Nearly all cervical cancers are caused by human papillomavirus (HPV). In 2006, adolescent females were recommended to receive the HPV vaccine. Our study aimed to quantify the impact of introducing the HPV vaccine in 2006 on cervical cancer incidence in 2022. We analyzed the latest Surveillance, Epidemiology, and End Results data. Our design compared the change in cervical cancer incidence from 2019 to 2022 between females recommended for HPV vaccination in 2006 (age 25-29) and females who were not (age 35-54). Beyond simple pre/post comparisons, our linear regression model adjusted for age-specific incidence trends. We found that, unlike the stagnate trends in older females between 2019 and 2022, in 25-29-year-old females, cervical cancer incidence declined 2.1 cases/100 000 (95% CI = -2.7 to -1.6): a 48% reduction from baseline trends. Although tempered by uneven adherence, after 15 years we finally appear to be realizing quantifiable benefits from this cancer prevention vaccine.
{"title":"Quantifying the impact of introducing HPV vaccines in 2006 on 25-29-year-old cervical cancer incidence in 2022.","authors":"Jason Semprini, Joshua Devine, Rachel Reimer","doi":"10.1093/jncics/pkaf059","DOIUrl":"10.1093/jncics/pkaf059","url":null,"abstract":"<p><p>Nearly all cervical cancers are caused by human papillomavirus (HPV). In 2006, adolescent females were recommended to receive the HPV vaccine. Our study aimed to quantify the impact of introducing the HPV vaccine in 2006 on cervical cancer incidence in 2022. We analyzed the latest Surveillance, Epidemiology, and End Results data. Our design compared the change in cervical cancer incidence from 2019 to 2022 between females recommended for HPV vaccination in 2006 (age 25-29) and females who were not (age 35-54). Beyond simple pre/post comparisons, our linear regression model adjusted for age-specific incidence trends. We found that, unlike the stagnate trends in older females between 2019 and 2022, in 25-29-year-old females, cervical cancer incidence declined 2.1 cases/100 000 (95% CI = -2.7 to -1.6): a 48% reduction from baseline trends. Although tempered by uneven adherence, after 15 years we finally appear to be realizing quantifiable benefits from this cancer prevention vaccine.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Buraq Ahmed, Qutaiba Al-Khames Aga, Kwok-Leung Cheung, Jana de Boniface, Michael Gnant, Maria-Joao Cardoso, Emad Rakha, Thiraviyam Elumalai, Nadia Harbeck, Orit Kaidar-Person, Amit Agrawal
Background: Although the relative proportion of triple-negative breast cancer decreases with age, its prevalence is rising with an aging population. This study examined real-world treatment practices, whether age in older women with triple-negative breast cancer affects therapy and outcomes, focusing on the potentially curable nature of early-stage triple-negative breast cancer.
Methods: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PRISMA-compliant search using population, intervention, comparison, outcomes criteria identified literature from 2014 to 2023 across 5 databases (MEDLINE, Embase, PubMed, Web of Science, and Scopus), focusing on women aged 65 years and older with early-stage triple-negative breast cancer.
Results: From 7171 records, 37 studies were included. Older women with triple-negative breast cancer exhibited less aggressive features, including lower Ki67, higher androgen receptor, and higher Bcl2 expression. Breast-conserving surgery with radiation therapy (RT) was associated with improved overall survival and breast cancer-specific survival, with fewer recurrences compared with mastectomy with or without RT. Older women with triple-negative breast cancer were more likely to receive RT than systemic therapy, and the lack of RT correlated with worse outcomes. Multivariate analyses showed that systemic treatment improved 5-year overall survival and breast cancer-specific survival. Overall, outcomes did not show significant differences between women aged 70 years and older and women younger than 70 years at a median follow-up of 46 months.
Conclusions: The lack of overall outcome improvements for older women with triple-negative breast cancer following treatment may not solely be due to absent targetable receptors because the intrinsic biology in older patients may be relatively favorable. Instead, treatment selection biases against active treatment due to age-related factors may contribute substantially. Treatment decisions should be biology based and guided by a multidisciplinary, holistic, and patient-centered approach that carefully considers comorbidities, functional status, social support, and patient preferences.
