JAMA Oncology最新文献

{"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}

{"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}

{"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}

{"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}

{"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}

{"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; &lt;jats:italic&gt;P&lt;/jats:italic&gt; &amp;amp;lt; .001) and overall survival (hazard ratio, 0.53; 95% CI, 0.39-0.73; &lt;jats:italic&gt;P&lt;/jats:italic&gt; &amp;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}

{"title":"Dissection of Progressive Disease Patterns for a Modified Classification for Immunotherapy","authors":"Jonas Saal, Markus Eckstein, Manuel Ritter, Peter Brossart, Julian Luetkens, Jörg Ellinger, Viktor Grünwald, Michael Hölzel, Niklas Klümper","doi":"10.1001/jamaoncol.2024.5672","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5672","url":null,"abstract":"ImportanceProgressive disease (PD) in patients treated with immune checkpoint inhibitors (ICIs) varies widely in outcomes according to the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1. Efforts to modify RECIST for ICI treatment have not resolved the heterogeneity in PD patterns, posing a clinical challenge.ObjectiveTo develop and validate a modified PD classification based on PD patterns and evaluate its association with postprogression survival (PPOS) in patients treated with the programmed cell death protein ligand 1 antibody atezolizumab across various solid tumors.Design, Setting, and ParticipantsThis study analyzed data from 5 phase 3 trials (IMmotion151, IMvigor211, OAK, Impower133, and IMspire150) involving patients treated with atezolizumab for renal cell carcinoma (RCC), urothelial carcinoma, small cell lung cancer, non–small cell lung cancer, and melanoma. This post hoc analysis was conducted from March to September 2024.ExposureTreatment with atezolizumab.Main Outcomes and MeasuresThe primary outcome was the association of PD patterns with PPOS. Seven PD patterns were identified based on the enlargement of target and nontarget lesions or new lesions and their combinations.ResultsA total of 1377 patients were analyzed across the 5 trials. In RCC, 7 PD patterns significantly affected prognosis. The 6-month PPOS probability ranged from 26% for progression in target and nontarget lesions plus new lesions to 90% for progression in either target or nontarget lesions alone. A modified PD classification was developed that categorized PD into 3 risk levels: low risk (progression of existing lesions), intermediate risk (new lesions without progression of existing lesions), and high risk (progression of existing lesions plus new lesions). This score was associated with PPOS in ICI-treated RCC, with hazard ratios of 0.23 (95% CI, 0.13-0.41; <jats:italic>P</jats:italic> &amp;amp;lt; .001) and 0.39 (95% CI, 0.23-0.66; <jats:italic>P</jats:italic> &amp;amp;lt; .001) for low-risk and intermediate-risk PD compared with high-risk PD, respectively. Validation in additional trials confirmed the score’s applicability across various tumors.Conclusions and RelevanceIn this study, a survival score was developed based on PD patterns. The risk classification was associated with PPOS across various solid tumors treated with immunotherapy and may therefore enhance prognostication and clinical decision-making, potentially providing a valuable tool for treating patients with PD who are receiving immunotherapy.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"14 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142887229","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}

{"title":"A Values Proposition for Cancer Care","authors":"William E. Rosa, Andrew S. Epstein, Judith E. Nelson","doi":"10.1001/jamaoncol.2024.5572","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5572","url":null,"abstract":"This Viewpoint discusses what a value proposition could look like in oncology and how it should reflect a clinician’s commitment to partner with patients to improve outcomes through individualized communication and shared decision-making centered on the patient’s values.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"76 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777391","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}

