Pub Date : 2025-01-16DOI: 10.1001/jamaoncol.2024.5937
Yazan Abboud, Anand Shah, Riya Sutariya, Vraj P. Shah, Ahmed Al-Khazraji, Paul J. Gaglio, Kaveh Hajifathalian
This observational study reports on a comprehensive nationwide evaluation of rising gastroenteropancreatic neuroendocrine tumor incidence in the US from 2001 to 2020.
本观察性研究报告了2001年至2020年美国胃肠胰腺神经内分泌肿瘤发病率上升的综合全国评估。
{"title":"Gastroenteropancreatic Neuroendocrine Tumor Incidence by Sex and Age in the US","authors":"Yazan Abboud, Anand Shah, Riya Sutariya, Vraj P. Shah, Ahmed Al-Khazraji, Paul J. Gaglio, Kaveh Hajifathalian","doi":"10.1001/jamaoncol.2024.5937","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5937","url":null,"abstract":"This observational study reports on a comprehensive nationwide evaluation of rising gastroenteropancreatic neuroendocrine tumor incidence in the US from 2001 to 2020.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"68 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986885","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 : 2025-01-16DOI: 10.1001/jamaoncol.2024.5927
Kirithiga Ramalingam, Rachel Woody, Alexa Glencer, Christopher J. Schwartz, Hidetoshi Mori, Jasmine Wong, Gillian Hirst, Jennifer Rosenbluth, Natsuko Onishi, Jessica Gibbs, Nola Hylton, Alexander D. Borowsky, Michael Campbell, Laura J. Esserman
ImportanceIntratumoral immunotherapy that leverages the biological characteristics of high-risk ductal carcinoma in situ (DCIS) may be able to reduce the extent of surgical treatment and provide an alternative approach to improve patient outcomes.ObjectiveTo determine if combination intratumoral immunotherapy can activate immune cells to shrink or eliminate high-risk DCIS.Design, Setting, and ParticipantsThis phase 1 open-label nonrandomized clinical trial at a single academic center tested the safety and efficacy of intratumoral immunotherapy in patients with high-risk DCIS, defined as at least 2 of the following present: younger than 45 years, tumor size greater than 5 cm, high-grade, palpable mass, hormone receptor (HR)–negative, or ERBB2-positive. Patients were enrolled between June 8, 2021, and December 13, 2022.InterventionPembrolizumab (anti–programmed cell death protein 1), dose ranging from 2 mg to 8 mg, and mRNA-2752 (a combination of interleukin [IL]-23, IL-36γ, and OX40L mRNAs), dose ranging from 1 mg to 4 mg, delivered intratumorally, with 2 to 4 doses given 2 to 3 weeks apart.Main Outcomes and MeasuresThe primary objective was to evaluate the safety and tolerability of intratumoral injections of pembrolizumab and mRNA-2752. The secondary objectives were to assess radiologic and pathological responses and immunological and histological differences in the posttreatment tumor microenvironment.ResultsTen female patients with high-risk DCIS (median [range] age, 46 [35-80] years) were enrolled. The median (range) tumor size was 5.3 (1.0-10.0) cm. Five tumors were HR-negative ERBB2-positive; 2 HR-negative ERBB2-negative; 2 HR-positive ERBB2-negative; and 1 HR-positive ERBB2-positive. Of all treated patients, 8 of 10 responded to treatment, and all 8 patients had ERBB2-positive or HR-negative DCIS. Three patients had complete responses. Three patients with negative posttreatment core biopsy results declined surgery and remained disease-free after 1 to 2 years. Multiplex immunofluorescence staining demonstrated that high baseline levels of tumor-infiltrating lymphocytes and programmed cell death ligand 1–positive cells (immune or tumor) were associated with a better treatment response. All patients experienced up to 1 week of fever, malaise, flulike symptoms, axillary adenopathy, erythema, injection site swelling, and swelling in the breast. One patient had intermittent urticaria for 3 months. The dose was serially reduced from 8 mg to 2 mg for pembrolizumab and 4 mg to 1 mg for mRNA-2752 to improve tolerability. The final recommended combination dose is pembrolizumab, 4 mg, with mRNA-2752, 1 mg.Conclusions and RelevanceIn this phase 1 nonrandomized clinical trial, the results suggest that intratumoral injections of pembrolizumab and mRNA-2752 are safe and may induce rapid regression of high-risk DCIS with high immune infiltrates. These findings warrant additional investigation, and studies are ongoing.Trial RegistrationClinicalTrials.gov Id
{"title":"Intratumoral Injection of mRNA-2752 and Pembrolizumab for High-Risk Ductal Carcinoma In Situ","authors":"Kirithiga Ramalingam, Rachel Woody, Alexa Glencer, Christopher J. Schwartz, Hidetoshi Mori, Jasmine Wong, Gillian Hirst, Jennifer Rosenbluth, Natsuko Onishi, Jessica Gibbs, Nola Hylton, Alexander D. Borowsky, Michael Campbell, Laura J. Esserman","doi":"10.1001/jamaoncol.2024.5927","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5927","url":null,"abstract":"ImportanceIntratumoral immunotherapy that leverages the biological characteristics of high-risk ductal carcinoma in situ (DCIS) may be able to reduce the extent of surgical treatment and provide an alternative approach to improve patient outcomes.ObjectiveTo determine if combination intratumoral immunotherapy can activate immune cells to shrink