JNCI Journal of the National Cancer Institute最新文献

{"title":"Continued prioritization of biomedical research over sociomedical research may widen disparities in cancer outcomes.","authors":"Rebecca D Kehm","doi":"10.1093/jnci/djae150","DOIUrl":"10.1093/jnci/djae150","url":null,"abstract":"","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":"1547-1548"},"PeriodicalIF":9.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141723687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in breast cancer specific death by clinical stage at diagnoses between 2000-2017.","authors":"Michal Marczyk, Adriana Kahn, Andrea Silber, Mariya Rosenblit, Michael P Digiovanna, Maryam Lustberg, Lajos Pusztai","doi":"10.1093/jnci/djae241","DOIUrl":"10.1093/jnci/djae241","url":null,"abstract":"<p><strong>Background: </strong>Approximately 40,000 individuals die from metastatic breast cancer each year. We examined what fractions of annual breast cancer-specific death (BCSD) are due to stage I, II, III, IV disease and if these proportions changed over time.</p><p><strong>Methods: </strong>We used data from SEER covering 1975 to 2017. After filtering for female sex at birth, one primary tumor type, surgery, AJCC (6th edition) stage > 0, no bilateral cancer, and survival data available, the final analysis included 972,763 patients. Temporal trends were assessed using a linear model and ANOVA test.</p><p><strong>Results: </strong>The contribution of stage I and II cancers to BCSD increased significantly from 16.2% to 23.1%, and from 30.7% to 39.5%, respectively between 2000 and 2017. The contribution of stages III and IV cancers decreased from 36.4% to 30.3%, and from 16.7% to 7.1%. In 2000, 0.92%, 4.0% and 10.7% of BCSD were due to T1a, T1b, and T1c node-negative cancers which increased significantly to 1.9%, 5.8%, and 14.7% by 2017. These temporal trends were similar for hormone receptor-positive and -negative cancers. The contribution of BCSD to all-cause mortality declined from 23.9% to 16.6% for stage I, and from 47.7% to 36.9% for stage II cancers by 2017.</p><p><strong>Conclusions: </strong>Patients with stage I/II breast cancers have excellent prognosis, yet these cancers account for over 60% of current BCSD because of their large absolute numbers. To further reduce breast cancer death strategies are needed to identify and treat patients with stage I/II disease who remain at risk for recurrence.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142346975","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":"Automated patient selection and care coaches to increase advance care planning for cancer patients.","authors":"Michael F Gensheimer, Winifred Teuteberg, Manali I Patel, Divya Gupta, Mahjabin Noroozi, Xi Ling, Touran Fardeen, Briththa Seevaratnam, Ying Lu, Nina Alves, Brian Rogers, Mary Khay Asuncion, Jan Denofrio, Jennifer Hansen, Nigam H Shah, Thomas Chen, Elwyn Cabebe, Douglas W Blayney, A Dimitrios Colevas, Kavitha Ramchandran","doi":"10.1093/jnci/djae243","DOIUrl":"10.1093/jnci/djae243","url":null,"abstract":"<p><strong>Background: </strong>Advance care planning/serious illness conversations can help clinicians understand patients' values and preferences. There are limited data on how to increase these conversations, and their effect on care patterns. We hypothesized that using a machine learning survival model to select patients for serious illness conversations, along with trained care coaches to conduct the conversations, would increase uptake in cancer patients at high risk of short-term mortality.</p><p><strong>Methods: </strong>We conducted a cluster-randomized stepped wedge study on the physician level. Oncologists entered the intervention condition in a random order over six months. Adult patients with metastatic cancer were included. Patients with <2 year computer-predicted survival and no prognosis documentation were classified as high-priority for serious illness conversations. In the intervention condition, providers received automated weekly emails highlighting high-priority patients and were asked to document prognosis for them. Care coaches reached out to these patients to conduct the remainder of the conversation. The primary endpoint was proportion of visits with prognosis documentation within 14 days.