AVAHO

TOPLINE:

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

METHODOLOGY:

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

TAKEAWAY:

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

IN PRACTICE:

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

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

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

TOPLINE:

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

METHODOLOGY:

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

TAKEAWAY:

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

IN PRACTICE:

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

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

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

TOPLINE:

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

METHODOLOGY:

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

TAKEAWAY:

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

IN PRACTICE:

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

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

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

TOPLINE:

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

METHODOLOGY:

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

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

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

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

 

TAKEAWAY:

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

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

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

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

 

IN PRACTICE:

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

TOPLINE:

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

METHODOLOGY:

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

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

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

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

 

TAKEAWAY:

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

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

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

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

 

IN PRACTICE:

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

TOPLINE:

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

METHODOLOGY:

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

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

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

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

 

TAKEAWAY:

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

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

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

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

 

IN PRACTICE:

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

SOURCE:

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

LIMITATIONS:

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

DISCLOSURES:

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

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

TOPLINE:

The incidence of skin cancer in England varied by ethnicity: White individuals had higher rates of melanoma, cutaneous squamous cell carcinoma, and basal cell carcinoma than Asian or Black individuals. In contrast, acral lentiginous melanoma was most common among Black individuals, whereas cutaneous T-cell lymphoma and Kaposi sarcoma were highest among those in the "Other" ethnic group.

METHODOLOGY:

• Researchers analysed all cases of cutaneous melanoma (melanoma and acral lentiginous melanoma), basal cell carcinoma, cutaneous squamous cell carcinoma, cutaneous T-cell lymphoma, and Kaposi sarcoma using data from the NHS National Disease Registration Service cancer registry between 2013 and 2020.
• Data collection incorporated ethnicity information from multiple health care datasets, including Clinical Outcomes and Services Dataset, Patient Administration System, Radiotherapy Dataset, Diagnostic Imaging Dataset, and Hospital Episode Statistics.
• A population analysis categorised patients into 7 standardised ethnic groups (on the basis of Office for National Statistics classifications): White, Asian, Chinese, Black, mixed, other, and unknown groups, with ethnicity data being self-reported by patients.
• Outcomes included European age-standardised rates calculated using the 2013 European Standard Population and reported per 100,000 person-years (PYs).

TAKEAWAY:

• White Individuals had 13-fold higher rates of cutaneous squamous cell carcinoma (61.75 per 100,000 PYs), 26-fold and 27-fold higher rates of basal cell carcinoma (153.69 per 100,000 PYs), and 33-fold and 16-fold higher rates of cutaneous melanoma (27.29 per 100,000 PYs) than Asian and Black individuals, respectively.
• Black individuals had the highest incidence of acral lentiginous melanoma (0.85 per 100,000 PYs), and those in the other ethnic group had the highest incidence of cutaneous T-cell lymphoma (1.74 per 100,000 PYs) and Kaposi sarcoma (1.57 per 100,000 PYs).
• The presentation of early-stage melanoma was low among Asian (53.5%), Black (62.4%), mixed (62.5%), and other (76.4%) ethnic groups compared to that among White ethnicities (79.8%).
• Acral lentiginous melanomas were less likely to get urgent suspected cancer pathway referrals than overall melanoma (40.1% vs 44.6%; P < .001) and more likely to be diagnosed late than overall melanoma (stage I/II at diagnosis; 72% vs 80%; P < .0001).

IN PRACTICE:

"The findings emphasise the need for better, targeted ethnicity data collection strategies to address incidence, outcomes and health care equity for not just skin cancer but all health conditions in underserved populations," the authors wrote. "While projects like the Global Burden of Disease have improved global health care reporting, continuous audit and improvement of collected data are essential to provide better care across people of all ethnicities."

SOURCE:

This study was led by Shehnaz Ahmed, British Association of Dermatologists, London, England. It was published online on September 10, 2025, in the British Journal of Dermatology.

LIMITATIONS:

Census data collection after every 10 years could have contributed to inaccurate population estimates and incidence rates. Small sample sizes in certain ethnic groups could have led to potential confounders, requiring a cautious interpretation of relative incidence. The NHS data included only self-reported ethnicity data with no available details of skin phototypes, skin tones, or racial ancestry. This study lacked granular ethnicity census data and stage data for basal cell carcinoma, cutaneous small cell carcinoma, and Kaposi sarcoma.

