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Differential Age-Related Declines in Cardiorespiratory Fitness Between People With and Without Type 2 Diabetes Mellitus

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Mayo Clinic Proceedings: Innovations, Quality and Outcomes 2021年第4期5卷 743-752页

作者： Ortaglia, Andrew McDonald, Samantha M. Wirth, Michael D. Sui, Xuemei Bottai, Matteo Department of Epidemiology and Biostatistics Arnold School of Public Health University of South Carolina Columbia Department of Foundational Sciences and Research School of Dental Medicine East Carolina University Greenville NC United States College of Nursing Cancer Prevention and Control Program Arnold School of Public Health University of South Carolina Columbia Department of Exercise Science Arnold School of Public Health University of South Carolina Columbia Division of Biostatistics Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden

Objective: To assess the extent to which the established age-related decline in cardiorespiratory fitness (CRF) is augmented in adult men with type 2 diabetes mellitus (T2DM). Participants and Methods: This study used data from the Aerobics Center Longitudinal Study, conducted between September 18, 1974, and August 3, 2006, in primarily non-Hispanic white, middle-to-upper class adults. The analyses were restricted to adult men with complete data on age, CRF, and T2DM (35,307 participants). Quantile regression models were used to estimate age-related differences in CRF, estimated using a maximal treadmill test, between persons with and without T2DM. Smoking status and birth cohort served as covariates. Results: Age-related declines in CRF were observed in men with and without T2DM. For men younger than 60 years, at low-mid percentiles of the CRF distribution the magnitude of the age-related decline in CRF was significantly higher (P-values=.00, .02) in men with T2DM than in those without T2DM. At upper percentiles, the decline with age between the 2 groups was virtually identical. Significant declines in CRF in men 45 years or younger were observed only at high levels of CRF for those without T2DM and at low levels of CRF for those with T2DM (P-values .00, .04). Conclusion: This study reported that men younger than 60 years with T2DM at the low-mid CRF percentiles experience an accelerated age-related decline in CRF. Men younger than 60 years with T2DM exhibiting high levels of CRF experienced a decline in CRF comparable to men without T2DM. This study highlights the importance of incorporating sufficient levels of exercise or activity to maintain high CRF in men with T2DM. © 2021 [Author/Employing Institution]

关键词： ACLS Aerobics Center Longitudinal Study CRF cardiorespiratory fitness NCD noncommunicable disease T2DM type 2 diabetes mellitus V̇ o 2max maximum oxygen consumption

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Mortality Risk from Chronic Ischemic Heart Disease Associated with Short-Term Co-Exposure to Summer Heatwave and Ozone

SSRN

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SSRN 2024年

作者： Shen, Jiajun Lu, Yuchen Zhang, Yalin Zhang, Jingjing Wang, Yixiang Tan, Yuxi Zheng, Hao Zhang, Yunquan Hubei Province Key Laboratory of Occupational Hazard Identification and Control School of Public Health Wuhan University of Science and Technology Wuhan430065 China Head and Neck Surgery Department Hubei Cancer Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan430079 China Department of Environmental Health Jiangsu Provincial Center for Disease Control and Prevention Nanjing210009 China Department of Epidemiology and Biostatistics China

Background:Summer heat and ozone may pose a great threat to public health amid climate warming, however, their interactive effects on deaths from chronic ischemic heart disease (CIHD) have not been evaluated in existing investigations. Methods:We carried out a province-wide, individual-level case-crossover study by analyzing 33770 CIHD deaths occurring in warm season across Jiangsu, eastern China, between 2016 and 2019. Spatially-resolved estimates of maximum 8-hour average ozone concentrations and air temperatures were estimated on case days and control days at the residential address. Heatwave events were defined using multiple temperature thresholds and durations. Conditional logistic regression model was employed to assess the odds ratio and its 95% confidence interval of CIHD death associated with heatwave and ozone exposure. Stratified analyses were performed to compare ozone-related risks on heatwave days versus non-heatwave days, and heatwave-related risks on low-ozone days versus high-ozone days. Additive interactive effects were testified using multiple metrics including relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (SI).Results:In the overall population, the odds of CIHD mortality was 1.010 (95% CI: 1.007–1.014) for a 10-µg/m3 rise in warm-season ozone at lag-01 day, and ranged from 1.20 (95% CI: 1.15–1.25) to 1.64 (95% CI: 1.54–1.73) for heatwaves under various definitions. Stratified analyses showed intensified ozone-related CIHD risks on heatwave days compared to non-heatwave days, and higher heatwave-related risks on high-ozone days than low-ozone days. We observed significant synergistic interactive effects of heatwave and high-level ozone on CIHD mortality (SI >1), where the excess risk was elevated by 10%–19% (REOI >0) under co-exposure scenarios and 8%–11% (AP >0) of the odds could be attributed to the additive interaction. Conclusions:This study provided novel evidence for the syner