目的:虽然三阴性乳腺癌(TNBC)的相对比例随着年龄的增长而下降,但其患病率随着人口老龄化而上升。本研究考察了现实世界的治疗实践,年龄是否会影响老年妇女TNBC (owTNBC)的治疗和结果,重点关注早期TNBC的潜在可治愈性。方法:使用PICO标准对5个数据库(MEDLINE、Embase、PubMed、Web of Science和Scopus)中2014年至2023年的文献进行符合prisma标准的检索,重点关注65岁及以上的早期TNBC女性。结果:从7171份记录中,纳入了37项研究。owTNBC表现出较低的侵袭性特征,包括较低的Ki67,较高的雄激素受体和较高的Bcl2表达。与乳房切除术+/-放疗相比,保乳手术加放疗(RT)可提高总生存率和乳腺癌特异性生存率(BCSS),并减少复发率。owTNBC患者更有可能接受RT而不是全身治疗,并且缺乏RT与较差的结果相关。多因素分析显示,全身治疗可改善5年总生存率和BCSS。结论:owTNBC治疗后缺乏总体预后改善可能不仅仅是由于缺乏靶向受体,因为老年患者的内在生物学可能相对有利。相反,由于与年龄相关的因素,治疗选择偏差对积极治疗的影响可能很大。治疗决定应以生物学为基础,并以多学科、整体和以患者为中心的方法为指导,仔细考虑合并症、功能状态、社会支持和患者偏好。
{"title":"Treatment strategies for triple-negative primary breast cancer in older women: a systematic review.","authors":"Buraq Ahmed, Qutaiba Al-Khames Aga, Kwok-Leung Cheung, Jana de Boniface, Michael Gnant, Maria-Joao Cardoso, Emad Rakha, Thiraviyam Elumalai, Nadia Harbeck, Orit Kaidar-Person, Amit Agrawal","doi":"10.1093/jncics/pkaf049","DOIUrl":"10.1093/jncics/pkaf049","url":null,"abstract":"<p><strong>Background: </strong>Although the relative proportion of triple-negative breast cancer decreases with age, its prevalence is rising with an aging population. This study examined real-world treatment practices, whether age in older women with triple-negative breast cancer affects therapy and outcomes, focusing on the potentially curable nature of early-stage triple-negative breast cancer.</p><p><strong>Methods: </strong>A Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PRISMA-compliant search using population, intervention, comparison, outcomes criteria identified literature from 2014 to 2023 across 5 databases (MEDLINE, Embase, PubMed, Web of Science, and Scopus), focusing on women aged 65 years and older with early-stage triple-negative breast cancer.</p><p><strong>Results: </strong>From 7171 records, 37 studies were included. Older women with triple-negative breast cancer exhibited less aggressive features, including lower Ki67, higher androgen receptor, and higher Bcl2 expression. Breast-conserving surgery with radiation therapy (RT) was associated with improved overall survival and breast cancer-specific survival, with fewer recurrences compared with mastectomy with or without RT. Older women with triple-negative breast cancer were more likely to receive RT than systemic therapy, and the lack of RT correlated with worse outcomes. Multivariate analyses showed that systemic treatment improved 5-year overall survival and breast cancer-specific survival. Overall, outcomes did not show significant differences between women aged 70 years and older and women younger than 70 years at a median follow-up of 46 months.</p><p><strong>Conclusions: </strong>The lack of overall outcome improvements for older women with triple-negative breast cancer following treatment may not solely be due to absent targetable receptors because the intrinsic biology in older patients may be relatively favorable. Instead, treatment selection biases against active treatment due to age-related factors may contribute substantially. Treatment decisions should be biology based and guided by a multidisciplinary, holistic, and patient-centered approach that carefully considers comorbidities, functional status, social support, and patient preferences.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12199755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kamran Abbasi, Parveen Ali, Virginia Barbour, Marion Birch, Inga Blum, Peter Doherty, Andy Haines, Ira Helfand, Richard Horton, Kati Juva, Jose F Lapena, Robert Mash, Olga Mironova, Arun Mitra, Carlos Monteiro, Elena N Naumova, David Onazi, Tilman Ruff, Peush Sahni, James Tumwine, Carlos Umaña, Paul Yonga, Chris Zielinski
{"title":"Ending nuclear weapons, before they end us†.","authors":"Kamran Abbasi, Parveen Ali, Virginia Barbour, Marion Birch, Inga Blum, Peter Doherty, Andy Haines, Ira Helfand, Richard Horton, Kati Juva, Jose F Lapena, Robert Mash, Olga Mironova, Arun Mitra, Carlos Monteiro, Elena N Naumova, David Onazi, Tilman Ruff, Peush Sahni, James Tumwine, Carlos Umaña, Paul Yonga, Chris Zielinski","doi":"10.1093/jncics/pkaf044","DOIUrl":"10.1093/jncics/pkaf044","url":null,"abstract":"","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":"9 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12085997/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144093861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erin J Aiello Bowles, Hongyuan Gao, Lynn E Fleckenstein, Perla Bravo, Michael G Nash, Bryan Comstock, Chris Neslund-Dudas, Jin Mou, Larry G Kessler
We validated updated National Health Interview Survey questions on mammography indications compared with electronic health records (EHRs). We asked 244 Kaiser Permanente Washington members ages 40-74 years and eligible for breast cancer screening to self-report their most recent mammogram reason by using a series of new hierarchical yes/no questions. We first asked if they had the mammogram because of a health problem, then as a follow-up test, and last for screening. We compared self-reported reasons with 2 EHR datasets: procedure/diagnostic codes and radiologist-defined indications. Self-reported exams for a health problem had 89.2% agreement with codes and 92.2% agreement with radiologist-defined indications. Self-reported exams for follow-up had 87.5% agreement with codes and 89.3% agreement with radiologist-defined indications. Self-reported exams for screening had 91.4% agreement with codes and 95.7% agreement with radiologist-defined indications. Self-reported mammogram indications have good agreement with procedure/diagnostic codes and radiologist-reported indications, when asked using this novel hierarchical approach.