</p><p><strong>Results: </strong>6,372 visits in 1,825 patients were included in the primary analysis. The proportion of visits with prognosis documentation within 14 days was higher in the intervention condition than control condition: 2.9% vs 1.1% (adjusted odds ratio 4.3, p < .0001). The proportion of visits with advance care planning documentation was also higher in the intervention condition: 7.7% vs 1.8% (adjusted odds ratio 14.2, p < .0001). In high-priority visits, advance care planning documentation rate in intervention/control visits was 24.2% vs 4.0%.</p><p><strong>Conclusion: </strong>The intervention increased documented conversations, with contributions by both providers and care coaches.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142346973","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":"Impact of COVID-19 on 2021 cancer incidence rates and potential rebound from 2020 decline.","authors":"Nadia Howlader, Huann-Sheng Chen, Anne-Michelle Noone, Daniel Miller, Jeffry Byrne, Serban Negoita, Kathleen A Cronin, Angela B Mariotto","doi":"10.1093/jnci/djae180","DOIUrl":"https://doi.org/10.1093/jnci/djae180","url":null,"abstract":"<p><p>The COVID-19 pandemic led to substantial declines in cancer incidence rates in 2020, likely because of disruptions in screening and diagnostic services. This study aimed to assess the impact of the pandemic on cancer incidence rates in the United States using 2021 incidence data from the Surveillance, Epidemiology, and End Results program. The analysis compared observed 2021 cancer incidence rates with expected prepandemic trends, evaluating changes by individual cancer site and stage. Although incidence overall and in many cancer sites the rates were close to prepandemic levels, they did not exhibit a recovery that incorporated the delayed diagnoses from 2020. There were exceptions, however, such as metastatic breast cancer, which showed significantly higher observed rates than expected (rate ratio = 1.09, 95% confidence interval = 1.04 to 1.13). Ongoing monitoring and targeted interventions are needed to address the long-term consequences of the COVID-19 pandemic on cancer care and outcomes.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307794","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":"Utility of genomic testing in children, adolescents, and young adults with cancer.","authors":"Emily Debortoli, Ella Mcgahan, Tatiane Yanes, Jennifer Berkman, Noemi Fuentes-Bolanos, Vivienne Milch, Julia Steinberg, Aideen Mcinerney-Leo","doi":"10.1093/jnci/djae233","DOIUrl":"https://doi.org/10.1093/jnci/djae233","url":null,"abstract":"<p><p>Genomic testing can inform the diagnosis and personalise management of cancers in children, adolescents, and young adults (CAYA). This scoping review explored the clinical utility and impact of genomic testing in general CAYA cancer cohorts. Relevant records published in English between 2017-2024 were identified by searching PubMed. 36 studies (32 original articles; 4 reviews) were identified on genomic testing in CAYA cancers, most of which were advanced cancers. Studies internationally reported that approximately 16-18% of CAYAs with cancer carry an associated pathogenic germline variant where 40% are de-novo, and can guide treatment (eg, DNA repair gene variants). Somatic variants, predominantly copy number or structural rearrangements, inform diagnosis in up to 95% of primary cancers. Between 18-69% of patients have a somatic variant with a matched therapy, but only one third receive the genomic-guided recommendation, predominantly due to declining patient condition. Few studies evaluated the impact of matched therapies on response and survival. Combining comprehensive DNA and RNA sequencing maximises sensitivity. Circulating tumour DNA was detected in most primary cancers and shows high concordance with tumour tissue. In conclusion, genomic testing of CAYA cancers is feasible, informs diagnoses and guides personalised care. Further research is needed on response to genomic-guided treatments.