关键词： Heart

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Population simulation modeling of disparities in US breast cancer mortality

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Journal of the National cancer Institute - Monographs 2023年第62期2023卷 178-187页

作者： Mandelblatt, Jeanne S. Schechter, Clyde B. Stout, Natasha K. Huang, Hui Stein, Sarah Hunter Chapman, Christina Trentham-Dietz, Amy Jayasekera, Jinani Gangnon, Ronald E. Hampton, John M. Abraham, Linn O’Meara, Ellen S. Sheppard, Vanessa B. Lee, Sandra J. Department of Oncology Georgetown University Medical Center and Cancer Prevention and Control Program at Georgetown Lombardi Comprehensive Cancer Center WA United States Departments of Family and Social Medicine and of Epidemiology and Population Health Albert Einstein College of Medicine Bronx NY United States Department of Population Sciences Harvard Medical School and Harvard Pilgrim Health Care Institute Boston MA United States Department of Data Science Dana-Farber Cancer Institute and Harvard Medical School Boston MA United States Department of Radiation Oncology Section of Health Services Research Baylor College of Medicine and Health Policy Quality and Informatics Program at the Center for Innovations in Quality Effectiveness and Safety Michael E. DeBakey VA Medical Center Houston TX United States Department of Population Health Sciences and Carbone Cancer Center University of Wisconsin-Madison Madison WI United States Health Equity and Decision Sciences Research Lab National Institute on Minority Health and Health Disparities Intramural Research Program National Institutes of Health Bethesda MD United States Departments of Population Health Sciences and of Biostatistics and Medical Informatics and Carbone Cancer Center University of Wisconsin-Madison Madison WI United States Kaiser Permanente Washington Health Research Institute Seattle WA United States Department of Health Behavior and Policy and Massey Cancer Center Virginia Commonwealth University Richmond VA United States

BACKGROUND: Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence. METHODS: Three cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy. RESULTS: Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness. CONCLUSION: Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities. © The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: ***

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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

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NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain Department of Biostatistics School of Public Health University of Washington Seattle WA USA Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Department of Public Health Richard Doll Building University of Oxford Oxford UK Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

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Personalized Biopsy Schedules Using an Interval-censored Cause-specific Joint Model

arXiv

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arXiv 2022年

作者： Yang, Zhenwei Rizopoulos, Dimitris Heijnsdijk, Eveline A.M. Newcomb, Lisa F. Erler, Nicole S. Department of Biostatistics Erasmus Medical Center Rotterdam Netherlands Department of Epidemiology Erasmus Medical Center Rotterdam Netherlands Department of Public Health Erasmus Medical Center Rotterdam Netherlands Fred Hutchinson Cancer Center Cancer Prevention Program Public Health Sciences SeattleWA United States

Active surveillance (AS), where biopsies are conducted to detect cancer progression, has been acknowledged as an efficient way to reduce the overtreatment of prostate cancer. Most AS cohorts use fixed biopsy schedules for all patients. However, the ideal test frequency remains unknown, and the routine use of such invasive tests burdens the patients. An emerging idea is to generate personalized biopsy schedules based on each patient’s progression-specific risk. To achieve that, we propose the interval-censored cause-specific joint model (ICJM), which models the impact of longitudinal biomarkers on cancer progression while considering the competing event of early treatment initiation. The underlying likelihood function incorporates the interval-censoring of cancer progression, the competing risk of treatment, and the uncertainty about whether cancer progression occurred since the last biopsy in patients that are right-censored or experience the competing event. The model can produce patient-specific risk profiles until a horizon time. If the risk exceeds a certain threshold, a biopsy is conducted. The optimal threshold can be chosen by balancing two indicators of the biopsy schedules: the expected number of biopsies and expected delay in detection of cancer progression. A simulation study showed that our personalized schedules could considerably reduce the number of biopsies per patient by 41%-52% compared to the fixed schedules, though at the cost of a slightly longer detection delay. © 2022, CC BY-NC-ND.

关键词： Biopsy

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Embedding lifestyle interventions into cancer care: has telehealth narrowed the equity gap?