{"title":"Accuracy of self-reported exam indications for breast cancer screening.","authors":"Erin J Aiello Bowles, Hongyuan Gao, Lynn E Fleckenstein, Perla Bravo, Michael G Nash, Bryan Comstock, Chris Neslund-Dudas, Jin Mou, Larry G Kessler","doi":"10.1093/jncics/pkaf046","DOIUrl":"10.1093/jncics/pkaf046","url":null,"abstract":"<p><p>We validated updated National Health Interview Survey questions on mammography indications compared with electronic health records (EHRs). We asked 244 Kaiser Permanente Washington members ages 40-74 years and eligible for breast cancer screening to self-report their most recent mammogram reason by using a series of new hierarchical yes/no questions. We first asked if they had the mammogram because of a health problem, then as a follow-up test, and last for screening. We compared self-reported reasons with 2 EHR datasets: procedure/diagnostic codes and radiologist-defined indications. Self-reported exams for a health problem had 89.2% agreement with codes and 92.2% agreement with radiologist-defined indications. Self-reported exams for follow-up had 87.5% agreement with codes and 89.3% agreement with radiologist-defined indications. Self-reported exams for screening had 91.4% agreement with codes and 95.7% agreement with radiologist-defined indications. Self-reported mammogram indications have good agreement with procedure/diagnostic codes and radiologist-reported indications, when asked using this novel hierarchical approach.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12124912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143967156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rulin C Hechter, Lie Hong Chen, Jiaxiao Shi, Zheng Gu, Moira Brady-Rogers, Rowan T Chlebowski, Reina Haque
Background: Harm associated with persistent opioid use beyond the first-year intensive cancer treatment is underinvestigated in cancer survivors. We examined rates and risk factors for persistent opioid use and all-cause mortality after the first-year breast cancer survivorship.
Methods: This retrospective cohort study used electronic health record data from Kaiser Permanente Southern California for women diagnosed with a nonmetastatic breast cancer between 2009 and 2019 who filled 2 or more opioid prescriptions. Rates of persistent opioid use were estimated from first-year survivorship through December 31, 2021. Rate ratios (RRs) and 95% confidence intervals (CIs) for factors associated with persistent use were estimated using a multivariable Poisson regression model. Hazard ratios (HRs) for all-cause mortality associated with persistent opioid use were estimated using multivariable Cox regression models.
Results: Of 14 347 eligible individuals (mean [SD] age = 61.9 [12.5]), 2285 (15.9%) developed persistent opioid use, with an incident rate of 25.5 per 1000 person-years. Risk factors included older age (≥65 vs < 65 years: RR = 1.63, 95% CI = 1.24 to 2.14), smoking (current: 1.89, 1.68 to 2.13; former: 1.30, 1.20 to 1.41), baseline comorbidities (Elixhauser Comorbidity Index 5+ vs 0: 1.70, 1.29 to 2.24), and substance use disorders (1.58, 1.43 to 1.74). All-cause mortality was doubled among individuals with persistent use (51.6, 48.0 to 55.6 per 1000 person-years) than in those without (25.3, 24.2 to 26.4). Persistent use was associated with an increased all-cause mortality (adjusted HR = 1.84, 1.66 to 2.04).
Conclusions: Persistent opioid use was common in breast cancer survivors and associated with increased mortality. Further research is needed to explore factors that may be contributing to increased mortality.