or eliminate high-risk DCIS.Design, Setting, and ParticipantsThis phase 1 open-label nonrandomized clinical trial at a single academic center tested the safety and efficacy of intratumoral immunotherapy in patients with high-risk DCIS, defined as at least 2 of the following present: younger than 45 years, tumor size greater than 5 cm, high-grade, palpable mass, hormone receptor (HR)–negative, or ERBB2-positive. Patients were enrolled between June 8, 2021, and December 13, 2022.InterventionPembrolizumab (anti–programmed cell death protein 1), dose ranging from 2 mg to 8 mg, and mRNA-2752 (a combination of interleukin [IL]-23, IL-36γ, and OX40L mRNAs), dose ranging from 1 mg to 4 mg, delivered intratumorally, with 2 to 4 doses given 2 to 3 weeks apart.Main Outcomes and MeasuresThe primary objective was to evaluate the safety and tolerability of intratumoral injections of pembrolizumab and mRNA-2752. The secondary objectives were to assess radiologic and pathological responses and immunological and histological differences in the posttreatment tumor microenvironment.ResultsTen female patients with high-risk DCIS (median [range] age, 46 [35-80] years) were enrolled. The median (range) tumor size was 5.3 (1.0-10.0) cm. Five tumors were HR-negative ERBB2-positive; 2 HR-negative ERBB2-negative; 2 HR-positive ERBB2-negative; and 1 HR-positive ERBB2-positive. Of all treated patients, 8 of 10 responded to treatment, and all 8 patients had ERBB2-positive or HR-negative DCIS. Three patients had complete responses. Three patients with negative posttreatment core biopsy results declined surgery and remained disease-free after 1 to 2 years. Multiplex immunofluorescence staining demonstrated that high baseline levels of tumor-infiltrating lymphocytes and programmed cell death ligand 1–positive cells (immune or tumor) were associated with a better treatment response. All patients experienced up to 1 week of fever, malaise, flulike symptoms, axillary adenopathy, erythema, injection site swelling, and swelling in the breast. One patient had intermittent urticaria for 3 months. The dose was serially reduced from 8 mg to 2 mg for pembrolizumab and 4 mg to 1 mg for mRNA-2752 to improve tolerability. The final recommended combination dose is pembrolizumab, 4 mg, with mRNA-2752, 1 mg.Conclusions and RelevanceIn this phase 1 nonrandomized clinical trial, the results suggest that intratumoral injections of pembrolizumab and mRNA-2752 are safe and may induce rapid regression of high-risk DCIS with high immune infiltrates. These findings warrant additional investigation, and studies are ongoing.Trial RegistrationClinicalTrials.gov Id","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"245 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986884","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}
ImportanceIntegration of molecular biomarker information into systemic therapy has become standard practice in breast cancer care. However, its implementation in guiding radiotherapy (RT) is slower. Although postoperative RT is recommended for most patients after breast-conserving surgery and, depending on risk factors, following mastectomy, emerging evidence has indicated that patients with low scores on gene expression signatures or selected clinical-pathological features may have very low local recurrence rates. This narrative review explored the potential of biomarker-directed personalized RT approaches, which may optimize treatment strategies and be associated with improved patient outcomes and experiences.ObservationsDistinctions between prognostic and predictive biomarkers were highlighted, emphasizing the importance of analytical and clinical validity in biomarker-based studies. Findings from studies investigating the prognostic and predictive value of various genomic signatures and immunohistochemical markers for guiding breast RT were presented. These included the Adjuvant Radiotherapy Intensification Classifier and the Profile for the Omission of Local Adjuvant Radiation, which have shown potential in predicting RT benefits. The genomic-adjusted radiation dose and role of tumor-infiltrating lymphocytes were also discussed. Ongoing clinical trials exploring the use of biomarkers in ductal carcinoma in situ and invasive breast cancer to refine RT decision-making were illustrated.Conclusions and RelevanceThe results of this narrative review suggest that evidence-based shared decision-making is crucial to optimize treatment according to the individual's predicted benefits and risks along with their personal preferences. Incorporation of biomarker-directed approaches in RT for breast cancer may hold promise for personalized treatment, potentially facilitating omission of RT for patients at low risk of recurrence, while identifying those who may benefit from intensified therapy. This personalized RT approach may be associated with improved clinical outcomes and quality of life and facilitate decision-making for people with breast cancer. However, there remains a need for robust clinical and analytical validation of biomarkers to ensure reliability and clinical utility for RT optimization.
