as cancer and treatment type, and reasons for delaying vaccination in the general public also apply to cancer patients (recent COVID-19 exposure, for example).
In general, however, patients with cancer should be assigned to Centers for Disease Control and Prevention priority group 1 b/c and immunized when vaccination is available to them, the guidelines state. Exceptions to this recommendation include:
- Patients undergoing hematopoietic stem cell transplant or receiving engineered cellular therapy such as chimeric antigen receptor T-cell therapy. Vaccination should be delayed for at least 3 months in these patients to maximize vaccine efficacy. Caregivers of these patients, however, should be immunized when possible.
- Patients with hematologic malignancies who are receiving intensive cytotoxic chemotherapy, such as cytarabine- or anthracycline-based regimens for acute myeloid leukemia. Vaccination in these patients should be delayed until absolute neutrophil count recovery.
- Patients undergoing major surgery. Vaccination should occur at least a few days before or after surgery.
- Patients who have experienced a severe or immediate adverse reaction to any of the ingredients in the mRNA COVID-19 vaccines.
Conversely, vaccination should occur when available in patients with hematologic malignancies and marrow failure who are expected to have limited or no recovery, patients with hematologic malignancies who are on long-term maintenance therapy, and patients with solid tumors who are receiving cytotoxic chemotherapy, targeted therapy, checkpoint inhibitors and other immunotherapy, or radiotherapy.
Caregivers, household contacts, and other close contacts who are 16 years of age and older should be vaccinated whenever they are eligible.
Unique concerns in patients with cancer
The NCCN recommendations were developed to address the unique issues and concerns with respect to patients with cancer, who have an increased risk of severe illness from SARS-CoV-2 infection. But the guidelines come with a caveat: “[t]here are limited safety and efficacy data in these patients,” the NCCN emphasized in a press statement.
“Right now, there is urgent need and limited data,” Steven Pergam, MD, co-leader of the NCCN COVID-19 Vaccination Committee, said in the statement.
“Our number one goal is helping to get the vaccine to as many people as we can,” Dr. Pergam said. “That means following existing national and regional directions for prioritizing people who are more likely to face death or severe illness from COVID-19.”
Dr. Pergam, associate professor at Fred Hutchinson Cancer Research Center in Seattle, further explained that “people receiving active cancer treatment are at greater risk for worse outcomes from COVID-19, particularly if they are older and have additional comorbidities, like immunosuppression.”
NCCN’s recommendations couldn’t have come at a better time for patients with cancer, according to Nora Disis, MD, a professor at the University of Washington in Seattle.
“The NCCN’s recommendations to prioritize COVID vaccinations for cancer patients on active treatment is an important step forward in protecting our patients from the infection,” Dr. Disis said in an interview.
“Cancer patients may be at higher risk for the complications seen with infection. In addition, cancer is a disease of older people, and a good number of our patients have the comorbidities that would predict a poorer outcome if they should become sick,” Dr. Disis added. “With the correct treatment, many patients with cancer will be long-term survivors. It is important that they be protected from infection with COVID to realize their best outcome.”
Additional vaccine considerations
The NCCN recommendations also address several other issues of importance for cancer patients, including:
- Deprioritizing other vaccines. COVID-19 vaccines should take precedence over other vaccines because data on dual vaccination are lacking. The NCCN recommends waiting 14 days after COVID-19 vaccination to deliver other vaccines.
- Vaccinating clinical trial participants. Trial leads should be consulted to prevent protocol violations or exclusions.
- Decision-making in the setting of limited vaccine availability. The NCCN noted that decisions on allocation must be made in accordance with state and local vaccine guidance but suggests prioritizing appropriate patients on active treatment, those planning to start treatment, and those who have just completed treatment. Additional risk factors for these patients, as well as other factors associated with risk for adverse COVID-19 outcomes, should also be considered. These include advanced age, comorbidities, and adverse social and demographic factors such as poverty and limited health care access.
- The need for ongoing prevention measures. Vaccines have been shown to decrease the incidence of COVID-19 and related complications, but it remains unclear whether vaccines prevent infection and subsequent transmission. This means everyone should continue following prevention recommendations, such as wearing masks and avoiding crowds.
The NCCN stressed that these recommendations are “intended to be a living document that is constantly evolving – it will be updated rapidly whenever new data comes out, as well as any potential new vaccines that may get approved in the future.” The NCCN also noted that the advisory committee will meet regularly to refine the recommendations as needed.
Dr. Pergam disclosed relationships with Chimerix Inc., Merck & Co., Global Life Technologies Inc., and Sanofi-Aventis. Dr. Disis disclosed grants from Pfizer, Bavarian Nordisk, Janssen, and Precigen. She is the founder of EpiThany and editor-in-chief of JAMA Oncology.
Vaccination timing considerations vary based on factors such as cancer and treatment type, and reasons for delaying vaccination in the general public also apply to cancer patients (recent COVID-19 exposure, for example).
In general, however, patients with cancer should be assigned to Centers for Disease Control and Prevention priority group 1 b/c and immunized when vaccination is available to them, the guidelines state. Exceptions to this recommendation include:
- Patients undergoing hematopoietic stem cell transplant or receiving engineered cellular therapy such as chimeric antigen receptor T-cell therapy. Vaccination should be delayed for at least 3 months in these patients to maximize vaccine efficacy. Caregivers of these patients, however, should be immunized when possible.
- Patients with hematologic malignancies who are receiving intensive cytotoxic chemotherapy, such as cytarabine- or anthracycline-based regimens for acute myeloid leukemia. Vaccination in these patients should be delayed until absolute neutrophil count recovery.
- Patients undergoing major surgery. Vaccination should occur at least a few days before or after surgery.
- Patients who have experienced a severe or immediate adverse reaction to any of the ingredients in the mRNA COVID-19 vaccines.