{"title":"Persistent prescription opioid use and all-cause mortality following the first-year breast cancer survivorship.","authors":"Rulin C Hechter, Lie Hong Chen, Jiaxiao Shi, Zheng Gu, Moira Brady-Rogers, Rowan T Chlebowski, Reina Haque","doi":"10.1093/jncics/pkaf060","DOIUrl":"10.1093/jncics/pkaf060","url":null,"abstract":"<p><strong>Background: </strong>Harm associated with persistent opioid use beyond the first-year intensive cancer treatment is underinvestigated in cancer survivors. We examined rates and risk factors for persistent opioid use and all-cause mortality after the first-year breast cancer survivorship.</p><p><strong>Methods: </strong>This retrospective cohort study used electronic health record data from Kaiser Permanente Southern California for women diagnosed with a nonmetastatic breast cancer between 2009 and 2019 who filled 2 or more opioid prescriptions. Rates of persistent opioid use were estimated from first-year survivorship through December 31, 2021. Rate ratios (RRs) and 95% confidence intervals (CIs) for factors associated with persistent use were estimated using a multivariable Poisson regression model. Hazard ratios (HRs) for all-cause mortality associated with persistent opioid use were estimated using multivariable Cox regression models.</p><p><strong>Results: </strong>Of 14 347 eligible individuals (mean [SD] age = 61.9 [12.5]), 2285 (15.9%) developed persistent opioid use, with an incident rate of 25.5 per 1000 person-years. Risk factors included older age (≥65 vs < 65 years: RR = 1.63, 95% CI = 1.24 to 2.14), smoking (current: 1.89, 1.68 to 2.13; former: 1.30, 1.20 to 1.41), baseline comorbidities (Elixhauser Comorbidity Index 5+ vs 0: 1.70, 1.29 to 2.24), and substance use disorders (1.58, 1.43 to 1.74). All-cause mortality was doubled among individuals with persistent use (51.6, 48.0 to 55.6 per 1000 person-years) than in those without (25.3, 24.2 to 26.4). Persistent use was associated with an increased all-cause mortality (adjusted HR = 1.84, 1.66 to 2.04).</p><p><strong>Conclusions: </strong>Persistent opioid use was common in breast cancer survivors and associated with increased mortality. Further research is needed to explore factors that may be contributing to increased mortality.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12205851/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144274852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hideaki Bando, Yuriko Takeda, Toshihiro Misumi, Tomomi Nishikawa, Masashi Wakabayashi, Kentaro Yamazaki, Eiji Oki, Jean-Yves Douillard, Cornelis J A Punt, Miriam Koopman, Eric Van Cutsem, Carsten Bokemeyer, Alan P Venook, Heinz-Josef Lenz, Yoshihiko Maehara, Thierry Andre, Qian Shi, Aimery de Gramont, Takayuki Yoshino
Background: Early tumor shrinkage and depth of response have emerged as potential prognostic indicators in metastatic colorectal cancer (CRC). However, their associations with overall survival, progression-free survival (PFS), and postprogression survival in patients receiving anti-epidermal growth factor receptor (EGFR) antibodies or bevacizumab remain unclear.
Methods: We analyzed 3219 treatment-naive patients with RAS wild-type metastatic CRC from 8 randomized studies (CRYSTAL, OPUS, PRIME, CAIRO2, CALGB80405, WJOG4407G, ATOM, PARADIGM) in the Aid and Research in Digestive Cancerology database. Early tumor shrinkage was defined as a 20% or more reduction in tumor size at 8 ± 2 weeks, whereas depth of response was assessed by maximum tumor shrinkage at nadir. Cox regression models evaluated the associations of early tumor shrinkage and depth of response with overall survival, PFS, and postprogression survival, adjusting for confounders. A 2-sided test was conducted with a significance level of .05.
Results: Early tumor shrinkage and depth of response substantially stratified overall survival, PFS, and postprogression survival outcomes across all treatment groups. Early tumor shrinkage positivity was associated with improved overall survival, PFS, and postprogression survival in anti-EGFR and bevacizumab-based therapies, with a trend toward better outcomes in the anti-EGFR group. The depth of response analysis revealed optimal cutoff values of 0.55 for anti-EGFR-based therapy and 0.47 for bevacizumab-based therapy to achieve a median overall survival of approximately 32 months.
Conclusions: Early tumor shrinkage and depth of response serve as valuable prognostic markers in RAS wild-type metastatic CRC, particularly for patients treated with anti-EGFR antibodies. These findings highlight the potential role of early tumor shrinkage and depth of response in guiding treatment strategies and improving outcomes for patients with CRC.