重要性将分子生物标记信息纳入全身治疗已成为乳腺癌治疗的标准做法。然而，其在指导放射治疗（RT）中的应用却较为缓慢。虽然大多数患者在接受保乳手术后都建议进行术后放疗，而且根据风险因素，乳房切除术后也建议进行术后放疗，但新出现的证据表明，基因表达特征或选定临床病理特征得分较低的患者的局部复发率可能很低。本综述探讨了以生物标志物为导向的个性化 RT 方法的潜力，这种方法可能会优化治疗策略并改善患者的预后和体验。会上介绍了对指导乳腺 RT 的各种基因组特征和免疫组化标记物的预后和预测价值的研究结果。其中包括 "辅助放疗强化分类器"（Adjuvant Radiotherapy Intensification Classifier）和 "局部辅助放疗遗漏概况"（Profile for the Omission of Local Adjuvant Radiation），它们在预测乳腺放射治疗的获益方面已显示出潜力。会上还讨论了基因组调整放射剂量和肿瘤浸润淋巴细胞的作用。本综述的结果表明，以证据为基础的共同决策对于根据个人预测的获益和风险以及个人偏好优化治疗至关重要。在乳腺癌的 RT 治疗中纳入生物标志物导向方法可能会为个性化治疗带来希望，有可能帮助低复发风险患者省去 RT 治疗，同时识别那些可能从强化治疗中获益的患者。这种个性化 RT 方法可能会改善临床疗效和生活质量，并有助于乳腺癌患者做出决策。然而，生物标记物仍需经过严格的临床和分析验证，以确保其在 RT 优化方面的可靠性和临床实用性。
{"title":"Biomarker-Directed Radiotherapy in Breast Cancer: A Narrative Review.","authors":"Icro Meattini,Charlotte E Coles,Trine Tramm,Simona Borghesi,David Krug,Angel Montero,Valerio Nardone,Viola Salvestrini,Marianna Valzano,Vincenzo Valentini,Cynthia Aristei,Philip Poortmans,","doi":"10.1001/jamaoncol.2024.5780","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5780","url":null,"abstract":"ImportanceIntegration of molecular biomarker information into systemic therapy has become standard practice in breast cancer care. However, its implementation in guiding radiotherapy (RT) is slower. Although postoperative RT is recommended for most patients after breast-conserving surgery and, depending on risk factors, following mastectomy, emerging evidence has indicated that patients with low scores on gene expression signatures or selected clinical-pathological features may have very low local recurrence rates. This narrative review explored the potential of biomarker-directed personalized RT approaches, which may optimize treatment strategies and be associated with improved patient outcomes and experiences.ObservationsDistinctions between prognostic and predictive biomarkers were highlighted, emphasizing the importance of analytical and clinical validity in biomarker-based studies. Findings from studies investigating the prognostic and predictive value of various genomic signatures and immunohistochemical markers for guiding breast RT were presented. These included the Adjuvant Radiotherapy Intensification Classifier and the Profile for the Omission of Local Adjuvant Radiation, which have shown potential in predicting RT benefits. The genomic-adjusted radiation dose and role of tumor-infiltrating lymphocytes were also discussed. Ongoing clinical trials exploring the use of biomarkers in ductal carcinoma in situ and invasive breast cancer to refine RT decision-making were illustrated.Conclusions and RelevanceThe results of this narrative review suggest that evidence-based shared decision-making is crucial to optimize treatment according to the individual's predicted benefits and risks along with their personal preferences. Incorporation of biomarker-directed approaches in RT for breast cancer may hold promise for personalized treatment, potentially facilitating omission of RT for patients at low risk of recurrence, while identifying those who may benefit from intensified therapy. This personalized RT approach may be associated with improved clinical outcomes and quality of life and facilitate decision-making for people with breast cancer. However, there remains a need for robust clinical and analytical validation of biomarkers to ensure reliability and clinical utility for RT optimization.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"45 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988591","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 : 2025-01-16DOI: 10.1001/jamaoncol.2024.6157
James A Colbert,Louis Potters
{"title":"Overcoming Barriers to Make Patient-Reported Outcome Collection the Standard of Care in Oncology.","authors":"James A Colbert,Louis Potters","doi":"10.1001/jamaoncol.2024.6157","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.6157","url":null,"abstract":"","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"66 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988523","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 : 2025-01-09DOI: 10.1001/jamaoncol.2024.5794
Kanika Arora, Sarah P. Suehnholz, Hongxin Zhang, Irina Ostrovnaya, Ritika Kundra, Subhiksha Nandakumar, Moriah H. Nissan, A. Rose Brannon, Chaitanya Bandlamudi, Marc Ladanyi, Alexander Drilon, Carol L. Brown, David B. Solit, Nikolaus Schultz, Michael F. Berger, Debyani Chakravarty
ImportanceAlthough differences in the prevalence of key cancer-specific somatic mutations as a function of genetic ancestry among patients with cancer has been well-established, few studies have addressed the practical clinical implications of these differences for the growing number of biomarker-driven treatments.ObjectiveTo determine if the approval of precision oncology therapies has benefited patients with cancer from various ancestral backgrounds equally over time.Design, Setting, and ParticipantsA retrospective analysis of samples from patients with solid cancers who underwent clinical sequencing using the integrated mutation profiling of actionable cancer targets (MSK-IMPACT) assay between January 2014 and December 2022 was carried out. The annual fraction of patients per ancestral group with at least 1 level 1 biomarker