Conversely, vaccination should occur when available in patients with hematologic malignancies and marrow failure who are expected to have limited or no recovery, patients with hematologic malignancies who are on long-term maintenance therapy, and patients with solid tumors who are receiving cytotoxic chemotherapy, targeted therapy, checkpoint inhibitors and other immunotherapy, or radiotherapy.
Caregivers, household contacts, and other close contacts who are 16 years of age and older should be vaccinated whenever they are eligible.
Unique concerns in patients with cancer
The NCCN recommendations were developed to address the unique issues and concerns with respect to patients with cancer, who have an increased risk of severe illness from SARS-CoV-2 infection. But the guidelines come with a caveat: “[t]here are limited safety and efficacy data in these patients,” the NCCN emphasized in a press statement.
“Right now, there is urgent need and limited data,” Steven Pergam, MD, co-leader of the NCCN COVID-19 Vaccination Committee, said in the statement.
“Our number one goal is helping to get the vaccine to as many people as we can,” Dr. Pergam said. “That means following existing national and regional directions for prioritizing people who are more likely to face death or severe illness from COVID-19.”
Dr. Pergam, associate professor at Fred Hutchinson Cancer Research Center in Seattle, further explained that “people receiving active cancer treatment are at greater risk for worse outcomes from COVID-19, particularly if they are older and have additional comorbidities, like immunosuppression.”
NCCN’s recommendations couldn’t have come at a better time for patients with cancer, according to Nora Disis, MD, a professor at the University of Washington in Seattle.
“The NCCN’s recommendations to prioritize COVID vaccinations for cancer patients on active treatment is an important step forward in protecting our patients from the infection,” Dr. Disis said in an interview.
“Cancer patients may be at higher risk for the complications seen with infection. In addition, cancer is a disease of older people, and a good number of our patients have the comorbidities that would predict a poorer outcome if they should become sick,” Dr. Disis added. “With the correct treatment, many patients with cancer will be long-term survivors. It is important that they be protected from infection with COVID to realize their best outcome.”
Additional vaccine considerations
The NCCN recommendations also address several other issues of importance for cancer patients, including:
- Deprioritizing other vaccines. COVID-19 vaccines should take precedence over other vaccines because data on dual vaccination are lacking. The NCCN recommends waiting 14 days after COVID-19 vaccination to deliver other vaccines.
- Vaccinating clinical trial participants. Trial leads should be consulted to prevent protocol violations or exclusions.
- Decision-making in the setting of limited vaccine availability. The NCCN noted that decisions on allocation must be made in accordance with state and local vaccine guidance but suggests prioritizing appropriate patients on active treatment, those planning to start treatment, and those who have just completed treatment. Additional risk factors for these patients, as well as other factors associated with risk for adverse COVID-19 outcomes, should also be considered. These include advanced age, comorbidities, and adverse social and demographic factors such as poverty and limited health care access.
- The need for ongoing prevention measures. Vaccines have been shown to decrease the incidence of COVID-19 and related complications, but it remains unclear whether vaccines prevent infection and subsequent transmission. This means everyone should continue following prevention recommendations, such as wearing masks and avoiding crowds.
The NCCN stressed that these recommendations are “intended to be a living document that is constantly evolving – it will be updated rapidly whenever new data comes out, as well as any potential new vaccines that may get approved in the future.” The NCCN also noted that the advisory committee will meet regularly to refine the recommendations as needed.
Dr. Pergam disclosed relationships with Chimerix Inc., Merck & Co., Global Life Technologies Inc., and Sanofi-Aventis. Dr. Disis disclosed grants from Pfizer, Bavarian Nordisk, Janssen, and Precigen. She is the founder of EpiThany and editor-in-chief of JAMA Oncology.
Model predicts acute kidney injury in cancer patients a month in advance
A model that crunches data from routine blood tests can accurately identify cancer patients who will develop acute kidney injury (AKI) up to a month before it happens, according to a cohort study.
The algorithm spotted nearly 74% of the patients who went on to develop AKI within 30 days, providing a window for intervention and possibly prevention, according to investigators.
These results were reported at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (abstract PR-11).
“Cancer patients are a high-risk population for AKI due to the nature of their treatment and illness,” said presenter Lauren A. Scanlon, PhD, a data scientist at The Christie NHS Foundation Trust in Huddersfield, England. “AKI causes a huge disruption in treatment and distress for the patient, so it would be amazing if we could, say, predict the AKI before it occurs and prevent it from even happening.”
U.K. health care providers are already using an algorithm to monitor patients’ creatinine levels, comparing new values against historic ones, Dr. Scanlon explained. When that algorithm detects AKI, it issues an alert that triggers implementation of an AKI care bundle, including measures such as fluid monitoring and medication review, within 24 hours.
Taking this concept further, Dr. Scanlon and colleagues developed a random forest model, a type of machine learning algorithm, that incorporates other markers from blood tests routinely obtained for all patients, with the aim of predicting AKI up to 30 days in advance.
“Using routinely collected blood test results will ensure that the model is applicable to all our patients and can be implemented in an automated manner,” Dr. Scanlon noted.
The investigators developed and trained the model using 597,403 blood test results from 48,865 patients undergoing cancer treatment between January 2017 and May 2020.
The model assigns patients to five categories of risk for AKI in the next 30 days: very low, low, medium, high, and very high.
“We wanted the model to output in this way so that it could be used by clinicians alongside their own insight and knowledge on a case-by-case basis,” Dr. Scanlon explained.
The investigators then prospectively validated the model and its risk categories in another 9,913 patients who underwent cancer treatment between June and August 2020.
Using a model threshold of medium risk or higher, the model correctly predicted AKI in 330 (73.8%) of the 447 patients in the validation cohort who ultimately developed AKI.
“This is pretty amazing and shows that this model really is working and can correctly detect these AKIs up to 30 days before they occur, giving a huge window to put in place preventive strategies,” Dr. Scanlon said.