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307796","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":"Disparities in the Utilization of MRI for Prostate Cancer Detection: A Population-Based Study.","authors":"Christiane J El Khoury, Stephen J Freedland, Krupa Gandhi, Scott W Keith, Nikita Nikita, Amy Shaver, Swapnil Sharma, Wm Kevin Kelly, Grace Lu-Yao","doi":"10.1093/jnci/djae234","DOIUrl":"https://doi.org/10.1093/jnci/djae234","url":null,"abstract":"<p><strong>Background: </strong>Racial disparities exist in prostate cancer (PCa) care and outcomes. Ultrasound-guided biopsy may miss a significant portion of clinically significant PCa while magnetic resonance imaging (MRI) improves its detection. This study aims to investigate demographic and SES factors influencing MRI utilization for PCa detection.</p><p><strong>Methods: </strong>SEER-Medicare data were used to assess use of pre-diagnostic MRI in 90,908 patients diagnosed with primary PCa (2012-2019). Modified Poisson regression models adjusted for socioeconomic factors such as income, education, Medicare buy-in and dual eligibility were used to examine factors associated with MRI use. All statistical tests were two-sided.</p><p><strong>Results: </strong>Pre-diagnostic MRI utilization increased substantially between 2012 (3.8%) and 2019 (32.6%). The disparity in utilization between non-Hispanic Black and non-Hispanic White patients decreased by more than half from 43% (RR = 0.57, 95%CI = 0.48-0.67) in 2012 to 20% (RR = 0.80, 95%CI = 0.74-0.86) in 2019. Rural residents were 35% less likely (RR = 0.65, 95%CI = 0.61-0.69) to undergo MRI, while those in the Central US (vs West) were 49% less likely (RR = 0.49, 95%CI = 0.48-0.51). No significant disparities in MRI use were identified between ages ≥75 and 64-75. SES factors associated with MRI were income, education, Medicare buy-in and dual eligibility.</p><p><strong>Conclusions: </strong>This study revealed increased MRI utilization over time including among those 75 and older. Racial disparities decreased, while wide urban/rural disparities remained. Targeted public health interventions should focus on geographical factors, as \"urban/rural designations\" and \"US region\" were associated with the most prominent disparities. Future research should explore pathways contributing to these disparities, using a multidisciplinary approach, including geographical studies, to help eliminate healthcare inequities.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307793","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":"Tracking Community Outreach and Engagement Activities among National Cancer Institute-Designated Cancer Centers.","authors":"Todd Burus, Caree R McAfee, Pamela C Hull, Amy E Leader, Christopher McNair","doi":"10.1093/jnci/djae232","DOIUrl":"https://doi.org/10.1093/jnci/djae232","url":null,"abstract":"<p><p>The National Cancer Institute's (NCI) Cancer Center Support Grant mandates that NCI-Designated Cancer Centers establish a Community Outreach and Engagement (COE) component to help direct efforts at reducing cancer burden within their catchment areas. Despite the critical role of COE offices, little is known about how they track and evaluate outreach activities and outcomes. We gathered information on current practices from representatives of 40 out of 65 COE offices using an online survey. While nearly all responding centers (97.5%) tracked COE activities, no consensus existed on resources used and satisfaction with current solutions was mixed (51.0% not satisfied). Respondents expressed need for a centralized, standardized, and comprehensive tracking solution to capture outreach events and external partnerships, automate report generation, and ensure alignment with COE aims. This study highlights challenges COE offices face with resource limitations and a heterogeneity of activities to track, and the need for a standard evaluation framework.