DISCLOSURES:

This research was supported through a partnership between the British Association of Dermatologists and NHS England's National Disease Registration Service. Two authors reported being employees of the British Association of Dermatologists.

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

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

TOPLINE:

The incidence of skin cancer in England varied by ethnicity: White individuals had higher rates of melanoma, cutaneous squamous cell carcinoma, and basal cell carcinoma than Asian or Black individuals. In contrast, acral lentiginous melanoma was most common among Black individuals, whereas cutaneous T-cell lymphoma and Kaposi sarcoma were highest among those in the "Other" ethnic group.

METHODOLOGY:

• Researchers analysed all cases of cutaneous melanoma (melanoma and acral lentiginous melanoma), basal cell carcinoma, cutaneous squamous cell carcinoma, cutaneous T-cell lymphoma, and Kaposi sarcoma using data from the NHS National Disease Registration Service cancer registry between 2013 and 2020.
• Data collection incorporated ethnicity information from multiple health care datasets, including Clinical Outcomes and Services Dataset, Patient Administration System, Radiotherapy Dataset, Diagnostic Imaging Dataset, and Hospital Episode Statistics.
• A population analysis categorised patients into 7 standardised ethnic groups (on the basis of Office for National Statistics classifications): White, Asian, Chinese, Black, mixed, other, and unknown groups, with ethnicity data being self-reported by patients.
• Outcomes included European age-standardised rates calculated using the 2013 European Standard Population and reported per 100,000 person-years (PYs).

TAKEAWAY:

• White Individuals had 13-fold higher rates of cutaneous squamous cell carcinoma (61.75 per 100,000 PYs), 26-fold and 27-fold higher rates of basal cell carcinoma (153.69 per 100,000 PYs), and 33-fold and 16-fold higher rates of cutaneous melanoma (27.29 per 100,000 PYs) than Asian and Black individuals, respectively.
• Black individuals had the highest incidence of acral lentiginous melanoma (0.85 per 100,000 PYs), and those in the other ethnic group had the highest incidence of cutaneous T-cell lymphoma (1.74 per 100,000 PYs) and Kaposi sarcoma (1.57 per 100,000 PYs).
• The presentation of early-stage melanoma was low among Asian (53.5%), Black (62.4%), mixed (62.5%), and other (76.4%) ethnic groups compared to that among White ethnicities (79.8%).
• Acral lentiginous melanomas were less likely to get urgent suspected cancer pathway referrals than overall melanoma (40.1% vs 44.6%; P < .001) and more likely to be diagnosed late than overall melanoma (stage I/II at diagnosis; 72% vs 80%; P < .0001).

IN PRACTICE:

"The findings emphasise the need for better, targeted ethnicity data collection strategies to address incidence, outcomes and health care equity for not just skin cancer but all health conditions in underserved populations," the authors wrote. "While projects like the Global Burden of Disease have improved global health care reporting, continuous audit and improvement of collected data are essential to provide better care across people of all ethnicities."

SOURCE:

This study was led by Shehnaz Ahmed, British Association of Dermatologists, London, England. It was published online on September 10, 2025, in the British Journal of Dermatology.

LIMITATIONS:

Census data collection after every 10 years could have contributed to inaccurate population estimates and incidence rates. Small sample sizes in certain ethnic groups could have led to potential confounders, requiring a cautious interpretation of relative incidence. The NHS data included only self-reported ethnicity data with no available details of skin phototypes, skin tones, or racial ancestry. This study lacked granular ethnicity census data and stage data for basal cell carcinoma, cutaneous small cell carcinoma, and Kaposi sarcoma.

DISCLOSURES:

This research was supported through a partnership between the British Association of Dermatologists and NHS England's National Disease Registration Service. Two authors reported being employees of the British Association of Dermatologists.

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

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

TOPLINE:

The incidence of skin cancer in England varied by ethnicity: White individuals had higher rates of melanoma, cutaneous squamous cell carcinoma, and basal cell carcinoma than Asian or Black individuals. In contrast, acral lentiginous melanoma was most common among Black individuals, whereas cutaneous T-cell lymphoma and Kaposi sarcoma were highest among those in the "Other" ethnic group.

