Pub Date : 2025-12-26DOI: 10.1001/jamaoncol.2025.5385
Aaron P Mitchell,Rachel E Sachs,Stacie B Dusetzina
{"title":"Oncology Drug Revenue and Price Negotiation.","authors":"Aaron P Mitchell,Rachel E Sachs,Stacie B Dusetzina","doi":"10.1001/jamaoncol.2025.5385","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5385","url":null,"abstract":"","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"8 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1001/jamaoncol.2025.5672
Polina V Kukhareva,Haojia Li,Christian Balbin,Elizabeth R Stevens,Devin M Mann,Jorie M Butler,Tanner J Caverly,Guilherme Del Fiol,Kimberly A Kaphingst,Chelsey R Schlechter,Victoria L Tiase,Angela Fagerlin,Yue Zhang,Rachel Hess,Michael C Flynn,Chakravarthy Reddy,Douglas Martin,Phillip B Warner,Claude Nanjo,Joshua Choi,Quyen Ngo-Metzger,Kensaku Kawamoto
ImportanceLung cancer screening (LCS) with low-dose computed tomography (CT) remains underused in the US, partly because of incomplete smoking history documentation in electronic health records (EHRs) and limited time for shared decision-making in primary care.ObjectiveTo determine whether a patient-facing, EHR-integrated tool combined with clinician-facing clinical decision support improves the identification of LCS-eligible patients and the ordering of low-dose CT compared with clinician-facing tools alone.Design, Setting, and ParticipantsThis pragmatic, unstratified, randomized clinical trial with parallel groups was conducted from March 29, 2024, to March 28, 2025, at primary care clinics at University of Utah Health and New York University Langone Health. Adults aged 50 to 79 years with a documented smoking history, an active patient portal account, and a primary care visit in the preceding year were included. Study 1 enrolled patients with uncertain LCS eligibility (10 to 19 pack-years, unknown pack-years, or missing quit date); study 2 enrolled patients with documented eligibility (20 or more pack-years and currently smoking or quit smoking within 15 years).InterventionsThe control included the clinician-facing Decision Precision+ tool (preventive care reminders and a shared decision-making tool). The intervention included the Decision Precision+ tool as well as the MyLungHealth tool, which collected detailed smoking history (study 1) and delivered personalized education and risk/benefit information (studies 1 and 2) via the patient portal in English and Spanish.Main Outcomes and MeasuresThe primary outcomes were the proportion of patients newly identified as eligible for LCS (study 1) and low-dose CT ordering rates (study 2) over 12 months. Analyses used intention-to-treat mixed-effects logistic regression.ResultsThere were 31 303 randomized participants, including 26 729 in study 1 (13 144 [49.2%] female; 13 580 [50.8%] male; median [IQR] age, 62 [55-69] years) and 4574 in study 2 (2230 [48.8%] female; 2344 [51.2%] male; median [IQR] age, 63 [56-69] years). In study 1, the MyLungHealth tool increased new LCS eligibility identification (635 of 13 412 [4.7%] vs 308 of 13 317 [2.3%]; adjusted odds ratio, 2.19; 95% CI, 1.99-2.42; P < .001). In study 2, low-dose CT ordering was higher in the intervention arm (474 of 2312 [20.5%] vs 434 of 2262 [19.2%]; adjusted odds ratio, 1.16; 95% CI, 1.04-1.30; P = .008).Conclusions and RelevanceIn this randomized clinical trial, integrating a patient-centered tool into primary care EHR workflows increased the identification of patients eligible for LCS and the ordering of low-dose CTs. The relative increases in these primary outcomes were substantial, but absolute increases were more modest. Research on more intensive interventions is warranted to evaluate their ability to further improve LCS screening.Trial RegistrationClinicalTrials.gov Identifier: NCT06338592.