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307795","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":"Lung cancer screening with low-dose computed tomography-where do we go from here?","authors":"Ashley Elizabeth Prosper, Yannan Lin, Denise R Aberle","doi":"10.1093/jnci/djae197","DOIUrl":"https://doi.org/10.1093/jnci/djae197","url":null,"abstract":"","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142287739","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":"Long-Term survival across breslow thickness categories: Findings from a Population-Based study of 210,042 Australian melanoma patients.","authors":"Serigne N Lo, Gabrielle J Williams, Anne E Cust, Alexander H R Varey, Sydney Ch'ng Md, Richard A Scolyer, John F Thompson","doi":"10.1093/jnci/djae198","DOIUrl":"10.1093/jnci/djae198","url":null,"abstract":"<p><p>The prognosis of a patient with a primary cutaneous melanoma is known to be related to the Breslow thickness of their tumor. This study sought to determine long-term (30-year) survival rates for the four AJCC 8th Edition T-categories by analyzing Australian registry data for 210,042 melanoma patients diagnosed from 1982-2014. The 30-year incidence rates of death due to melanoma and non-melanoma causes (with 95% confidence intervals) were 7.1% (CI 6.9-7.3%) and 32.8% (CI 32.3-33.3%), respectively. For T2 melanomas, the corresponding rates were 21.6% (CI 21.0-22.3%) and 35.6% (CI 34.7-36.6%), for T3 melanomas 34.2% (CI 33.4-35.1%) and 39.6% (CI 38.5-40.8%), and for T4 melanomas 44.3% (CI 43.2-45.3%) and 39.6% (CI 38.3-41.0%). A plateau in melanoma-related deaths occurred in T4 patients after 20 years but there were ongoing melanoma-related deaths for the other T-categories beyond 30 years. A progressive rise in the risk of death from other causes occurred across all T-categories.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142154143","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":"Understanding risk factors for endometrial cancer in young women.","authors":"Noah Charles Peeri, Kimberly A Bertrand, Renhua Na, Immaculata De Vivo, Veronica Wendy Setiawan, Venkatraman E Seshan, Laia Alemany, Yu Chen, Megan A Clarke, Tess Clendenen, Linda S Cook, Laura Costas, Luigino Dal Maso, Jo L Freudenheim, Christine M Friedenreich, Gretchen L Gierach, Marc T Goodman, Carlo La Vecchia, Fabio Levi, Marta Lopez-Querol, Lingeng Lu, Kirsten B Moysich, George Mutter, Jeffin Naduparambil, Eva Negri, Kelli O'Connell, Tracy O'Mara, Julie R Palmer, Fabio Parazzini, Kathryn Lee Penney, Stacey Petruzella, Peggy Reynolds, Fulvio Ricceri, Harvey Risch, Thomas E Rohan, Carlotta Sacerdote, Sven Sandin, Xiao-Ou Shu, Rachael Z Stolzenberg-Solomon, Penelope M Webb, Nicolas Wentzensen, Lynne R Wilkens, Wanghong Xu, Herbert Yu, Anne Zeleniuch-Jacquotte, Wei Zheng, Xingyi Guo, Loren Lipworth, Mengmeng Du","doi":"10.1093/jnci/djae210","DOIUrl":"10.1093/jnci/djae210","url":null,"abstract":"<p><strong>Background: </strong>The American Cancer Society recommends physicians inform average risk women about endometrial cancer (EC) risk on reaching menopause, but new diagnoses are rising fastest in women <50 years. Educating these women about EC risks requires knowledge of risk factors. However, EC in young women is rare and challenging to study in single study populations.</p><p><strong>Methods: </strong>We included 13,846 incident EC patients (1,639 < 50 years) and 30,569 matched control individuals from the Epidemiology of Endometrial Cancer Consortium. We used generalized linear models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for 6 risk factors and EC risk. We created a risk score to evaluate the combined associations and population attributable fractions of these factors.</p><p><strong>Results: </strong>In younger and older women, we observed positive associations with BMI and diabetes, and inverse associations with age at menarche, oral contraceptive use, and parity. Current smoking was associated with reduced risk only in women ≥50 years (PHet<0.01). BMI was the strongest risk factor [OR≥35 vs <25 kg/m2=5.57 (95% CI:4.33-7.16) for <50 years; OR≥35 vs <25 kg/m2=4.68 (95% CI : 4.30-5.09) for ≥50 years; PHet=0.14]. Possessing ≥4 risk factors was associated with ∼9-fold increased risk in women <50 years and ∼4-fold increased risk in women ≥50 years (PHet<0.01). Together, 59.1% of ECs in women <50 and 55.6% in women ≥50 were attributable to these factors.</p><p><strong>Conclusions: </strong>Our data confirm younger and older women share common EC risk factors. Early educational efforts centered on these factors may help mitigate the rising EC burden in young women.</p>","PeriodicalId":14809,"journal":{"name":"JNCI Journal of the National Cancer Institute","volume":" ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140157","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}