was calculated for FDA drug approvals from January 1998 to December 2023. Analysis began in January 2024.Main Outcomes and MeasuresFor each patient, genetic ancestry was quantitatively inferred, and patients were grouped based on predominant reference ancestry. OncoKB was used to identify all Food and Drug Administration (FDA)–recognized somatic biomarkers associated with FDA-approved therapies (level 1 biomarkers) in each tumor sample.ResultsOverall, the study included 59 433 patients. The approval of the EGFR-tyrosine kinase inhibitor erlotinib for patients with EGFR-mutant lung cancers in 2013 disproportionately benefited patients of East Asian and South Asian ancestries, leading to higher patient fractions with level 1 biomarkers in these ancestral groups compared with other populations. Although the increase in precision oncology drug approvals from 2019 to 2020 had a notable positive impact on clinical actionability for patients of European ancestry, patients of African ancestry had the lowest fraction of level 1 biomarkers compared with other groups from 2019 onward.Conclusion and RelevanceThis study systematically assessed and compared temporal changes in genomic biomarker-based eligibility for precision oncology therapies as a function of inferred genetic ancestry derived from DNA sequencing data. Despite the accelerated rate of FDA approvals for precision oncology therapies over the past decade, measurable differences in biomarker-based drug eligibility among patient ancestral groups exist. These differences may exacerbate the systemic disparities in clinical outcomes in patients of African ancestry due to existing deficiencies in their access to cancer care.
{"title":"Genetic Ancestry–Based Differences in Biomarker-Based Eligibility for Precision Oncology Therapies","authors":"Kanika Arora, Sarah P. Suehnholz, Hongxin Zhang, Irina Ostrovnaya, Ritika Kundra, Subhiksha Nandakumar, Moriah H. Nissan, A. Rose Brannon, Chaitanya Bandlamudi, Marc Ladanyi, Alexander Drilon, Carol L. Brown, David B. Solit, Nikolaus Schultz, Michael F. Berger, Debyani Chakravarty","doi":"10.1001/jamaoncol.2024.5794","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5794","url":null,"abstract":"ImportanceAlthough differences in the prevalence of key cancer-specific somatic mutations as a function of genetic ancestry among patients with cancer has been well-established, few studies have addressed the practical clinical implications of these differences for the growing number of biomarker-driven treatments.ObjectiveTo determine if the approval of precision oncology therapies has benefited patients with cancer from various ancestral backgrounds equally over time.Design, Setting, and ParticipantsA retrospective analysis of samples from patients with solid cancers who underwent clinical sequencing using the integrated mutation profiling of actionable cancer targets (MSK-IMPACT) assay between January 2014 and December 2022 was carried out. The annual fraction of patients per ancestral group with at least 1 level 1 biomarker was calculated for FDA drug approvals from January 1998 to December 2023. Analysis began in January 2024.Main Outcomes and MeasuresFor each patient, genetic ancestry was quantitatively inferred, and patients were grouped based on predominant reference ancestry. OncoKB was used to identify all Food and Drug Administration (FDA)–recognized somatic biomarkers associated with FDA-approved therapies (level 1 biomarkers) in each tumor sample.ResultsOverall, the study included 59 433 patients. The approval of the <jats:italic>EGFR</jats:italic>-tyrosine kinase inhibitor erlotinib for patients with <jats:italic>EGFR</jats:italic>-mutant lung cancers in 2013 disproportionately benefited patients of East Asian and South Asian ancestries, leading to higher patient fractions with level 1 biomarkers in these ancestral groups compared with other populations. Although the increase in precision oncology drug approvals from 2019 to 2020 had a notable positive impact on clinical actionability for patients of European ancestry, patients of African ancestry had the lowest fraction of level 1 biomarkers compared with other groups from 2019 onward.Conclusion and RelevanceThis study systematically assessed and compared temporal changes in genomic biomarker-based eligibility for precision oncology therapies as a function of inferred genetic ancestry derived from DNA sequencing data. Despite the accelerated rate of FDA approvals for precision oncology therapies over the past decade, measurable differences in biomarker-based drug eligibility among patient ancestral groups exist. These differences may exacerbate the systemic disparities in clinical outcomes in patients of African ancestry due to existing deficiencies in their access to cancer care.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"2 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939823","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 : 2025-01-09DOI: 10.1001/jamaoncol.2024.6151
Lawrence B. Marks, Caprice C. Greenberg, Lukasz M. Mazur
This Viewpoint discusses strategies used with driving that can be applied to health care to promote consistent and predictable physician and patient actions.