{"title":"Enhancement of Patient-Centered Lung Cancer Screening: The MyLungHealth Randomized Clinical Trial.","authors":"Polina V Kukhareva,Haojia Li,Christian Balbin,Elizabeth R Stevens,Devin M Mann,Jorie M Butler,Tanner J Caverly,Guilherme Del Fiol,Kimberly A Kaphingst,Chelsey R Schlechter,Victoria L Tiase,Angela Fagerlin,Yue Zhang,Rachel Hess,Michael C Flynn,Chakravarthy Reddy,Douglas Martin,Phillip B Warner,Claude Nanjo,Joshua Choi,Quyen Ngo-Metzger,Kensaku Kawamoto","doi":"10.1001/jamaoncol.2025.5672","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5672","url":null,"abstract":"ImportanceLung cancer screening (LCS) with low-dose computed tomography (CT) remains underused in the US, partly because of incomplete smoking history documentation in electronic health records (EHRs) and limited time for shared decision-making in primary care.ObjectiveTo determine whether a patient-facing, EHR-integrated tool combined with clinician-facing clinical decision support improves the identification of LCS-eligible patients and the ordering of low-dose CT compared with clinician-facing tools alone.Design, Setting, and ParticipantsThis pragmatic, unstratified, randomized clinical trial with parallel groups was conducted from March 29, 2024, to March 28, 2025, at primary care clinics at University of Utah Health and New York University Langone Health. Adults aged 50 to 79 years with a documented smoking history, an active patient portal account, and a primary care visit in the preceding year were included. Study 1 enrolled patients with uncertain LCS eligibility (10 to 19 pack-years, unknown pack-years, or missing quit date); study 2 enrolled patients with documented eligibility (20 or more pack-years and currently smoking or quit smoking within 15 years).InterventionsThe control included the clinician-facing Decision Precision+ tool (preventive care reminders and a shared decision-making tool). The intervention included the Decision Precision+ tool as well as the MyLungHealth tool, which collected detailed smoking history (study 1) and delivered personalized education and risk/benefit information (studies 1 and 2) via the patient portal in English and Spanish.Main Outcomes and MeasuresThe primary outcomes were the proportion of patients newly identified as eligible for LCS (study 1) and low-dose CT ordering rates (study 2) over 12 months. Analyses used intention-to-treat mixed-effects logistic regression.ResultsThere were 31 303 randomized participants, including 26 729 in study 1 (13 144 [49.2%] female; 13 580 [50.8%] male; median [IQR] age, 62 [55-69] years) and 4574 in study 2 (2230 [48.8%] female; 2344 [51.2%] male; median [IQR] age, 63 [56-69] years). In study 1, the MyLungHealth tool increased new LCS eligibility identification (635 of 13 412 [4.7%] vs 308 of 13 317 [2.3%]; adjusted odds ratio, 2.19; 95% CI, 1.99-2.42; P < .001). In study 2, low-dose CT ordering was higher in the intervention arm (474 of 2312 [20.5%] vs 434 of 2262 [19.2%]; adjusted odds ratio, 1.16; 95% CI, 1.04-1.30; P = .008).Conclusions and RelevanceIn this randomized clinical trial, integrating a patient-centered tool into primary care EHR workflows increased the identification of patients eligible for LCS and the ordering of low-dose CTs. The relative increases in these primary outcomes were substantial, but absolute increases were more modest. Research on more intensive interventions is warranted to evaluate their ability to further improve LCS screening.Trial RegistrationClinicalTrials.gov Identifier: NCT06338592.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"8 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1001/jamaoncol.2025.5561
Yongmei Huang,Yukio Suzuki,Jason D Wright
{"title":"Concerns in the Propensity Score-Matched Analysis-Reply.","authors":"Yongmei Huang,Yukio Suzuki,Jason D Wright","doi":"10.1001/jamaoncol.2025.5561","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5561","url":null,"abstract":"","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"25 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1001/jamaoncol.2025.5594
Zoe E Quandt,Shanda Finnigan,Vanessa Hill,Joe E Dib,Jason Burian,Sapir Tessler,Darah Davidson,Abdul Rafeh Naqash,Mark S Anderson,Megan Othus,Elad Sharon