{"title":"Associations between early tumor shrinkage/depth of response and survival from the ARCAD database.","authors":"Hideaki Bando, Yuriko Takeda, Toshihiro Misumi, Tomomi Nishikawa, Masashi Wakabayashi, Kentaro Yamazaki, Eiji Oki, Jean-Yves Douillard, Cornelis J A Punt, Miriam Koopman, Eric Van Cutsem, Carsten Bokemeyer, Alan P Venook, Heinz-Josef Lenz, Yoshihiko Maehara, Thierry Andre, Qian Shi, Aimery de Gramont, Takayuki Yoshino","doi":"10.1093/jncics/pkaf042","DOIUrl":"10.1093/jncics/pkaf042","url":null,"abstract":"<p><strong>Background: </strong>Early tumor shrinkage and depth of response have emerged as potential prognostic indicators in metastatic colorectal cancer (CRC). However, their associations with overall survival, progression-free survival (PFS), and postprogression survival in patients receiving anti-epidermal growth factor receptor (EGFR) antibodies or bevacizumab remain unclear.</p><p><strong>Methods: </strong>We analyzed 3219 treatment-naive patients with RAS wild-type metastatic CRC from 8 randomized studies (CRYSTAL, OPUS, PRIME, CAIRO2, CALGB80405, WJOG4407G, ATOM, PARADIGM) in the Aid and Research in Digestive Cancerology database. Early tumor shrinkage was defined as a 20% or more reduction in tumor size at 8 ± 2 weeks, whereas depth of response was assessed by maximum tumor shrinkage at nadir. Cox regression models evaluated the associations of early tumor shrinkage and depth of response with overall survival, PFS, and postprogression survival, adjusting for confounders. A 2-sided test was conducted with a significance level of .05.</p><p><strong>Results: </strong>Early tumor shrinkage and depth of response substantially stratified overall survival, PFS, and postprogression survival outcomes across all treatment groups. Early tumor shrinkage positivity was associated with improved overall survival, PFS, and postprogression survival in anti-EGFR and bevacizumab-based therapies, with a trend toward better outcomes in the anti-EGFR group. The depth of response analysis revealed optimal cutoff values of 0.55 for anti-EGFR-based therapy and 0.47 for bevacizumab-based therapy to achieve a median overall survival of approximately 32 months.</p><p><strong>Conclusions: </strong>Early tumor shrinkage and depth of response serve as valuable prognostic markers in RAS wild-type metastatic CRC, particularly for patients treated with anti-EGFR antibodies. These findings highlight the potential role of early tumor shrinkage and depth of response in guiding treatment strategies and improving outcomes for patients with CRC.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12159729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144024309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eric T Hyde, Kelly R Evenson, Gretchen E Bandoli, Jingjing Zou, Noe C Crespo, Humberto Parada, Michael J LaMonte, Annie Green Howard, Steve Nguyen, Meghan B Skiba, Tracy E Crane, Marcia L Stefanick, I-Min Lee, Andrea Z LaCroix
Background: Data on prospective associations of accelerometer-measured physical activity, sedentary behavior, and mortality among cancer survivors are lacking. Our study examined accelerometer-measured daily physical activity (including light, moderate to vigorous, total, and steps), sedentary behavior (sitting time and mean bout duration), and mortality among cancer survivors in the Women's Health Accelerometry Collaboration.
Methods: Postmenopausal women in the Collaboration who reported a cancer diagnosis at least 1 year prior to wearing an ActiGraph GT3X+ device on the hip for at least 4 of 7 days from 2011 to 2015 were included. Outcomes included all-cause, cancer-related, and cardiovascular disease (CVD)-related mortality. Covariate-adjusted Cox regression estimated hazard ratios (HRs) and 95% CIs for each physical activity and sedentary behavior measure in association with mortality.
Results: Overall, 2479 cancer survivors (mean [SD] age, 74.2 [6.7] years) were followed up for 8.3 years. For all-cause mortality (n = 594 cases), every 78.1 minutes per day in light physical activity, 96.5 minutes per day in total physical activity, 102.2 minutes per day in sitting time, and 4.8 minutes in a sitting bout duration had hazard ratios of 0.92 (95% CI = 0.84 to 1.01), 0.89 (95% CI = 0.80 to 0.98), 1.12 (95% CI = 1.02 to 1.24), and 1.04 (95% CI = 0.96 to 1.12), respectively. Linear associations for cancer mortality (n = 168) and CVD mortality (n = 109) were not statistically significant, except for steps (hazard ratio per 2469 steps/d = 0.66, 95% CI = 0.45 to 0.96) and sitting time (hazard ratio = 1.30, 95% CI = 1.02 to 1.67) for CVD mortality. Nonlinear associations showed benefits of moderate to vigorous physical activity (for all-cause and CVD mortality) and steps (all-cause mortality only) maximized at approximately 60 minutes per day and 5000-6000 steps per day, respectively.