本观点讨论了可应用于卫生保健的与驾驶一起使用的策略，以促进一致和可预测的医生和患者行动。
{"title":"What We Can Learn About Patient Safety While Driving to Work","authors":"Lawrence B. Marks, Caprice C. Greenberg, Lukasz M. Mazur","doi":"10.1001/jamaoncol.2024.6151","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.6151","url":null,"abstract":"This Viewpoint discusses strategies used with driving that can be applied to health care to promote consistent and predictable physician and patient actions.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"20 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939874","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 : 2025-01-09DOI: 10.1001/jamaoncol.2024.5786
Gregory A. Abel, Haesook T. Kim, Ira Zackon, Edwin T. Alyea, Alexandra S. Bailey, John P. Winters, Kenneth R. Meehan, John L. Reagan, Jeanna H. Walsh, Thomas P. Walsh, Alexandra Ivanov, Meredith A. Faggen, Sarah Sinclair, Amy C. Joyce, Sara D. Close, Amy Emmert, Jon Koreth, Joseph H. Antin, Corey S. Cutler, Vincent T. Ho, Robert J. Soiffer
ImportanceAlthough sharing care with local oncologists after allogeneic hematopoietic cell transplantation (HCT) has been proposed for patients living far from HCT centers, it is not known whether a shared strategy is safe or improves patient quality of life (QOL).ObjectiveTo determine the efficacy and safety of sharing follow-up care after HCT between the HCT specialty center and local oncologists.Design, Setting, and ParticipantsThis was a multicenter collaborative randomized clinical trial of patients undergoing HCT at Dana-Farber Cancer Institute (DFCI)—a high volume HCT center in Boston (Massachusetts)—and 8 local oncology practices. Eligible patients were enrolled from December 2017 to December 2021 and were randomized 1:1 to shared vs usual care after neutrophil engraftment, stratified by local sites in Massachusetts, Rhode Island, New Hampshire, New York, and Maine. Data analyses were performed in January 2024.InterventionShared care involved alternating post-HCT visits at DFCI and local oncology practices through day 100; for usual care, all post-HCT visits occurred only at DFCI.Main Outcomes and MeasuresCoprimary outcomes were nonrelapse mortality (NRM) at day 100, and QOL measured by the FACT-BMT (Functional Assessment of Cancer Therapy–Bone Marrow Transplantation) instrument and the QLQ-C30 (European Organization for Research and Treatment of Cancer’s Quality of Life Questionnaire) at day 180. Prespecified secondary outcomes included day 100 QOL and 1-year overall survival.ResultsA total of 302 participants (median [range] age, 63 [20-79] years; 117 [38.7%] females; 185 [61.3%] males) were included in the analysis; 152 were randomized to shared care and 150 to usual care. Day 100 NRM was noninferior for shared vs usual care (2.6% [95% CI, 0.7% to 6.6%] vs 2.7% [95% CI, 0.7% to 6.7%]; P = .98). There were no differences at day 180 for the FACT-BMT total score (mean difference, 3.8; 95% CI, −2.1 to 9.6; P = .20) or QLQ-C30 global score (1.9; 95% CI, −4.9 to 8.8; P = .58). At day 100, the FACT-BMT total score was better for shared care (mean difference, 6.6; 95% CI, 1.0 to 12.1; P = .02) as was the QLQ-C30 global score (8.8; 95% CI, 1.8 to 15.7; P = .02).Conclusions and RelevanceThis randomized clinical trial found that shared care resulted in noninferior NRM at day 100 but similar QOL at day 180, with improved QOL at day 100. These data suggest that shared care is safe, improves QOL early on, and has the potential to become a routine model for post-HCT care.Trial RegistrationClinicalTrials.gov Identifier: NCT03244826
{"title":"Shared Local Oncology Care After Allogeneic Hematopoietic Cell Transplantation","authors":"Gregory A. Abel, Haesook T. Kim, Ira Zackon, Edwin T. Alyea, Alexandra S. Bailey, John P. Winters, Kenneth R. Meehan, John L. Reagan, Jeanna H. Walsh, Thomas P. Walsh, Alexandra Ivanov, Meredith A. Faggen, Sarah Sinclair, Amy C. Joyce, Sara D. Close, Amy Emmert, Jon Koreth, Joseph H. Antin, Corey S. Cutler, Vincent T. Ho, Robert J. Soiffer","doi":"10.1001/jamaoncol.2024.5786","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5786","url":null,"abstract":"ImportanceAlthough sharing care with local oncologists after allogeneic hematopoietic cell transplantation (HCT) has been proposed for patients living far from HCT centers, it is not known whether a shared strategy is safe or improves patient quality of life (QOL).ObjectiveTo determine the efficacy and safety of sharing follow-up care after HCT between the HCT specialty center and local oncologists.Design, Setting, and ParticipantsThis was a multicenter collaborative randomized clinical trial of patients undergoing HCT at Dana-Farber Cancer Institute (DFCI)—a high volume HCT center in Boston (Massachusetts)—and 8 local oncology practices. Eligible patients were enrolled from December 2017 to December 2021 and were randomized 1:1 to shared vs usual care after neutrophil engraftment, stratified by local sites in Massachusetts, Rhode Island, New Hampshire, New York, and