ImportanceImmune-related adverse events (IRAEs) limit the use of cancer immunotherapy. Understanding the risk of severe IRAEs may help improve the use of cancer immunotherapy.ObjectiveTo review and assess hyperglycemic events across thousands of patients to characterize immune checkpoint inhibitor (ICI)-induced diabetes (ICI-D) using a large-scale trial conglomerate.Design, Setting, and ParticipantsAdverse event (AE) reports related to diabetes, hyperglycemia, and acidosis were retrieved from the National Cancer Institute (NCI) Cancer Therapy Evaluation Program (CTEP) database. Trial data from June 2015 to December 2022 were analyzed. Clinical information was manually retrieved. Overall counts of patients on each trial were retrieved from central NCI data. NCI CTEP trials are hosted in both academic and community medical centers. This analysis includes patients across 158 trials who were treated with varying regimens that included programmed cell death 1 protein (PD-1) or programmed cell death 1 ligand 1 (PD-L1) inhibitors through an NCI CTEP trial for their cancer from June 2015 to December 2022. Data clarifications were requested and then data were analyzed from January 2023 to June 1, 2025.Main Outcomes and MeasuresClinical characteristics differentiating ICI-D from other causes of hyperglycemia were enumerated. Cumulative incidence rates of ICI-D were calculated using trial-level data. Logistic regression was used to calculate the odds of developing ICI-D.ResultsIn 13 966 patients across 158 trials, the overall cumulative incidence of ICI-D was low (0.52 per 100 treated patients), but incidence varied by treatment type and was lower if patients were exposed to concurrent chemotherapy (0.65% without chemotherapy vs 0.26% with chemotherapy; odds ratio [OR], 0.38; 95% CI, 0.21-0.71; P = .002) and higher if patients were exposed to combined immunotherapy (0.94% with combination immunotherapy vs 0.37% with PD-1/PD-L1 inhibitor monotherapy; OR, 2.68; 95% CI, 1.69-4.24). Despite these low rates, the health care burden of ICI-D was high, with 90% requiring hospitalization at diagnosis and 43% requiring intensive care. The degree of hyperglycemia can be used to differentiate different etiologies of hyperglycemia, with higher glucose levels being more likely to be due to ICI-D.Conclusions and RelevanceResults of this study suggest that ICI-D is a rare but morbid condition that varies based on the combination of ICIs with other agents.
{"title":"Immune Checkpoint Inhibitor-Induced Diabetes Across National Cancer Institute Trials That Included PD-1 or PD-L1 Agents.","authors":"Zoe E Quandt,Shanda Finnigan,Vanessa Hill,Joe E Dib,Jason Burian,Sapir Tessler,Darah Davidson,Abdul Rafeh Naqash,Mark S Anderson,Megan Othus,Elad Sharon","doi":"10.1001/jamaoncol.2025.5594","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5594","url":null,"abstract":"ImportanceImmune-related adverse events (IRAEs) limit the use of cancer immunotherapy. Understanding the risk of severe IRAEs may help improve the use of cancer immunotherapy.ObjectiveTo review and assess hyperglycemic events across thousands of patients to characterize immune checkpoint inhibitor (ICI)-induced diabetes (ICI-D) using a large-scale trial conglomerate.Design, Setting, and ParticipantsAdverse event (AE) reports related to diabetes, hyperglycemia, and acidosis were retrieved from the National Cancer Institute (NCI) Cancer Therapy Evaluation Program (CTEP) database. Trial data from June 2015 to December 2022 were analyzed. Clinical information was manually retrieved. Overall counts of patients on each trial were retrieved from central NCI data. NCI CTEP trials are hosted in both academic and community medical centers. This analysis includes patients across 158 trials who were treated with varying regimens that included programmed cell death 1 protein (PD-1) or programmed cell death 1 ligand 1 (PD-L1) inhibitors through an NCI CTEP trial for their cancer from June 2015 to December 2022. Data clarifications were requested and then data were analyzed from January 2023 to June 1, 2025.Main Outcomes and MeasuresClinical characteristics differentiating ICI-D from other causes of hyperglycemia were enumerated. Cumulative incidence rates of ICI-D were calculated using trial-level data. Logistic regression was used to calculate the odds of developing ICI-D.ResultsIn 13 966 patients across 158 trials, the overall cumulative incidence of ICI-D was low (0.52 per 100 treated patients), but incidence varied by treatment type and was lower if