Conclusions: Among postmenopausal cancer survivors, higher physical activity and lower sedentary behavior was associated with reduced hazards of all-cause and CVD mortality.
{"title":"Accelerometer-measured physical activity, sedentary behavior, and mortality among cancer survivors: the Women's Health Accelerometry Collaboration.","authors":"Eric T Hyde, Kelly R Evenson, Gretchen E Bandoli, Jingjing Zou, Noe C Crespo, Humberto Parada, Michael J LaMonte, Annie Green Howard, Steve Nguyen, Meghan B Skiba, Tracy E Crane, Marcia L Stefanick, I-Min Lee, Andrea Z LaCroix","doi":"10.1093/jncics/pkaf034","DOIUrl":"10.1093/jncics/pkaf034","url":null,"abstract":"<p><strong>Background: </strong>Data on prospective associations of accelerometer-measured physical activity, sedentary behavior, and mortality among cancer survivors are lacking. Our study examined accelerometer-measured daily physical activity (including light, moderate to vigorous, total, and steps), sedentary behavior (sitting time and mean bout duration), and mortality among cancer survivors in the Women's Health Accelerometry Collaboration.</p><p><strong>Methods: </strong>Postmenopausal women in the Collaboration who reported a cancer diagnosis at least 1 year prior to wearing an ActiGraph GT3X+ device on the hip for at least 4 of 7 days from 2011 to 2015 were included. Outcomes included all-cause, cancer-related, and cardiovascular disease (CVD)-related mortality. Covariate-adjusted Cox regression estimated hazard ratios (HRs) and 95% CIs for each physical activity and sedentary behavior measure in association with mortality.</p><p><strong>Results: </strong>Overall, 2479 cancer survivors (mean [SD] age, 74.2 [6.7] years) were followed up for 8.3 years. For all-cause mortality (n = 594 cases), every 78.1 minutes per day in light physical activity, 96.5 minutes per day in total physical activity, 102.2 minutes per day in sitting time, and 4.8 minutes in a sitting bout duration had hazard ratios of 0.92 (95% CI = 0.84 to 1.01), 0.89 (95% CI = 0.80 to 0.98), 1.12 (95% CI = 1.02 to 1.24), and 1.04 (95% CI = 0.96 to 1.12), respectively. Linear associations for cancer mortality (n = 168) and CVD mortality (n = 109) were not statistically significant, except for steps (hazard ratio per 2469 steps/d = 0.66, 95% CI = 0.45 to 0.96) and sitting time (hazard ratio = 1.30, 95% CI = 1.02 to 1.67) for CVD mortality. Nonlinear associations showed benefits of moderate to vigorous physical activity (for all-cause and CVD mortality) and steps (all-cause mortality only) maximized at approximately 60 minutes per day and 5000-6000 steps per day, respectively.</p><p><strong>Conclusions: </strong>Among postmenopausal cancer survivors, higher physical activity and lower sedentary behavior was associated with reduced hazards of all-cause and CVD mortality.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12062960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143730145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jaimi L Allen, Laura Q Rogers, Michelle Y Martin, Benjamin C Amick
This study examined the association of physical activity (PA) with cognitive difficulties (CD) and education, income, poverty, and age among cancer survivors (CS) using data from the 2020 National Health Interview Survey. Causal mediation analysis was tested using the bootstrapping method to examine associations between PA, cognitive difficulties, and other sociodemographic characteristics. Results showed statistically significant disparities in both CD and physical inactivity among CS with low education, low income, high poverty, and certain age categories. Health disparities related to CD based on race/ethnicity, sex, and age were also identified. Physical activity mediated the relationship between CD and education, income, poverty, and age. Future research is needed to gain deeper insight into the mechanisms of PA-induced health benefits and to develop specific PA prescription guidelines in the subgroups at risk for CD.