Maine. Data analyses were performed in January 2024.InterventionShared care involved alternating post-HCT visits at DFCI and local oncology practices through day 100; for usual care, all post-HCT visits occurred only at DFCI.Main Outcomes and MeasuresCoprimary outcomes were nonrelapse mortality (NRM) at day 100, and QOL measured by the FACT-BMT (Functional Assessment of Cancer Therapy–Bone Marrow Transplantation) instrument and the QLQ-C30 (European Organization for Research and Treatment of Cancer’s Quality of Life Questionnaire) at day 180. Prespecified secondary outcomes included day 100 QOL and 1-year overall survival.ResultsA total of 302 participants (median [range] age, 63 [20-79] years; 117 [38.7%] females; 185 [61.3%] males) were included in the analysis; 152 were randomized to shared care and 150 to usual care. Day 100 NRM was noninferior for shared vs usual care (2.6% [95% CI, 0.7% to 6.6%] vs 2.7% [95% CI, 0.7% to 6.7%]; <jats:italic>P</jats:italic> = .98). There were no differences at day 180 for the FACT-BMT total score (mean difference, 3.8; 95% CI, −2.1 to 9.6; <jats:italic>P</jats:italic> = .20) or QLQ-C30 global score (1.9; 95% CI, −4.9 to 8.8; <jats:italic>P</jats:italic> = .58). At day 100, the FACT-BMT total score was better for shared care (mean difference, 6.6; 95% CI, 1.0 to 12.1; <jats:italic>P</jats:italic> = .02) as was the QLQ-C30 global score (8.8; 95% CI, 1.8 to 15.7; <jats:italic>P</jats:italic> = .02).Conclusions and RelevanceThis randomized clinical trial found that shared care resulted in noninferior NRM at day 100 but similar QOL at day 180, with improved QOL at day 100. These data suggest that shared care is safe, improves QOL early on, and has the potential to become a routine model for post-HCT care.Trial RegistrationClinicalTrials.gov Identifier: <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" ext-link-type=\"uri\" xlink:href=\"https://clinicaltrials.gov/study/NCT03244826\">NCT03244826</jats:ext-link>","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"22 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939875","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 : 2024-12-26DOI: 10.1001/jamaoncol.2024.5816
Manuel David Gil-Sierra,María Del Pilar Briceño-Casado,Cristina Moreno-Ramos
{"title":"Immunotherapy Benefit Over Best Supportive Care in Hepatocellular Cancer With Child-Pugh B Dysfunction.","authors":"Manuel David Gil-Sierra,María Del Pilar Briceño-Casado,Cristina Moreno-Ramos","doi":"10.1001/jamaoncol.2024.5816","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5816","url":null,"abstract":"","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"306 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142887556","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 : 2024-12-26DOI: 10.1001/jamaoncol.2024.5506
Craig Horbinski, David A. Solomon, Rimas V. Lukas, Roger J. Packer, Priscilla Brastianos, Patrick Y. Wen, Matija Snuderl, Mitchel S. Berger, Susan Chang, Maryam Fouladi, Joanna J. Phillips, Burt Nabors, Daniel J. Brat, Jason T. Huse, Kenneth Aldape, Jann N. Sarkaria, Matthias Holdhoff, Terry C. Burns, Katherine B. Peters, Ingo K. Mellinghoff, David Arons, Evanthia Galanis
ImportanceMolecular techniques, including next-generation sequencing, genomic copy number profiling, fusion transcript detection, and genomic DNA methylation arrays, are now indispensable tools for the workup of central nervous system (CNS) tumors. Yet there remains a great deal of heterogeneity in using such biomarker testing across institutions and hospital systems. This is in large part because there is a persistent reluctance among third-party payers to cover molecular testing. The objective of this Review is to describe why comprehensive molecular biomarker testing is now required for the accurate diagnosis and grading and prognostication of CNS tumors and, in so doing, to justify more widespread use by clinicians and coverage by third-party payers.ObservationsThe 5th edition of the World Health Organization (WHO) classification system for CNS tumors incorporates specific molecular signatures into the essential diagnostic criteria for most tumor entities. Many CNS tumor types cannot be reliably diagnosed according to current WHO guidelines without molecular testing. The National Comprehensive Cancer Network also incorporates molecular testing into their guidelines for CNS tumors. Both sets of guidelines are maximally effective if they are implemented routinely for all patients with CNS tumors. Moreover, the cost of these tests is less than 5% of the overall average cost of caring for patients with CNS tumors and consistently improves management. This includes more accurate diagnosis and prognostication, clinical trial eligibility, and prediction of response to specific treatments. Each major group of CNS tumors in the WHO classification is evaluated and how molecular diagnostics enhances patient care is described.Conclusions and RelevanceRoutine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.