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Journal of the National cancer Institute - Monographs 2023年第61期2023卷 133-139页

作者： Dennett, Amy M Hirko, Kelly A Porter, Kathleen J Loh, Kah Poh Liao, Yue Yang, Lin Arem, Hannah Sukumar, Jasmine S Salerno, Elizabeth A Allied Health Clinical Research Office Eastern Health Bundoora VIC Australia School of Allied Health Human Services and Sport La Trobe University Bundoora VIC Australia Department of Epidemiology and Biostatistics College of Human Medicine Michigan State University East Lansing MI United States Department of Public Health Sciences School of Medicine University of Virginia Charlottesville VA United States Division of Hematology/Oncology Department of Medicine James P. Wilmot Cancer Institute Rochester NY United States Department of Kinesiology College of Nursing and Health Innovation University of Texas at Arlington Arlington TX United States Department of Cancer Epidemiology and Prevention Research Alberta Health Services Calgary Canada Departments of Oncology and Community Health Sciences Cumming School of Medicine University of Calgary Calgary Canada Healthcare Delivery Research Program MedStar Health Research Institute WA United States Department of Breast Medical Oncology University of Texas MD Anderson Cancer Center Houston TX United States Division of Public Health Sciences Department of Surgery Washington University School of Medicine St Louis MO United States

Lifestyle interventions targeting energy balance (ie, diet, exercise) are critical for optimizing the health and well-being of cancer survivors. Despite their benefits, access to these interventions is limited, especially in underserved populations, including older people, minority populations and those living in rural and remote areas. Telehealth has the potential to improve equity and increase access. This article outlines the advantages and challenges of using telehealth to support the integration of lifestyle interventions into cancer care. We describe 2 recent studies, GO-EXCAP and weSurvive, as examples of telehealth lifestyle intervention in underserved populations (older people and rural cancer survivors) and offer practical recommendations for future implementation. Innovative approaches to the use of telehealth-delivered lifestyle intervention during cancer survivorship offer great potential to reduce cancer burden. © The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: ***@***.

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Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

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EUROPEAN JOURNAL OF HUMAN GENETICS 2022年第5期30卷 630-631页

作者： Dareng, Eileen O. Tyrer, Jonathan P. Barnes, Daniel R. Jones, Michelle R. Yang, Xin Aben, Katja K. H. Adank, Muriel A. Agata, Simona Andrulis, Irene L. Anton-Culver, Hoda Antonenkova, Natalia N. Aravantinos, Gerasimos Arun, Banu K. Augustinsson, Annelie Balmana, Judith Bandera, Elisa V. Barkardottir, Rosa B. Barrowdale, Daniel Beckmann, Matthias W. Beeghly-Fadiel, Alicia Benitez, Javier Bermisheva, Marina Bernardini, Marcus Q. Bjorge, Line Black, Amanda Bogdanova, Natalia V. Bonanni, Bernardo Borg, Ake Brenton, James D. Budzilowska, Agnieszka Butzow, Ralf Buys, Saundra S. Cai, Hui Caligo, Maria A. Campbell, Ian Cannioto, Rikki Cassingham, Hayley Chang-Claude, Jenny Chanock, Stephen J. Chen, Kexin Chiew, Yoke-Eng Chung, Wendy K. Claes, Kathleen B. M. Colonna, Sarah Cook, Linda S. Couch, Fergus J. Daly, Mary B. Dao, Fanny Davies, Eleanor de la Hoya, Miguel de Putter, Robin Dennis, Joe DePersia, Allison Devilee, Peter Diez, Orland Ding, Yuan Chun Doherty, Jennifer A. Domchek, Susan M. Dork, Thilo du Bois, Andreas Durst, Matthias Eccles, Diana M. Eliassen, Heather A. Engel, Christoph Evans, Gareth D. Fasching, Peter A. Flanagan, James M. Fortner, Renee T. Machackova, Eva Friedman, Eitan Ganz, Patricia A. Garber, Judy Gensini, Francesca Giles, Graham G. Glendon, Gord Godwin, Andrew K. Goodman, Marc T. Greene, Mark H. Gronwald, Jacek Hahnen, Eric Haiman, Christopher A. Hakansson, Niclas Hamann, Ute Hansen, Thomas V. O. Harris, Holly R. Hartman, Mikael Heitz, Florian Hildebrandt, Michelle A. T. Hogdall, Estrid Hogdall, Claus K. Hopper, John L. Huang, Ruea-Yea Huff, Chad Hulick, Peter J. Huntsman, David G. Imyanitov, Evgeny N. Isaacs, Claudine Jakubowska, Anna James, Paul A. Janavicius, Ramunas Jensen, Allan Johannsson, Oskar Th. John, Esther M. Jones, Michael E. Kang, Daehee Karlan, Beth Y. Karnezis, Anthony Kelemen, Linda E. Khusnutdinova, Elza Kiemeney, Lambertus A. Kim, Byoung-Gie Kjaer, Susanne K. Komenaka, Ian Kupryjanczyk, Jolanta Kurian, Allison W. Kwong, Ava Lambrechts, Diether Larson, Melissa C. Lazaro, Conxi L University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands The Netherlands Cancer Institute—Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands Veneto Institute of Oncology IOV—IRCCS Immunology and Molecular Oncology Unit Padua Italy Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada University of Toronto Department of Molecular Genetics Toronto ON Canada University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus ‘Agii Anargiri’ Cancer Hospital Athens Greece University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden Vall d’Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain University Hospital of Vall d’Hebron Department of Medical Oncology Barcelona Spain Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA Landspitali University Hospital Department of Pathology Reykjavik Iceland University of Iceland BMC (Biomedical Centre) Faculty of Medicine Reykjavik Iceland University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nuremberg Department of Gynecology and Obstetrics Comprehensive Cancer Center ER-EMN Erlangen Germany Vanderbilt University School of Medicine Division of Epidemiology Department