Among the 154 patients in whom the model incorrectly predicted AKI, 9 patients had only a single follow-up blood test and 17 patients did not have any, leaving their actual outcomes unclear.
“Given that AKI detection uses blood tests, an AKI in these patients was never confirmed,” Dr. Scanlon noted. “So this could give a potential benefit of the model that we never intended: It could reduce undiagnosed AKI by flagging those who are at risk.”
“Our next steps are to test the model through a technology clinical trial to see if putting intervention strategies in place does prevent these AKIs from taking place,” Dr. Scanlon concluded. “We are also going to move to ongoing monitoring of the model performance.”
Dr. Scanlon disclosed no conflicts of interest. The study did not receive specific funding.
A model that crunches data from routine blood tests can accurately identify cancer patients who will develop acute kidney injury (AKI) up to a month before it happens, according to a cohort study.
The algorithm spotted nearly 74% of the patients who went on to develop AKI within 30 days, providing a window for intervention and possibly prevention, according to investigators.
These results were reported at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (abstract PR-11).
“Cancer patients are a high-risk population for AKI due to the nature of their treatment and illness,” said presenter Lauren A. Scanlon, PhD, a data scientist at The Christie NHS Foundation Trust in Huddersfield, England. “AKI causes a huge disruption in treatment and distress for the patient, so it would be amazing if we could, say, predict the AKI before it occurs and prevent it from even happening.”
U.K. health care providers are already using an algorithm to monitor patients’ creatinine levels, comparing new values against historic ones, Dr. Scanlon explained. When that algorithm detects AKI, it issues an alert that triggers implementation of an AKI care bundle, including measures such as fluid monitoring and medication review, within 24 hours.
Taking this concept further, Dr. Scanlon and colleagues developed a random forest model, a type of machine learning algorithm, that incorporates other markers from blood tests routinely obtained for all patients, with the aim of predicting AKI up to 30 days in advance.
“Using routinely collected blood test results will ensure that the model is applicable to all our patients and can be implemented in an automated manner,” Dr. Scanlon noted.
The investigators developed and trained the model using 597,403 blood test results from 48,865 patients undergoing cancer treatment between January 2017 and May 2020.
The model assigns patients to five categories of risk for AKI in the next 30 days: very low, low, medium, high, and very high.
“We wanted the model to output in this way so that it could be used by clinicians alongside their own insight and knowledge on a case-by-case basis,” Dr. Scanlon explained.
The investigators then prospectively validated the model and its risk categories in another 9,913 patients who underwent cancer treatment between June and August 2020.
Using a model threshold of medium risk or higher, the model correctly predicted AKI in 330 (73.8%) of the 447 patients in the validation cohort who ultimately developed AKI.
“This is pretty amazing and shows that this model really is working and can correctly detect these AKIs up to 30 days before they occur, giving a huge window to put in place preventive strategies,” Dr. Scanlon said.
Among the 154 patients in whom the model incorrectly predicted AKI, 9 patients had only a single follow-up blood test and 17 patients did not have any, leaving their actual outcomes unclear.
“Given that AKI detection uses blood tests, an AKI in these patients was never confirmed,” Dr. Scanlon noted. “So this could give a potential benefit of the model that we never intended: It could reduce undiagnosed AKI by flagging those who are at risk.”
“Our next steps are to test the model through a technology clinical trial to see if putting intervention strategies in place does prevent these AKIs from taking place,” Dr. Scanlon concluded. “We are also going to move to ongoing monitoring of the model performance.”
Dr. Scanlon disclosed no conflicts of interest. The study did not receive specific funding.
A model that crunches data from routine blood tests can accurately identify cancer patients who will develop acute kidney injury (AKI) up to a month before it happens, according to a cohort study.
The algorithm spotted nearly 74% of the patients who went on to develop AKI within 30 days, providing a window for intervention and possibly prevention, according to investigators.
These results were reported at the AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging (abstract PR-11).
“Cancer patients are a high-risk population for AKI due to the nature of their treatment and illness,” said presenter Lauren A. Scanlon, PhD, a data scientist at The Christie NHS Foundation Trust in Huddersfield, England. “AKI causes a huge disruption in treatment and distress for the patient, so it would be amazing if we could, say, predict the AKI before it occurs and prevent it from even happening.”
U.K. health care providers are already using an algorithm to monitor patients’ creatinine levels, comparing new values against historic ones, Dr. Scanlon explained. When that algorithm detects AKI, it issues an alert that triggers implementation of an AKI care bundle, including measures such as fluid monitoring and medication review, within 24 hours.
Taking this concept further, Dr. Scanlon and colleagues developed a random forest model, a type of machine learning algorithm, that incorporates other markers from blood tests routinely obtained for all patients, with the aim of predicting AKI up to 30 days in advance.
“Using routinely collected blood test results will ensure that the model is applicable to all our patients and can be implemented in an automated manner,” Dr. Scanlon noted.
The investigators developed and trained the model using 597,403 blood test results from 48,865 patients undergoing cancer treatment between January 2017 and May 2020.
The model assigns patients to five categories of risk for AKI in the next 30 days: very low, low, medium, high, and very high.
“We wanted the model to output in this way so that it could be used by clinicians alongside their own insight and knowledge on a case-by-case basis,” Dr. Scanlon explained.
The investigators then prospectively validated the model and its risk categories in another 9,913 patients who underwent cancer treatment between June and August 2020.
Using a model threshold of medium risk or higher, the model correctly predicted AKI in 330 (73.8%) of the 447 patients in the validation cohort who ultimately developed AKI.
“This is pretty amazing and shows that this model really is working and can correctly detect these AKIs up to 30 days before they occur, giving a huge window to put in place preventive strategies,” Dr. Scanlon said.
Among the 154 patients in whom the model incorrectly predicted AKI, 9 patients had only a single follow-up blood test and 17 patients did not have any, leaving their actual outcomes unclear.