METHODOLOGY:

• Researchers analysed all cases of cutaneous melanoma (melanoma and acral lentiginous melanoma), basal cell carcinoma, cutaneous squamous cell carcinoma, cutaneous T-cell lymphoma, and Kaposi sarcoma using data from the NHS National Disease Registration Service cancer registry between 2013 and 2020.
• Data collection incorporated ethnicity information from multiple health care datasets, including Clinical Outcomes and Services Dataset, Patient Administration System, Radiotherapy Dataset, Diagnostic Imaging Dataset, and Hospital Episode Statistics.
• A population analysis categorised patients into 7 standardised ethnic groups (on the basis of Office for National Statistics classifications): White, Asian, Chinese, Black, mixed, other, and unknown groups, with ethnicity data being self-reported by patients.
• Outcomes included European age-standardised rates calculated using the 2013 European Standard Population and reported per 100,000 person-years (PYs).

TAKEAWAY:

• White Individuals had 13-fold higher rates of cutaneous squamous cell carcinoma (61.75 per 100,000 PYs), 26-fold and 27-fold higher rates of basal cell carcinoma (153.69 per 100,000 PYs), and 33-fold and 16-fold higher rates of cutaneous melanoma (27.29 per 100,000 PYs) than Asian and Black individuals, respectively.
• Black individuals had the highest incidence of acral lentiginous melanoma (0.85 per 100,000 PYs), and those in the other ethnic group had the highest incidence of cutaneous T-cell lymphoma (1.74 per 100,000 PYs) and Kaposi sarcoma (1.57 per 100,000 PYs).
• The presentation of early-stage melanoma was low among Asian (53.5%), Black (62.4%), mixed (62.5%), and other (76.4%) ethnic groups compared to that among White ethnicities (79.8%).
• Acral lentiginous melanomas were less likely to get urgent suspected cancer pathway referrals than overall melanoma (40.1% vs 44.6%; P < .001) and more likely to be diagnosed late than overall melanoma (stage I/II at diagnosis; 72% vs 80%; P < .0001).

IN PRACTICE:

"The findings emphasise the need for better, targeted ethnicity data collection strategies to address incidence, outcomes and health care equity for not just skin cancer but all health conditions in underserved populations," the authors wrote. "While projects like the Global Burden of Disease have improved global health care reporting, continuous audit and improvement of collected data are essential to provide better care across people of all ethnicities."

SOURCE:

This study was led by Shehnaz Ahmed, British Association of Dermatologists, London, England. It was published online on September 10, 2025, in the British Journal of Dermatology.

LIMITATIONS:

Census data collection after every 10 years could have contributed to inaccurate population estimates and incidence rates. Small sample sizes in certain ethnic groups could have led to potential confounders, requiring a cautious interpretation of relative incidence. The NHS data included only self-reported ethnicity data with no available details of skin phototypes, skin tones, or racial ancestry. This study lacked granular ethnicity census data and stage data for basal cell carcinoma, cutaneous small cell carcinoma, and Kaposi sarcoma.

DISCLOSURES:

This research was supported through a partnership between the British Association of Dermatologists and NHS England's National Disease Registration Service. Two authors reported being employees of the British Association of Dermatologists.

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

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

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

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

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

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

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.

Background

Patients diagnosed with lung cancer are predominantly non-small cell lung cancer (NSCLC), a leading cause of cancer-related deaths. Thus, it is imperative to investigate and distinguish the differences present at diagnosis to possibly improve survival outcomes. NSCLC commonly metastasizes within older patients near the mean age of 71 years, but also in early onset patients which represents the patients younger than the earliest lung cancer screening age of 50.

Objective

To reveal differences in ratios of metastasis locations in squamous cell carcinoma (SCC), adenocarcinoma (ACC), and adenosquamous carcinoma (ASC).

Methods

The National Cancer Database (NCDB) was utilized to identify patients diagnosed with SCC, ACC, and ASC using the histology codes 8070, 8140, and 8560 from the ICD-O-3.2 from 2004 to 2022. Age groups were 70 years. Metastases located to the brain, liver, bone, and lung were included. Chi-Square tests were performed. The data was analyzed using R version 4.4.2 and statistical significance was set to α = 0.05.

Results

In this study, 1,445,119 patients were analyzed. Chi-Square tests identified significant differences in the ratios of organ metastasis locations between age groups in each subtype (p < 0.001). SCC in each age group similarly metastasized most to bone (36.3%, 34.7%, 34.5%), but notably more local lung metastasis was observed in the oldest group (33.6%). In ACC and ASC, the oldest group also had greater ratios of spread within the lungs (28.0%, 27.2%). Overall, the younger the age group, distant spread to the brain increased (ex. 29.0%, 24.4%, 17.5%). This suggests a widely heterogenous distribution of metastases at diagnosis of NSCLC subtypes and patient age.