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

关键词： Clinical genetics Genetic markers Risk factors Biomedicine general Human Genetics Bioinformatics Gene Expression Cytogenetics

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Incidence, risk factors, and mortality of atrial fibrillation in breast cancer: a SEER-Medicare analysis (vol 43, pg 300, 2022)

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EUROPEAN HEART JOURNAL 2022年第21期43卷 2019-2019页

作者： Guha, Avirup Department of Medicine Case Western Reserve University 11100 Euclid Ave Cleveland OH 44106 USA Cardio-Oncology Program Division of Cardiology The Ohio State University Medical Center 452 W. 10th Ave. Columbus OH 43210 USA Department of Medicine Division of Cardiology and Vascular Biology Center Medical College of Georgia at Augusta University 1460 Laney Walker Blvd Augusta GA 30912 USA Cardio-Oncology Program Division of Cardiology Department of Internal Medicine University of Pennsylvania 3400 Civic Center Boulevard Philadelphia PA 19104 USA Duke Cancer Institute Duke University 2 Seeley Mudd 10 Bryan Searle Drive Durham NC 27710 USA Breast Cancer Center Smilow Cancer Hospital Yale University 35 Park St New Haven CT 06511 USA Department of Epidemiology Rollins School of Public Health Emory University 1518 Clifton Rd Atlanta GA 30322 USA Division of Cancer Prevention and Control Department of Internal Medicine College of Medicine The Ohio State University 1590 N High St Suite 525 Columbus OH 43201 USA

Aims The national incidence, risk factors, and associated mortality of atrial fibrillation (AF) in breast cancer patients are unknown. Methods and results Using the Surveillance, epidemiology, and End Results-Medicare-linked database, we identified females, ≥66 years old, with a new primary diagnosis of breast cancer from 2007 through 2014. These patients were individually matched 1:1 to Medicare enrolees without cancer, and each pair was followed for 1 year to identify a primary outcome of AF. Cumulative incidence was calculated using competing risk survival statistics. Following this, identifying risk factors of AF among breast cancer patients was conducted using the adjusted Cox proportional hazards model. Finally, Kaplan–Meier methods and adjusted Cox proportional hazards modelling were performed to estimate mortality in breast cancer patients with incident and prevalent AF. This study included 85 423 breast cancer patients. Among these 9425 (11.0%) had AF diagnosis prior to the breast cancer diagnosis. New-onset AF was diagnosed in 2993 (3.9%) patients in a 1-year period after the breast cancer diagnosis [incidence 3.3%, 95% confidence interval (CI) 3.0–3.5%, at 1 year; higher rate in the first 60 days (0.6%/month)]. Comparatively, the incidence of new-onset AF in matched non-cancer controls was 1.8% (95% CI 1.6–2.0%). Apart from traditional demographic and cardiovascular risk factors, breast cancer stage was strongly associated with the development of AF [American Joint Committee on cancer (AJCC) Stage II/III/IV vs. I: adjusted hazard ratio (aHR) 1.51/2.63/4.21, respectively]. New-onset AF after breast cancer diagnosis (aHR 3.00) is associated with increased 1-year cardiovascular mortality. Conclusion AF incidence is significantly higher in women after a breast cancer diagnosis. Higher breast cancer stages at diagnos are significantly associated with a higher risk of AF. New-onset AF in the new breast cancer diagnosis setting increases 1-year cardiovascular mo