“Given that AKI detection uses blood tests, an AKI in these patients was never confirmed,” Dr. Scanlon noted. “So this could give a potential benefit of the model that we never intended: It could reduce undiagnosed AKI by flagging those who are at risk.”
“Our next steps are to test the model through a technology clinical trial to see if putting intervention strategies in place does prevent these AKIs from taking place,” Dr. Scanlon concluded. “We are also going to move to ongoing monitoring of the model performance.”
Dr. Scanlon disclosed no conflicts of interest. The study did not receive specific funding.
FROM AACR: AI, DIAGNOSIS, AND IMAGING 2021
COVID-19 vaccines and cancer patients: 4 things to know
Earlier this week, Medscape spoke with Nora Disis, MD, about vaccinating cancer patients. Disis is a medical oncologist and director of both the Institute of Translational Health Sciences and the Cancer Vaccine Institute, the University of Washington, Seattle, Washington. As editor-in-chief of JAMA Oncology, she has watched COVID-19 developments in the oncology community over the past year.
Here are a few themes that Disis said oncologists should be aware of as vaccines eventually begin reaching cancer patients.
We should expect cancer patients to respond to vaccines. Historically, some believed that cancer patients would be unable to mount an immune response to vaccines. Data on other viral vaccines have shown otherwise. For example, there has been a long history of studies of flu vaccination in cancer patients, and in general, those vaccines confer protection. Likewise for pneumococcal vaccine, which, generally speaking, cancer patients should receive.
Special cases may include hematologic malignancies in which the immune system has been destroyed and profound immunosuppression occurs. Data on immunization during this immunosuppressed period are scarce, but what data are available suggest that once cancer patients are through this immunosuppressed period, they can be vaccinated successfully.
The type of vaccine will probably be important for cancer patients. Currently, there are 61 coronavirus vaccines in human clinical trials, and 17 have reached the final stages of testing. At least 85 preclinical vaccines are under active investigation in animals.
Both the Pfizer-BioNTech and Moderna COVID vaccines are mRNA type. There are many other types, including protein-based vaccines, viral vector vaccines based on adenoviruses, and inactivated or attenuated coronavirus vaccines.
The latter vaccines, particularly attenuated live virus vaccines, may not be a good choice for cancer patients. Especially in those with rapidly progressing disease or on chemotherapy, attenuated live viruses may cause a low-grade infection.
Incidentally, the technology used in the genetic, or mRNA, vaccines developed by both Pfizer-BioNTech and Moderna was initially developed for fighting cancer, and studies have shown that patients can generate immune responses to cancer-associated proteins with this type of vaccine.
These genetic vaccines could turn out to be the most effective for cancer patients, especially those with solid tumors.
Our understanding is very limited right now. Neither the Pfizer-BioNTech nor the Moderna early data discuss cancer patients. Two of the most important questions for cancer patients are dosing and booster scheduling. Potential defects in lymphocyte function among cancer patients may require unique initial dosing and booster schedules. In terms of timing, it is unclear how active therapy might affect a patient’s immune response to vaccination and whether vaccines should be timed with therapy cycles.
Vaccine access may depend on whether cancer patients are viewed as a vulnerable population. Those at higher risk for severe COVID-19 clearly have a greater need for vaccination. While there are data suggesting that cancer patients are at higher risk, they are a bit murky, in part because cancer patients are a heterogeneous group. For example, there are data suggesting that lung and blood cancer patients fare worse. There is also a suggestion that, like in the general population, COVID risk in cancer patients remains driven by comorbidities.
It is likely, then, that personalized risk factors such as type of cancer therapy, site of disease, and comorbidities will shape individual choices about vaccination among cancer patients.
A version of this article first appeared on Medscape.com.
Earlier this week, Medscape spoke with Nora Disis, MD, about vaccinating cancer patients. Disis is a medical oncologist and director of both the Institute of Translational Health Sciences and the Cancer Vaccine Institute, the University of Washington, Seattle, Washington. As editor-in-chief of JAMA Oncology, she has watched COVID-19 developments in the oncology community over the past year.
Here are a few themes that Disis said oncologists should be aware of as vaccines eventually begin reaching cancer patients.
We should expect cancer patients to respond to vaccines. Historically, some believed that cancer patients would be unable to mount an immune response to vaccines. Data on other viral vaccines have shown otherwise. For example, there has been a long history of studies of flu vaccination in cancer patients, and in general, those vaccines confer protection. Likewise for pneumococcal vaccine, which, generally speaking, cancer patients should receive.
Special cases may include hematologic malignancies in which the immune system has been destroyed and profound immunosuppression occurs. Data on immunization during this immunosuppressed period are scarce, but what data are available suggest that once cancer patients are through this immunosuppressed period, they can be vaccinated successfully.
The type of vaccine will probably be important for cancer patients. Currently, there are 61 coronavirus vaccines in human clinical trials, and 17 have reached the final stages of testing. At least 85 preclinical vaccines are under active investigation in animals.
Both the Pfizer-BioNTech and Moderna COVID vaccines are mRNA type. There are many other types, including protein-based vaccines, viral vector vaccines based on adenoviruses, and inactivated or attenuated coronavirus vaccines.
The latter vaccines, particularly attenuated live virus vaccines, may not be a good choice for cancer patients. Especially in those with rapidly progressing disease or on chemotherapy, attenuated live viruses may cause a low-grade infection.
Incidentally, the technology used in the genetic, or mRNA, vaccines developed by both Pfizer-BioNTech and Moderna was initially developed for fighting cancer, and studies have shown that patients can generate immune responses to cancer-associated proteins with this type of vaccine.
These genetic vaccines could turn out to be the most effective for cancer patients, especially those with solid tumors.
Our understanding is very limited right now. Neither the Pfizer-BioNTech nor the Moderna early data discuss cancer patients. Two of the most important questions for cancer patients are dosing and booster scheduling. Potential defects in lymphocyte function among cancer patients may require unique initial dosing and booster schedules. In terms of timing, it is unclear how active therapy might affect a patient’s immune response to vaccination and whether vaccines should be timed with therapy cycles.