patients were exposed to concurrent chemotherapy (0.65% without chemotherapy vs 0.26% with chemotherapy; odds ratio [OR], 0.38; 95% CI, 0.21-0.71; P = .002) and higher if patients were exposed to combined immunotherapy (0.94% with combination immunotherapy vs 0.37% with PD-1/PD-L1 inhibitor monotherapy; OR, 2.68; 95% CI, 1.69-4.24). Despite these low rates, the health care burden of ICI-D was high, with 90% requiring hospitalization at diagnosis and 43% requiring intensive care. The degree of hyperglycemia can be used to differentiate different etiologies of hyperglycemia, with higher glucose levels being more likely to be due to ICI-D.Conclusions and RelevanceResults of this study suggest that ICI-D is a rare but morbid condition that varies based on the combination of ICIs with other agents.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"22 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1001/jamaoncol.2025.5376
Hans Wildiers,Virginie Adam,Seamus O'Reilly,Josephine Van Cauwenberge,Amal Arahmani,Carlos L Arteaga,Philippe L Bedard,Judith Bliss,Panayota Boussis,Etienne Brain,Marc Buyse,Carmela Caballero,David Cameron,Fatima Cardoso,Eva Carrasco,Ana Casas,Boon Chua,Giuseppe Curigliano,Angela DeMichele,Laura Esserman,Giuseppe Floris,Matthew P Goetz,Theodora Goulioti,Benjamin Haibe-Kains,Christine Hodgdon,Michail Ignatiadis,Marleen Kok,Denis Lacombe,Barbro Linderholm,Sherene Loi,Christopher J Lord,Mairead MacKenzie,Julia Maues,Lydie Meheus,Judy Needham,Patrick Neven,Heather Parsons,Martine Piccart,Lajos Pusztai,Evangelia Razis,Shigehira Saji,Eva Schumacher-Wulf,Gabe S Sonke,Tania Spanic,Ian F Tannock,Andrew Tutt,Ander Urruticoechea,Laura van 't Veer,Ines Vaz-Luis,Gustavo Werutsky,Douglas Yee,Khalil Zaman,Christine Desmedt
ImportanceMolecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments.ObjectiveTo describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration.Evidence ReviewThis is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024.FindingsClinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug's approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity.Conclusions and RelevanceData and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens' related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.
{"title":"Enhancing Clinical Cancer Research Through Sharing of Data and Biospecimens.","authors":"Hans Wildiers,Virginie Adam,Seamus O'Reilly,Josephine Van Cauwenberge,Amal Arahmani,Carlos L Arteaga,Philippe L Bedard,Judith Bliss,Panayota Boussis,Etienne Brain,Marc Buyse,Carmela Caballero,David Cameron,Fatima Cardoso,Eva Carrasco,Ana Casas,Boon Chua,Giuseppe Curigliano,Angela DeMichele,Laura Esserman,Giuseppe Floris,Matthew P Goetz,Theodora Goulioti,Benjamin Haibe-Kains,Christine Hodgdon,Michail Ignatiadis,Marleen Kok,Denis Lacombe,Barbro Linderholm,Sherene Loi,Christopher J Lord,Mairead MacKenzie,Julia Maues,Lydie Meheus,Judy Needham,Patrick Neven,Heather Parsons,Martine Piccart,Lajos Pusztai,Evangelia Razis,Shigehira Saji,Eva Schumacher-Wulf,Gabe S Sonke,Tania Spanic,Ian F Tannock,Andrew Tutt,Ander Urruticoechea,Laura van 't Veer,Ines Vaz-Luis,Gustavo Werutsky,Douglas Yee,Khalil Zaman,Christine Desmedt","doi":"10.1001/jamaoncol.2025.5376","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5376","url":null,"abstract":"ImportanceMolecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments.ObjectiveTo describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration.Evidence ReviewThis is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024.FindingsClinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug's approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity.Conclusions and RelevanceData and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens' related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"16 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1001/jamaoncol.2025.5247
Annabelle D Robinson,Anthony M Joshua,Wendy Lipworth
{"title":"Managing Nonfinancial Conflicts of Interest in Oncology Research-A Guide for Practice.","authors":"Annabelle D Robinson,Anthony M Joshua,Wendy Lipworth","doi":"10.1001/jamaoncol.2025.5247","DOIUrl":"https://doi.org/10.1001/jamaoncol.2025.5247","url":null,"abstract":"","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"15 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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