关键词： Atrial fibrillation Breast cancer Incidence Risk factors Mortality SEER-Medicare

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Data gaps and opportunities for modeling cancer health equity

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Journal of the National cancer Institute - Monographs 2023年第62期2023卷 246-254页

作者： Trentham-Dietz, Amy Corley, Douglas A. Del Vecchio, Natalie J. Greenlee, Robert T. Haas, Jennifer S. Hubbard, Rebecca A. Hughes, Amy E. Kim, Jane J. Kobrin, Sarah Li, Christopher I. Meza, Rafael Neslund-Dudas, Christine M. Tiro, Jasmin A. Department of Population Health Sciences and Carbone Cancer Center School of Medicine and Public Health University of Wisconsin-Madison Madison WI United States Division of Research Kaiser Permanente Northern California Oakland CA United States Division of Public Health Sciences Fred Hutchinson Cancer Research Center Seattle WA United States Marshfield Clinic Research Institute Marshfield WI United States Division of General Internal Medicine Massachusetts General Hospital Boston MA United States Department of Biostatistics Epidemiology and Informatics Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Department of Population and Data Sciences University of Texas Southwestern Medical Center Dallas TX United States Department of Health Policy and Management Center for Health Decision Science Harvard T.H. Chan School of Public Health Boston MA United States Healthcare Delivery Research Program Division of Cancer Control & Population Sciences National Cancer Institute National Institutes of Health Rockville MD United States Department of Integrative Oncology British Columbia (BC) Cancer Research Institute Vancouver BC Canada Department of Public Health Sciences and Henry Ford Cancer Henry Ford Health Detroit MI United States Department of Public Health Sciences University of Chicago Biological Sciences Division University of Chicago Medicine Comprehensive Cancer Center Chicago IL United States

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change. © The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: ***@***.

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Disparities in Psychological Distress and Coping Behaviors Amongst Patients with Indolent Hematologic Malignancies

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Blood 2024年 144卷 3739-3739页

作者： Tammarah Sklarz Jill S Hasler Carolyn Y. Fang Zachary AK Frosch Department of Hematology/Oncology Fox Chase Cancer Center Philadelphia PA Biostatistics and Bioinformatics Facility Fox Chase Cancer Center Philadelphia PA Cancer Prevention and Control Research Program Fox Chase Cancer Center Temple University Health System Philadelphia PA Department of Hematology/Oncology； Cancer Prevention and Control Research Program Fox Chase Cancer Center Philadelphia PA

Introduction : Patients with indolent blood cancers often do not have an indication for treatment at diagnosis and are recommended to undergo observation as the initial management strategy. This strategy may lead to psychological distress which is associated with decreased cancer-specific survival. In the US, there are significant racial disparities in survival for patients diagnosed with blood cancers, yet less is known about the basis for these differences. One potential contributor to disparities in survival is the differential impact of mental health comorbidities given that racial minorities living in the US disproportionately experience more psychosocial stress. The aims of this study are to evaluate for racial disparities in the level of cancer-related stress experienced by patients undergoing active observation for indolent blood cancers and to contrast coping strategy use by race. Methods : This study employs use of existing data from a prospective observational research study where participants with indolent blood cancers managed by observation were asked to complete measures regarding sociodemographic background, health behaviors, cancer-specific stress, and psychological adjustment to cancer. Participants were enrolled from April 2016 to November 2020 and measures were obtained at study entry. Patients with chronic lymphocytic leukemia, follicular lymphoma, smoldering myeloma, and a B-cell lymphoma not otherwise specified were included. Race/ethnicity was defined into several categories: African American/Black, Asian, White, more than one race/other or Hispanic. For study comparison, patients were grouped into racially minoritized (Asian, Black or Hispanic/Latinx) and non-minoritized (White non-Hispanic) arms. cancer-specific stress was assessed using the Revised Impact of Events Scale (RIES). Psychological adjustment to cancer was assessed using the Mental Adjustment to cancer (MAC) scale which measures several types of coping responses. Patient health

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