{"title":"Molecular Testing for the World Health Organization Classification of Central Nervous System Tumors","authors":"Craig Horbinski, David A. Solomon, Rimas V. Lukas, Roger J. Packer, Priscilla Brastianos, Patrick Y. Wen, Matija Snuderl, Mitchel S. Berger, Susan Chang, Maryam Fouladi, Joanna J. Phillips, Burt Nabors, Daniel J. Brat, Jason T. Huse, Kenneth Aldape, Jann N. Sarkaria, Matthias Holdhoff, Terry C. Burns, Katherine B. Peters, Ingo K. Mellinghoff, David Arons, Evanthia Galanis","doi":"10.1001/jamaoncol.2024.5506","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5506","url":null,"abstract":"ImportanceMolecular techniques, including next-generation sequencing, genomic copy number profiling, fusion transcript detection, and genomic DNA methylation arrays, are now indispensable tools for the workup of central nervous system (CNS) tumors. Yet there remains a great deal of heterogeneity in using such biomarker testing across institutions and hospital systems. This is in large part because there is a persistent reluctance among third-party payers to cover molecular testing. The objective of this Review is to describe why comprehensive molecular biomarker testing is now required for the accurate diagnosis and grading and prognostication of CNS tumors and, in so doing, to justify more widespread use by clinicians and coverage by third-party payers.ObservationsThe 5th edition of the World Health Organization (WHO) classification system for CNS tumors incorporates specific molecular signatures into the essential diagnostic criteria for most tumor entities. Many CNS tumor types cannot be reliably diagnosed according to current WHO guidelines without molecular testing. The National Comprehensive Cancer Network also incorporates molecular testing into their guidelines for CNS tumors. Both sets of guidelines are maximally effective if they are implemented routinely for all patients with CNS tumors. Moreover, the cost of these tests is less than 5% of the overall average cost of caring for patients with CNS tumors and consistently improves management. This includes more accurate diagnosis and prognostication, clinical trial eligibility, and prediction of response to specific treatments. Each major group of CNS tumors in the WHO classification is evaluated and how molecular diagnostics enhances patient care is described.Conclusions and RelevanceRoutine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"32 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142887225","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 : 2024-12-26DOI: 10.1001/jamaoncol.2024.5356
Mehrdad Rakaee, Masoud Tafavvoghi, Biagio Ricciuti, Joao V. Alessi, Alessio Cortellini, Fabrizio Citarella, Lorenzo Nibid, Giuseppe Perrone, Elio Adib, Claudia A. M. Fulgenzi, Cassio Murilo Hidalgo Filho, Alessandro Di Federico, Falah Jabar, Sayed Hashemi, Ilias Houda, Elin Richardsen, Lill-Tove Rasmussen Busund, Tom Donnem, Idris Bahce, David J. Pinato, Åslaug Helland, Lynette M. Sholl, Mark M. Awad, David J. Kwiatkowski
ImportanceOnly a small fraction of patients with advanced non−small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to benefit from immunotherapy.ObjectiveTo develop a supervised deep learning−based ICI response prediction method; evaluate its performance alongside other known predictive biomarkers; and assess its association with clinical outcomes in patients with advanced NSCLC.Design, Setting, and ParticipantsThis multicenter cohort study developed and independently validated a deep learning−based response stratification model for predicting ICI treatment outcome in patients with advanced NSCLC from whole slide hematoxylin and eosin–stained images. Images for model development and validation were obtained from 1 participating center in the US and 3 in the European Union (EU) from August 2014 to December 2022. Data analyses were performed from September 2022 to May 2024.ExposureMonotherapy with ICIs.Main Outcomes and MeasuresModel performance measured by clinical end points and objective response rate (ORR) differentiation power vs other predictive biomarkers, ie, programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs).ResultsA total of 295 581 image tiles from 958 patients (mean [SD] age, 66.0 [10.6] years; 456 [48%] females and 502 [52%] males) treated with ICI for NSCLC were included in the analysis. The US-based development cohort consisted of 614 patients with median (IQR) follow-up time of 54.5 (38.2-68.1) months, and the EU-based validation cohort, 344 patients with 43.3 (27.4-53.9) months of follow-up. The ORR to ICI was 26% in the developmental cohort and 28% in the validation cohort. The deep learning model’s area under the receiver operating characteristic curve (AUC) for ORR was 0.75 (95% CI, 