{"title":"The mediating role of physical activity on cognitive disparities in cancer survivors.","authors":"Jaimi L Allen, Laura Q Rogers, Michelle Y Martin, Benjamin C Amick","doi":"10.1093/jncics/pkaf023","DOIUrl":"10.1093/jncics/pkaf023","url":null,"abstract":"<p><p>This study examined the association of physical activity (PA) with cognitive difficulties (CD) and education, income, poverty, and age among cancer survivors (CS) using data from the 2020 National Health Interview Survey. Causal mediation analysis was tested using the bootstrapping method to examine associations between PA, cognitive difficulties, and other sociodemographic characteristics. Results showed statistically significant disparities in both CD and physical inactivity among CS with low education, low income, high poverty, and certain age categories. Health disparities related to CD based on race/ethnicity, sex, and age were also identified. Physical activity mediated the relationship between CD and education, income, poverty, and age. Future research is needed to gain deeper insight into the mechanisms of PA-induced health benefits and to develop specific PA prescription guidelines in the subgroups at risk for CD.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12042741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Colorectal cancer (CRC) is a major global health challenge. Emerging research highlights the pivotal role of the gut microbiota in influencing CRC risk, progression, and treatment response. Metagenomic approaches, especially high-throughput shotgun sequencing, have provided unprecedented insights into the intricate connections between the gut microbiome and CRC. By enabling comprehensive taxonomic and functional profiling, metagenomics has revealed microbial signatures, activities, and biomarkers associated with colorectal tumorigenesis. Furthermore, metagenomics has shown a potential to guide patient stratification, predict treatment outcomes, and inform microbiome-targeted interventions. Despite remaining challenges in multi-omics data integration, taxonomic gaps, and validation across diverse cohorts, metagenomics has propelled our comprehension of the intricate gut microbiome-CRC interplay. This review underscores the clinical relevance of microbial signatures as potential diagnostic and prognostic tools in CRC. Furthermore, it discusses personalized treatment strategies guided by this omics' approach.
{"title":"Gut microbiome in colorectal cancer: metagenomics from bench to bedside.","authors":"Amir Torshizi Esfahani, Nikta Zafarjafarzadeh, Fatemeh Vakili, Anahita Bizhanpour, Amirhesam Mashaollahi, Bita Karimi Kordestani, Mahdieh Baratinamin, Somayeh Mohammadpour","doi":"10.1093/jncics/pkaf026","DOIUrl":"10.1093/jncics/pkaf026","url":null,"abstract":"<p><p>Colorectal cancer (CRC) is a major global health challenge. Emerging research highlights the pivotal role of the gut microbiota in influencing CRC risk, progression, and treatment response. Metagenomic approaches, especially high-throughput shotgun sequencing, have provided unprecedented insights into the intricate connections between the gut microbiome and CRC. By enabling comprehensive taxonomic and functional profiling, metagenomics has revealed microbial signatures, activities, and biomarkers associated with colorectal tumorigenesis. Furthermore, metagenomics has shown a potential to guide patient stratification, predict treatment outcomes, and inform microbiome-targeted interventions. Despite remaining challenges in multi-omics data integration, taxonomic gaps, and validation across diverse cohorts, metagenomics has propelled our comprehension of the intricate gut microbiome-CRC interplay. This review underscores the clinical relevance of microbial signatures as potential diagnostic and prognostic tools in CRC. Furthermore, it discusses personalized treatment strategies guided by this omics' approach.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143567148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Monjoy Saha, Mustapha Abubakar, Ruth M Pfeiffer, Thomas E Rohan, Máire A Duggan, Kathryn Richert-Boe, Jonas S Almeida, Gretchen L Gierach
Background: Benign breast disease is an important risk factor for breast cancer development. In this study, we analyzed hematoxylin and eosin-stained whole-slide images from diagnostic benign breast disease biopsies using different deep learning approaches to predict which individuals would subsequently developed breast cancer (cases) or would not (controls).
Methods: We randomly divided cases and controls from a nested case-control study of 946 women with benign breast disease into training (331 cases, 331 control individuals) and test (142 cases, 142 control individuals) groups. We employed customized VGG-16 and AutoML machine learning models for image-only classification using whole-slide images, logistic regression for classification using only clinicopathological characteristics, and a multimodal network combining whole-slide images and clinicopathological characteristics for classification.
Results: Both image-only (area under the receiver operating characteristic curve [AUROC] = 0.83 [SE = 0.001] and 0.78 [SE = 0.001] for customized VGG-16 and AutoML models, respectively) and multimodal (AUROC = 0.89 [SE = 0.03]) networks had high discriminatory accuracy for breast cancer. The clinicopathological-characteristics-only model had the lowest AUROC (0.54 [SE = 0.03]). In addition, compared with the customized VGG-16 model, which performed better than the AutoML model, the multimodal network had improved accuracy (AUROC = 0.89 [SE = 0.03] vs 0.83 [SE = 0.02]), sensitivity (AUROC = 0.93 [SE = 0.04] vs 0.83 [SE = 0.003]), and specificity (AUROC = 0.86 [SE = 0.03] vs 0.84 [SE = 0.003]).