Conclusions

This study demonstrated that patients with SCC, ACC, or ASC subtypes of NSCLC share similar predominant locations based in part on patient age, irrespective of cancer origin. NSCLC may more distantly metastasize in younger patients to the brain, while older patients may have locally metastatic cancer. Further analysis of key demographic variables as well as common undertaken treatment options may prove informative and reveal existing differences in survival outcomes.

Background

Patients diagnosed with lung cancer are predominantly non-small cell lung cancer (NSCLC), a leading cause of cancer-related deaths. Thus, it is imperative to investigate and distinguish the differences present at diagnosis to possibly improve survival outcomes. NSCLC commonly metastasizes within older patients near the mean age of 71 years, but also in early onset patients which represents the patients younger than the earliest lung cancer screening age of 50.

Objective

To reveal differences in ratios of metastasis locations in squamous cell carcinoma (SCC), adenocarcinoma (ACC), and adenosquamous carcinoma (ASC).

Methods

The National Cancer Database (NCDB) was utilized to identify patients diagnosed with SCC, ACC, and ASC using the histology codes 8070, 8140, and 8560 from the ICD-O-3.2 from 2004 to 2022. Age groups were 70 years. Metastases located to the brain, liver, bone, and lung were included. Chi-Square tests were performed. The data was analyzed using R version 4.4.2 and statistical significance was set to α = 0.05.

Results

In this study, 1,445,119 patients were analyzed. Chi-Square tests identified significant differences in the ratios of organ metastasis locations between age groups in each subtype (p < 0.001). SCC in each age group similarly metastasized most to bone (36.3%, 34.7%, 34.5%), but notably more local lung metastasis was observed in the oldest group (33.6%). In ACC and ASC, the oldest group also had greater ratios of spread within the lungs (28.0%, 27.2%). Overall, the younger the age group, distant spread to the brain increased (ex. 29.0%, 24.4%, 17.5%). This suggests a widely heterogenous distribution of metastases at diagnosis of NSCLC subtypes and patient age.

Conclusions

This study demonstrated that patients with SCC, ACC, or ASC subtypes of NSCLC share similar predominant locations based in part on patient age, irrespective of cancer origin. NSCLC may more distantly metastasize in younger patients to the brain, while older patients may have locally metastatic cancer. Further analysis of key demographic variables as well as common undertaken treatment options may prove informative and reveal existing differences in survival outcomes.

Background

Patients diagnosed with lung cancer are predominantly non-small cell lung cancer (NSCLC), a leading cause of cancer-related deaths. Thus, it is imperative to investigate and distinguish the differences present at diagnosis to possibly improve survival outcomes. NSCLC commonly metastasizes within older patients near the mean age of 71 years, but also in early onset patients which represents the patients younger than the earliest lung cancer screening age of 50.

Objective

To reveal differences in ratios of metastasis locations in squamous cell carcinoma (SCC), adenocarcinoma (ACC), and adenosquamous carcinoma (ASC).

Methods

The National Cancer Database (NCDB) was utilized to identify patients diagnosed with SCC, ACC, and ASC using the histology codes 8070, 8140, and 8560 from the ICD-O-3.2 from 2004 to 2022. Age groups were 70 years. Metastases located to the brain, liver, bone, and lung were included. Chi-Square tests were performed. The data was analyzed using R version 4.4.2 and statistical significance was set to α = 0.05.

Results

In this study, 1,445,119 patients were analyzed. Chi-Square tests identified significant differences in the ratios of organ metastasis locations between age groups in each subtype (p < 0.001). SCC in each age group similarly metastasized most to bone (36.3%, 34.7%, 34.5%), but notably more local lung metastasis was observed in the oldest group (33.6%). In ACC and ASC, the oldest group also had greater ratios of spread within the lungs (28.0%, 27.2%). Overall, the younger the age group, distant spread to the brain increased (ex. 29.0%, 24.4%, 17.5%). This suggests a widely heterogenous distribution of metastases at diagnosis of NSCLC subtypes and patient age.

Conclusions

This study demonstrated that patients with SCC, ACC, or ASC subtypes of NSCLC share similar predominant locations based in part on patient age, irrespective of cancer origin. NSCLC may more distantly metastasize in younger patients to the brain, while older patients may have locally metastatic cancer. Further analysis of key demographic variables as well as common undertaken treatment options may prove informative and reveal existing differences in survival outcomes.