Vaccine access may depend on whether cancer patients are viewed as a vulnerable population. Those at higher risk for severe COVID-19 clearly have a greater need for vaccination. While there are data suggesting that cancer patients are at higher risk, they are a bit murky, in part because cancer patients are a heterogeneous group. For example, there are data suggesting that lung and blood cancer patients fare worse. There is also a suggestion that, like in the general population, COVID risk in cancer patients remains driven by comorbidities.
It is likely, then, that personalized risk factors such as type of cancer therapy, site of disease, and comorbidities will shape individual choices about vaccination among cancer patients.
A version of this article first appeared on Medscape.com.
Earlier this week, Medscape spoke with Nora Disis, MD, about vaccinating cancer patients. Disis is a medical oncologist and director of both the Institute of Translational Health Sciences and the Cancer Vaccine Institute, the University of Washington, Seattle, Washington. As editor-in-chief of JAMA Oncology, she has watched COVID-19 developments in the oncology community over the past year.
Here are a few themes that Disis said oncologists should be aware of as vaccines eventually begin reaching cancer patients.
We should expect cancer patients to respond to vaccines. Historically, some believed that cancer patients would be unable to mount an immune response to vaccines. Data on other viral vaccines have shown otherwise. For example, there has been a long history of studies of flu vaccination in cancer patients, and in general, those vaccines confer protection. Likewise for pneumococcal vaccine, which, generally speaking, cancer patients should receive.
Special cases may include hematologic malignancies in which the immune system has been destroyed and profound immunosuppression occurs. Data on immunization during this immunosuppressed period are scarce, but what data are available suggest that once cancer patients are through this immunosuppressed period, they can be vaccinated successfully.
The type of vaccine will probably be important for cancer patients. Currently, there are 61 coronavirus vaccines in human clinical trials, and 17 have reached the final stages of testing. At least 85 preclinical vaccines are under active investigation in animals.
Both the Pfizer-BioNTech and Moderna COVID vaccines are mRNA type. There are many other types, including protein-based vaccines, viral vector vaccines based on adenoviruses, and inactivated or attenuated coronavirus vaccines.
The latter vaccines, particularly attenuated live virus vaccines, may not be a good choice for cancer patients. Especially in those with rapidly progressing disease or on chemotherapy, attenuated live viruses may cause a low-grade infection.
Incidentally, the technology used in the genetic, or mRNA, vaccines developed by both Pfizer-BioNTech and Moderna was initially developed for fighting cancer, and studies have shown that patients can generate immune responses to cancer-associated proteins with this type of vaccine.
These genetic vaccines could turn out to be the most effective for cancer patients, especially those with solid tumors.
Our understanding is very limited right now. Neither the Pfizer-BioNTech nor the Moderna early data discuss cancer patients. Two of the most important questions for cancer patients are dosing and booster scheduling. Potential defects in lymphocyte function among cancer patients may require unique initial dosing and booster schedules. In terms of timing, it is unclear how active therapy might affect a patient’s immune response to vaccination and whether vaccines should be timed with therapy cycles.
Vaccine access may depend on whether cancer patients are viewed as a vulnerable population. Those at higher risk for severe COVID-19 clearly have a greater need for vaccination. While there are data suggesting that cancer patients are at higher risk, they are a bit murky, in part because cancer patients are a heterogeneous group. For example, there are data suggesting that lung and blood cancer patients fare worse. There is also a suggestion that, like in the general population, COVID risk in cancer patients remains driven by comorbidities.
It is likely, then, that personalized risk factors such as type of cancer therapy, site of disease, and comorbidities will shape individual choices about vaccination among cancer patients.
A version of this article first appeared on Medscape.com.
Study shows no link between race and mortality in clear cell RCC
The issue of race and survival in patients with clear cell renal cell carcinoma (ccRCC) has been debated in the literature.
Some studies have shown worse survival for Black patients, while others have suggested that Black race is instead a stand-in for social determinants, including access to care.
New research suggests that Black race is not correlated with increased mortality from ccRCC. These results were published in Urology.
“Despite well documented racial biases and race-specific outcomes in the health care landscape, our study found race was not associated with 5-year cause-specific survival from ccRCC,” wrote investigator Dhaval Jivanji, a medical student at Florida International University, Miami, and colleagues.
In their retrospective study, the investigators examined 5-year survival in ccRCC patients, comparing results across races. The team used data from the Surveillance Epidemiology, and End Results (SEER) database, which collects cancer data from 13 states using population-based cancer registries. They extracted data on demographics, prevalence, and mortality, in relation to ccRCC.
A total of 8,421 subjects with ccRCC were included in the analysis, which covered the years 2007-2015. The primary outcome was 5-year survival, defined as cause-specific mortality up to the first 60 months from time of cancer diagnosis.
In addition to race, variables included in the statistical model were age (18-50, 51-60, 61-70,71-80, >80), sex (male/female), SEER Summary tumor staging (localized, regionalized, distant), insurance status (uninsured, insured, insured not specific, Medicaid), and marital status (single, married/partner, separated/divorced/widowed).
Demographic determinism
In the adjusted analysis, the researchers found no association between race and 5-year cause-specific survival in patients with ccRCC.
The hazard ratios for death were 0.96 for Black patients, 1.01 for American Indian/Alaska Native patients, and 0.99 for Asian/Pacific Islander patients, with White patients as the comparator.
In terms of the other covariates studied, the researchers found that older age (>50 years) and the presence of regional or distant tumors were associated with an increased hazard of death, while female sex and having insurance were associated with a decreased hazard of death.
“Our study found that age, tumor stage, and insurance status are significantly associated with 5-year cause-specific survival. Future studies will benefit from complete assessment of other demographic factors, including income, medical comorbidities, and access to care. These are negative predictors, and [their] potential impact on overall survival should be considered by the clinician in treatment and management plans for RCC patients,” the researchers concluded.