Conclusion: This study opens promising avenues for breast cancer risk assessment in women with benign breast disease. Integrating whole-slide images and clinicopathological characteristics through a multimodal approach substantially improved predictive model performance. Future research will explore deep learning techniques to understand benign breast disease progression to invasive breast cancer.
背景:乳腺良性疾病(BBD)是乳腺癌(BC)发展的重要危险因素。在这项研究中,我们使用不同的深度学习(DL)方法分析了诊断性BBD活检中苏木精和伊红染色的全切片图像(WSIs),以预测随后发展为乳腺癌的患者(病例)和未发展为乳腺癌的患者(对照组)。方法:我们将946例女性BBD病例和对照组随机分为训练组(331例,331例对照)和测试组(142例,142例对照)。我们使用定制的VGG-16和AutoML模型使用wsi进行图像分类;仅使用临床病理特征进行逻辑回归分类;以及结合wsi和临床病理特征进行分类的多模式网络。结果:单图像网络(定制VGG-16和AutoML的接收者工作特征曲线下面积,AUROC分别为0.83(标准误差,SE: 0.001)和0.78 (SE: 0.001))和多模式网络(AUROC为0.89 (SE: 0.03))对BC具有较高的鉴别准确率。仅临床病理特征模型的AUROC最低,为0.54 (SE: 0.03)。此外,与表现优于AutoML的定制VGG-16相比,多模态网络的准确率为0.89 (SE: 0.03) vs 0.83 (SE: 0.02),灵敏度为0.93 (SE: 0.04) vs 0.83 (SE: 0.003),特异性为0.86 (SE: 0.03) vs 0.84 (SE: 0.003)。结论:本研究为良性乳腺疾病女性乳腺癌风险评估开辟了有希望的途径。通过多模态方法整合整个幻灯片图像和临床病理特征显著提高了预测模型的性能。未来的研究将探索DL技术来了解BBD向浸润性BC的进展。
{"title":"Deep learning analysis of hematoxylin and eosin-stained benign breast biopsies to predict future invasive breast cancer.","authors":"Monjoy Saha, Mustapha Abubakar, Ruth M Pfeiffer, Thomas E Rohan, Máire A Duggan, Kathryn Richert-Boe, Jonas S Almeida, Gretchen L Gierach","doi":"10.1093/jncics/pkaf037","DOIUrl":"10.1093/jncics/pkaf037","url":null,"abstract":"<p><strong>Background: </strong>Benign breast disease is an important risk factor for breast cancer development. In this study, we analyzed hematoxylin and eosin-stained whole-slide images from diagnostic benign breast disease biopsies using different deep learning approaches to predict which individuals would subsequently developed breast cancer (cases) or would not (controls).</p><p><strong>Methods: </strong>We randomly divided cases and controls from a nested case-control study of 946 women with benign breast disease into training (331 cases, 331 control individuals) and test (142 cases, 142 control individuals) groups. We employed customized VGG-16 and AutoML machine learning models for image-only classification using whole-slide images, logistic regression for classification using only clinicopathological characteristics, and a multimodal network combining whole-slide images and clinicopathological characteristics for classification.</p><p><strong>Results: </strong>Both image-only (area under the receiver operating characteristic curve [AUROC] = 0.83 [SE = 0.001] and 0.78 [SE = 0.001] for customized VGG-16 and AutoML models, respectively) and multimodal (AUROC = 0.89 [SE = 0.03]) networks had high discriminatory accuracy for breast cancer. The clinicopathological-characteristics-only model had the lowest AUROC (0.54 [SE = 0.03]). In addition, compared with the customized VGG-16 model, which performed better than the AutoML model, the multimodal network had improved accuracy (AUROC = 0.89 [SE = 0.03] vs 0.83 [SE = 0.02]), sensitivity (AUROC = 0.93 [SE = 0.04] vs 0.83 [SE = 0.003]), and specificity (AUROC = 0.86 [SE = 0.03] vs 0.84 [SE = 0.003]).</p><p><strong>Conclusion: </strong>This study opens promising avenues for breast cancer risk assessment in women with benign breast disease. Integrating whole-slide images and clinicopathological characteristics through a multimodal approach substantially improved predictive model performance. Future research will explore deep learning techniques to understand benign breast disease progression to invasive breast cancer.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}