0.64-0.85) in the internal test set and 0.66 (95% CI, 0.60-0.72) in the validation cohort. In a multivariable analysis, the deep learning model’s score was an independent predictor of ICI response in the validation cohort for both progression-free (hazard ratio, 0.56; 95% CI, 0.42-0.76; <jats:italic>P</jats:italic> &lt; .001) and overall survival (hazard ratio, 0.53; 95% CI, 0.39-0.73; <jats:italic>P</jats:italic> &lt; .001). The tuned deep learning model achieved a higher AUC than TMB, TILs, and PD-L1 in the internal set; in the validation cohort, it was superior to TILs and comparable with PD-L1 (AUC, 0.67; 95% CI, 0.60-0.74), with a 10-percentage point improvement in specificity. In the validation cohort, combining the deep learning model with PD-L1 scores achieved an AUC of 0.70 (95% CI, 0.63-0.76), outperforming either marker alone, with a response rate of 51% compared to 41% for PD-L1 (≥50%) alone.Conclusions and RelevanceThe findings of this cohort study demonstrate a strong and independent deep learning−based feature associated with ICI respons
{"title":"Deep Learning Model for Predicting Immunotherapy Response in Advanced Non−Small Cell Lung Cancer","authors":"Mehrdad Rakaee, Masoud Tafavvoghi, Biagio Ricciuti, Joao V. Alessi, Alessio Cortellini, Fabrizio Citarella, Lorenzo Nibid, Giuseppe Perrone, Elio Adib, Claudia A. M. Fulgenzi, Cassio Murilo Hidalgo Filho, Alessandro Di Federico, Falah Jabar, Sayed Hashemi, Ilias Houda, Elin Richardsen, Lill-Tove Rasmussen Busund, Tom Donnem, Idris Bahce, David J. Pinato, Åslaug Helland, Lynette M. Sholl, Mark M. Awad, David J. Kwiatkowski","doi":"10.1001/jamaoncol.2024.5356","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5356","url":null,"abstract":"ImportanceOnly a small fraction of patients with advanced non−small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to benefit from immunotherapy.ObjectiveTo develop a supervised deep learning−based ICI response prediction method; evaluate its performance alongside other known predictive biomarkers; and assess its association with clinical outcomes in patients with advanced NSCLC.Design, Setting, and ParticipantsThis multicenter cohort study developed and independently validated a deep learning−based response stratification model for predicting ICI treatment outcome in patients with advanced NSCLC from whole slide hematoxylin and eosin–stained images. Images for model development and validation were obtained from 1 participating center in the US and 3 in the European Union (EU) from August 2014 to December 2022. Data analyses were performed from September 2022 to May 2024.ExposureMonotherapy with ICIs.Main Outcomes and MeasuresModel performance measured by clinical end points and objective response rate (ORR) differentiation power vs other predictive biomarkers, ie, programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs).ResultsA total of 295 581 image tiles from 958 patients (mean [SD] age, 66.0 [10.6] years; 456 [48%] females and 502 [52%] males) treated with ICI for NSCLC were included in the analysis. The US-based development cohort consisted of 614 patients with median (IQR) follow-up time of 54.5 (38.2-68.1) months, and the EU-based validation cohort, 344 patients with 43.3 (27.4-53.9) months of follow-up. The ORR to ICI was 26% in the developmental cohort and 28% in the validation cohort. The deep learning model’s area under the receiver operating characteristic curve (AUC) for ORR was 0.75 (95% CI, 0.64-0.85) in the internal test set and 0.66 (95% CI, 0.60-0.72) in the validation cohort. In a multivariable analysis, the deep learning model’s score was an independent predictor of ICI response in the validation cohort for both progression-free (hazard ratio, 0.56; 95% CI, 0.42-0.76; <jats:italic>P</jats:italic> &amp;lt; .001) and overall survival (hazard ratio, 0.53; 95% CI, 0.39-0.73; <jats:italic>P</jats:italic> &amp;lt; .001). The tuned deep learning model achieved a higher AUC than TMB, TILs, and PD-L1 in the internal set; in the validation cohort, it was superior to TILs and comparable with PD-L1 (AUC, 0.67; 95% CI, 0.60-0.74), with a 10-percentage point improvement in specificity. In the validation cohort, combining the deep learning model with PD-L1 scores achieved an AUC of 0.70 (95% CI, 0.63-0.76), outperforming either marker alone, with a response rate of 51% compared to 41% for PD-L1 (≥50%) alone.Conclusions and RelevanceThe findings of this cohort study demonstrate a strong and independent deep learning−based feature associated with ICI respons","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"304 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142887224","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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