In an editorial commentary published within the main article, Paul Russo, MD, of Weill Cornell Medicine, New York, stated: “Investigations such as this utilizing the SEER registries provide a 30,000-foot demographic view of some disease elements but lack important granularity, such as tumor size and grade, family income, critical medical comorbidities, and patient access to hospitals with surgical and medical oncologic expertise.”
Dr. Russo said it is well known that disparate access to diagnosis, surgical intervention, and expert treatment have an impact on survival.
He went on to ask: “Could African Americans have had superior outcomes if the data was controlled for these important variables? As urologic surgeons, we must join the greater medical community in understanding the root causes leading to structural racial and economic disparities, inequities in access to care, and the profound negative impact these disparities have on health outcomes in general and cancer outcomes specifically.”
The authors did not disclose funding or conflicts of interest.
SOURCE: Jivanji D et al. Urology. 2020. doi: 10.1016/j.urology.2020.10.055.
The issue of race and survival in patients with clear cell renal cell carcinoma (ccRCC) has been debated in the literature.
Some studies have shown worse survival for Black patients, while others have suggested that Black race is instead a stand-in for social determinants, including access to care.
New research suggests that Black race is not correlated with increased mortality from ccRCC. These results were published in Urology.
“Despite well documented racial biases and race-specific outcomes in the health care landscape, our study found race was not associated with 5-year cause-specific survival from ccRCC,” wrote investigator Dhaval Jivanji, a medical student at Florida International University, Miami, and colleagues.
In their retrospective study, the investigators examined 5-year survival in ccRCC patients, comparing results across races. The team used data from the Surveillance Epidemiology, and End Results (SEER) database, which collects cancer data from 13 states using population-based cancer registries. They extracted data on demographics, prevalence, and mortality, in relation to ccRCC.
A total of 8,421 subjects with ccRCC were included in the analysis, which covered the years 2007-2015. The primary outcome was 5-year survival, defined as cause-specific mortality up to the first 60 months from time of cancer diagnosis.
In addition to race, variables included in the statistical model were age (18-50, 51-60, 61-70,71-80, >80), sex (male/female), SEER Summary tumor staging (localized, regionalized, distant), insurance status (uninsured, insured, insured not specific, Medicaid), and marital status (single, married/partner, separated/divorced/widowed).
Demographic determinism
In the adjusted analysis, the researchers found no association between race and 5-year cause-specific survival in patients with ccRCC.
The hazard ratios for death were 0.96 for Black patients, 1.01 for American Indian/Alaska Native patients, and 0.99 for Asian/Pacific Islander patients, with White patients as the comparator.
In terms of the other covariates studied, the researchers found that older age (>50 years) and the presence of regional or distant tumors were associated with an increased hazard of death, while female sex and having insurance were associated with a decreased hazard of death.
“Our study found that age, tumor stage, and insurance status are significantly associated with 5-year cause-specific survival. Future studies will benefit from complete assessment of other demographic factors, including income, medical comorbidities, and access to care. These are negative predictors, and [their] potential impact on overall survival should be considered by the clinician in treatment and management plans for RCC patients,” the researchers concluded.
In an editorial commentary published within the main article, Paul Russo, MD, of Weill Cornell Medicine, New York, stated: “Investigations such as this utilizing the SEER registries provide a 30,000-foot demographic view of some disease elements but lack important granularity, such as tumor size and grade, family income, critical medical comorbidities, and patient access to hospitals with surgical and medical oncologic expertise.”
Dr. Russo said it is well known that disparate access to diagnosis, surgical intervention, and expert treatment have an impact on survival.
He went on to ask: “Could African Americans have had superior outcomes if the data was controlled for these important variables? As urologic surgeons, we must join the greater medical community in understanding the root causes leading to structural racial and economic disparities, inequities in access to care, and the profound negative impact these disparities have on health outcomes in general and cancer outcomes specifically.”
The authors did not disclose funding or conflicts of interest.
SOURCE: Jivanji D et al. Urology. 2020. doi: 10.1016/j.urology.2020.10.055.
The issue of race and survival in patients with clear cell renal cell carcinoma (ccRCC) has been debated in the literature.
Some studies have shown worse survival for Black patients, while others have suggested that Black race is instead a stand-in for social determinants, including access to care.
New research suggests that Black race is not correlated with increased mortality from ccRCC. These results were published in Urology.
“Despite well documented racial biases and race-specific outcomes in the health care landscape, our study found race was not associated with 5-year cause-specific survival from ccRCC,” wrote investigator Dhaval Jivanji, a medical student at Florida International University, Miami, and colleagues.
In their retrospective study, the investigators examined 5-year survival in ccRCC patients, comparing results across races. The team used data from the Surveillance Epidemiology, and End Results (SEER) database, which collects cancer data from 13 states using population-based cancer registries. They extracted data on demographics, prevalence, and mortality, in relation to ccRCC.
A total of 8,421 subjects with ccRCC were included in the analysis, which covered the years 2007-2015. The primary outcome was 5-year survival, defined as cause-specific mortality up to the first 60 months from time of cancer diagnosis.
In addition to race, variables included in the statistical model were age (18-50, 51-60, 61-70,71-80, >80), sex (male/female), SEER Summary tumor staging (localized, regionalized, distant), insurance status (uninsured, insured, insured not specific, Medicaid), and marital status (single, married/partner, separated/divorced/widowed).
Demographic determinism
In the adjusted analysis, the researchers found no association between race and 5-year cause-specific survival in patients with ccRCC.
The hazard ratios for death were 0.96 for Black patients, 1.01 for American Indian/Alaska Native patients, and 0.99 for Asian/Pacific Islander patients, with White patients as the comparator.
In terms of the other covariates studied, the researchers found that older age (>50 years) and the presence of regional or distant tumors were associated with an increased hazard of death, while female sex and having insurance were associated with a decreased hazard of death.