{"title":"Alteration of the Tumor Microenvironment With Intratumoral Dendritic Cells Before Chemotherapy in ERBB2 Breast Cancer","authors":"Hyo S. Han, Amy L. Aldrich, Saurabh K. Garg, R. Jared Weinfurtner, Jonathan V. Nguyen, Qianxing Mo, Junmin Whiting, Jennifer Childress, Hatem Soliman, Ricardo Costa, Avan Armaghani, Aixa Soyano, John Kiluk, Susan Hoover, Marie C. Lee, Nazanin Khakpour, Nithin Shenoi, Zena Jameel, Gary K. Koski, Brian J. Czerniecki","doi":"10.1001/jamaoncol.2024.5371","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5371","url":null,"abstract":"ImportanceCurrent chemotherapy regimens for patients with <jats:italic>ERBB2 </jats:italic>(formerly <jats:italic>HER</jats:italic>2)–positive breast cancer are associated with considerable morbidity. These patients may benefit from more effective and less toxic therapies.ObjectiveTo evaluate the safety, immunogenicity, and preliminary efficacy of intratumoral (IT) delivery of conventional type 1 dendritic cells (cDC1) in combination with <jats:italic>ERBB2</jats:italic>-targeted therapies.Design, Setting, and ParticipantsThis phase 1 (lead-in phase of a single-center phase 2 trial) nonrandomized clinical trial was conducted at Moffitt Cancer Center (Tampa, Florida). Patients were enrolled from October 2021 to October 2022. Data were analyzed in 2023 Patients with early-stage <jats:italic>ERBB2</jats:italic>-positive breast cancer with tumors 1 cm or larger were eligible.InterventionsTreatment included IT delivery of cDC1, 6 times weekly, followed by paclitaxel, 80 mg/m<jats:sup>2</jats:sup>, intravenously, 12 times weekly. Trastuzumab (8 mg/kg loading dose, then 6 mg/kg) and pertuzumab (840 mg loading dose, then 420 mg) were administered intravenously every 3 weeks for 6 cycles starting from day 1 of cDC1 injections. Two dose levels (DLs) of IT cDC1 (DL1 = 50 million and DL2 = 100 million cells) were evaluated, including 6 patients in each DL.Main Outcomes and MeasuresThe primary outcomes were the safety and immune response, and the secondary outcomes were the antitumor efficacy as measured by breast magnetic resonance imaging and residual cancer burden at surgery following neoadjuvant therapy.ResultsTwelve <jats:italic>ERBB2</jats:italic>-positive patients were enrolled and received treatment (DL1 = 6 and DL2 = 6). Nine patients had hormone receptor–positive disease and 3 had hormone receptor–negative disease, with clinical stage I (n = 5), II (n = 4), and III (n = 3). The most frequently observed adverse events with cDC1 were grade 1 to 2 chills (50%), fatigue (41.7%), headache (33%), and injection site reactions (33%). DL2 was associated with a diminished anti-<jats:italic>ERBB2</jats:italic> CD4 T-helper 1 blood response with a concomitant increase in innate and adaptive responses within the tumor. Preimmunotherapy and postimmunotherapy breast magnetic resonance imaging results showed 9 objective responses, 6 partial responses, 3 complete responses, and 3 stable diseases. Following surgery, 7 patients had a pathologic complete response.Conclusions and RelevanceIn this nonrandomized clinical trial, the addition of IT cDC1 and trastuzumab/pertuzumab before neoadjuvant chemotherapy was well tolerated with manageable adverse effects. Based on safety and immunogenicity, DL2 was selected for the phase 2 dose.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/NCT05325632\">NCT05325632</jats:ext-link>","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"9 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782390","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}

{"title":"Estimation of Cancer Deaths Averted From Prevention, Screening, and Treatment Efforts, 1975-2020","authors":"Katrina A. B. Goddard, Eric J. Feuer, Jeanne S. Mandelblatt, Rafael Meza, Theodore R. Holford, Jihyoun Jeon, Iris Lansdorp-Vogelaar, Roman Gulati, Natasha K. Stout, Nadia Howlader, Amy B. Knudsen, Daniel Miller, Jennifer L. Caswell-Jin, Clyde B. Schechter, Ruth Etzioni, Amy Trentham-Dietz, Allison W. Kurian, Sylvia K. Plevritis, John M. Hampton, Sarah Stein, Liyang P. Sun, Asad Umar, Philip E. Castle","doi":"10.1001/jamaoncol.2024.5381","DOIUrl":"https://doi.org/10.1001/jamaoncol.2024.5381","url":null,"abstract":"ImportanceCancer mortality has decreased over time, but the contributions of different interventions across the cancer control continuum to averting cancer deaths have not been systematically evaluated across major cancer sites.ObjectiveTo quantify the contributions of prevention, screening (to remove precursors [interception] or early detection), and treatment to cumulative number of cancer deaths averted from 1975 to 2020 for breast, cervical, colorectal, lung, and prostate cancers.Design, Setting, and ParticipantsIn this model-based study using population-level cancer mortality data, outputs from published models developed by the Cancer Intervention and Surveillance Modeling Network were extended to quantify cancer deaths averted through 2020. Model inputs were based on national data on risk factors, cancer incidence, cancer survival, and mortality due to other causes, and dissemination and effects of prevention, screening (for interception and early detection), and treatment. Simulated or modeled data using parameters derived from multiple birth cohorts of the US population were used.InterventionsPrimary prevention via smoking reduction (lung), screening for interception (cervix and colorectal) or early detection (breast, cervix, colorectal, and prostate), and therapy (breast, colorectal, lung, and prostate).Main Outcomes and MeasuresThe estimated cumulative number of cancer deaths averted with interventions vs no advances.ResultsAn estimated 5.94 million cancer deaths were averted for breast, cervical, colorectal, lung, and prostate cancers combined. Cancer prevention and screening efforts averted 8 of 10 of these deaths (4.75 million averted deaths). The contribution of each intervention varied by cancer site. Screening accounted for 25% of breast cancer deaths averted. Averted cervical cancer deaths were nearly completely averted through screening and removal of cancer precursors as treatment advances were modest during the study period. Averted colorectal cancer deaths were averted because of screening and removal of precancerous polyps or early detection in 79% and treatment advances in 21%. Most lung cancer deaths were avoided by smoking reduction (98%) because screening uptake was low and treatment largely palliative before 2014. Screening contributed to 56% of averted prostate cancer deaths.Conclusions and RelevanceOver the past 45 years, cancer prevention and screening accounted for most cancer deaths averted for these causes; however, their contribution varied by cancer site according to these models using population-level cancer mortality data. Despite progress, efforts to reduce the US cancer burden will require increased dissemination of effective interventions and new technologies and discoveries.","PeriodicalId":14850,"journal":{"name":"JAMA Oncology","volume":"16 1","pages":""},"PeriodicalIF":28.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782391","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}