“Our study found that age, tumor stage, and insurance status are significantly associated with 5-year cause-specific survival. Future studies will benefit from complete assessment of other demographic factors, including income, medical comorbidities, and access to care. These are negative predictors, and [their] potential impact on overall survival should be considered by the clinician in treatment and management plans for RCC patients,” the researchers concluded.
In an editorial commentary published within the main article, Paul Russo, MD, of Weill Cornell Medicine, New York, stated: “Investigations such as this utilizing the SEER registries provide a 30,000-foot demographic view of some disease elements but lack important granularity, such as tumor size and grade, family income, critical medical comorbidities, and patient access to hospitals with surgical and medical oncologic expertise.”
Dr. Russo said it is well known that disparate access to diagnosis, surgical intervention, and expert treatment have an impact on survival.
He went on to ask: “Could African Americans have had superior outcomes if the data was controlled for these important variables? As urologic surgeons, we must join the greater medical community in understanding the root causes leading to structural racial and economic disparities, inequities in access to care, and the profound negative impact these disparities have on health outcomes in general and cancer outcomes specifically.”
The authors did not disclose funding or conflicts of interest.
SOURCE: Jivanji D et al. Urology. 2020. doi: 10.1016/j.urology.2020.10.055.
FROM UROLOGY
Four factors may predict better survival with cabozantinib in mRCC
Starting cabozantinib at 60 mg/day, prior nephrectomy, favorable- or intermediate-risk disease, and body mass index of 25 kg/m2 or higher were all significantly associated with better OS.
These findings were based on data from the early access program of the CABOREAL study and were recently published in the European Journal of Cancer.
“The CABOREAL study describes cabozantinib use in a real-life setting in the largest unselected population to date of patients with mRCC,” lead author Laurence Albiges, MD, PhD, of the Gustave Roussy Cancer Center in Villejuif, France, and colleagues wrote.
The retrospective study enrolled 410 patients with mRCC who were treated with at least one dose of cabozantinib between September 2016 and February 2018. Clinical data were collected from medical records at 26 oncology centers in France.
The researchers evaluated the real-world use of cabozantinib, including duration of therapy, treatment discontinuations, and dose changes. OS and predictive factors of OS were assessed as well.
The median age of study participants was 63.0 years (range, 56.0-70.0 years). Roughly a third of patients (33.4%) received two prior lines of therapy (33.4%), and 41.2% received three or more lines of therapy before cabozantinib. Overall, 85.6% of patients had clear cell histology.
The median duration of cabozantinib treatment was 7.6 months (range, 3.2-15.7 months). The starting dose was 60 mg, 40 mg, and 20 mg in 70.9%, 26.7%, and 2.0% of patients, respectively.
The dose was decreased in 57.0% of patients, 58.7% required a dose modification, and 15.6% required a modified dose schedule. The median average daily dose was 40.0 mg (range, 13.9-60.0 mg).
Adverse events were the main reason for dose modification or treatment interruption. In all, 92.5% of patients had a modification because of an adverse event, and 85.0% had an interruption because of an adverse event.
Upon permanent discontinuation of cabozantinib, more than half of patients (54.4%) received subsequent therapy, including nivolumab (47.8%), axitinib (21.7%), and everolimus (19.0%).
The median OS was 14.4 months (95% confidence interval, 12.4-16.2 months), and the 1-year OS rate was 56.5% (95% CI, 51.5-61.2%).
Factors significantly associated with longer OS included cabozantinib initiation at 60 mg/day (P = .0486), prior nephrectomy (P = .0109), favorable or intermediate risk according to the International Metastatic RCC Database Consortium (P < .0001), and body mass index of 25 kg/m2 or higher (P = .0021).
“We report, for the first time, that the daily dose of 60 mg cabozantinib at initiation is an independent predictive factor of OS in a multivariate analysis,” the researchers wrote.
“It is interesting to see real-world studies like this to help to widen our understanding of how to utilize drugs like cabozantinib,” commented Simon Crabb, MBBS, PhD, of the University of Southampton (England).
“In general, we would expect a less favorable prognosis in patients with non-clear cell histology, likely in part part due to the underlying biology of the disease,” he added.
Dr. Albiges and colleagues acknowledged that the retrospective design and lack of a prospective safety evaluation were two key limitations of their study. However, the authors maintain that the reported cabozantinib use and exposure rates are indicative of the real-world setting.
This study was sponsored by Ipsen. Several authors disclosed financial relationships with Amgen, Astellas Pharma, AstraZeneca, Bristol-Myers Squibb, Exelixis, Ipsen, and numerous other companies. Dr. Crabb reported having no conflicts of interest related to this work.
SOURCE: Albiges L et al. Eur J Cancer. 2020 Nov 27. doi: 10.1016/j.ejca.2020.09.030.
Starting cabozantinib at 60 mg/day, prior nephrectomy, favorable- or intermediate-risk disease, and body mass index of 25 kg/m2 or higher were all significantly associated with better OS.
These findings were based on data from the early access program of the CABOREAL study and were recently published in the European Journal of Cancer.
“The CABOREAL study describes cabozantinib use in a real-life setting in the largest unselected population to date of patients with mRCC,” lead author Laurence Albiges, MD, PhD, of the Gustave Roussy Cancer Center in Villejuif, France, and colleagues wrote.
The retrospective study enrolled 410 patients with mRCC who were treated with at least one dose of cabozantinib between September 2016 and February 2018. Clinical data were collected from medical records at 26 oncology centers in France.
The researchers evaluated the real-world use of cabozantinib, including duration of therapy, treatment discontinuations, and dose changes. OS and predictive factors of OS were assessed as well.
The median age of study participants was 63.0 years (range, 56.0-70.0 years). Roughly a third of patients (33.4%) received two prior lines of therapy (33.4%), and 41.2% received three or more lines of therapy before cabozantinib. Overall, 85.6% of patients had clear cell histology.
The median duration of cabozantinib treatment was 7.6 months (range, 3.2-15.7 months). The starting dose was 60 mg, 40 mg, and 20 mg in 70.9%, 26.7%, and 2.0% of patients, respectively.
The dose was decreased in 57.0% of patients, 58.7% required a dose modification, and 15.6% required a modified dose schedule. The median average daily dose was 40.0 mg (range, 13.9-60.0 mg).
Adverse events were the main reason for dose modification or treatment interruption. In all, 92.5% of patients had a modification because of an adverse event, and 85.0% had an interruption because of an adverse event.
Upon permanent discontinuation of cabozantinib, more than half of patients (54.4%) received subsequent therapy, including nivolumab (47.8%), axitinib (21.7%), and everolimus (19.0%).
The median OS was 14.4 months (95% confidence interval, 12.4-16.2 months), and the 1-year OS rate was 56.5% (95% CI, 51.5-61.2%).
Factors significantly associated with longer OS included cabozantinib initiation at 60 mg/day (P = .0486), prior nephrectomy (P = .0109), favorable or intermediate risk according to the International Metastatic RCC Database Consortium (P < .0001), and body mass index of 25 kg/m2 or higher (P = .0021).
“We report, for the first time, that the daily dose of 60 mg cabozantinib at initiation is an independent predictive factor of OS in a multivariate analysis,” the researchers wrote.
“It is interesting to see real-world studies like this to help to widen our understanding of how to utilize drugs like cabozantinib,” commented Simon Crabb, MBBS, PhD, of the University of Southampton (England).
“In general, we would expect a less favorable prognosis in patients with non-clear cell histology, likely in part part due to the underlying biology of the disease,” he added.
Dr. Albiges and colleagues acknowledged that the retrospective design and lack of a prospective safety evaluation were two key limitations of their study. However, the authors maintain that the reported cabozantinib use and exposure rates are indicative of the real-world setting.
This study was sponsored by Ipsen. Several authors disclosed financial relationships with Amgen, Astellas Pharma, AstraZeneca, Bristol-Myers Squibb, Exelixis, Ipsen, and numerous other companies. Dr. Crabb reported having no conflicts of interest related to this work.
SOURCE: Albiges L et al. Eur J Cancer. 2020 Nov 27. doi: 10.1016/j.ejca.2020.09.030.
Starting cabozantinib at 60 mg/day, prior nephrectomy, favorable- or intermediate-risk disease, and body mass index of 25 kg/m2 or higher were all significantly associated with better OS.
These findings were based on data from the early access program of the CABOREAL study and were recently published in the European Journal of Cancer.
“The CABOREAL study describes cabozantinib use in a real-life setting in the largest unselected population to date of patients with mRCC,” lead author Laurence Albiges, MD, PhD, of the Gustave Roussy Cancer Center in Villejuif, France, and colleagues wrote.
The retrospective study enrolled 410 patients with mRCC who were treated with at least one dose of cabozantinib between September 2016 and February 2018. Clinical data were collected from medical records at 26 oncology centers in France.
The researchers evaluated the real-world use of cabozantinib, including duration of therapy, treatment discontinuations, and dose changes. OS and predictive factors of OS were assessed as well.
The median age of study participants was 63.0 years (range, 56.0-70.0 years). Roughly a third of patients (33.4%) received two prior lines of therapy (33.4%), and 41.2% received three or more lines of therapy before cabozantinib. Overall, 85.6% of patients had clear cell histology.
The median duration of cabozantinib treatment was 7.6 months (range, 3.2-15.7 months). The starting dose was 60 mg, 40 mg, and 20 mg in 70.9%, 26.7%, and 2.0% of patients, respectively.
The dose was decreased in 57.0% of patients, 58.7% required a dose modification, and 15.6% required a modified dose schedule. The median average daily dose was 40.0 mg (range, 13.9-60.0 mg).
Adverse events were the main reason for dose modification or treatment interruption. In all, 92.5% of patients had a modification because of an adverse event, and 85.0% had an interruption because of an adverse event.
Upon permanent discontinuation of cabozantinib, more than half of patients (54.4%) received subsequent therapy, including nivolumab (47.8%), axitinib (21.7%), and everolimus (19.0%).
The median OS was 14.4 months (95% confidence interval, 12.4-16.2 months), and the 1-year OS rate was 56.5% (95% CI, 51.5-61.2%).
Factors significantly associated with longer OS included cabozantinib initiation at 60 mg/day (P = .0486), prior nephrectomy (P = .0109), favorable or intermediate risk according to the International Metastatic RCC Database Consortium (P < .0001), and body mass index of 25 kg/m2 or higher (P = .0021).
“We report, for the first time, that the daily dose of 60 mg cabozantinib at initiation is an independent predictive factor of OS in a multivariate analysis,” the researchers wrote.
“It is interesting to see real-world studies like this to help to widen our understanding of how to utilize drugs like cabozantinib,” commented Simon Crabb, MBBS, PhD, of the University of Southampton (England).
“In general, we would expect a less favorable prognosis in patients with non-clear cell histology, likely in part part due to the underlying biology of the disease,” he added.
Dr. Albiges and colleagues acknowledged that the retrospective design and lack of a prospective safety evaluation were two key limitations of their study. However, the authors maintain that the reported cabozantinib use and exposure rates are indicative of the real-world setting.
This study was sponsored by Ipsen. Several authors disclosed financial relationships with Amgen, Astellas Pharma, AstraZeneca, Bristol-Myers Squibb, Exelixis, Ipsen, and numerous other companies. Dr. Crabb reported having no conflicts of interest related to this work.
SOURCE: Albiges L et al. Eur J Cancer. 2020 Nov 27. doi: 10.1016/j.ejca.2020.09.030.
FROM THE EUROPEAN JOURNAL OF CANCER