학술논문
BMI and breast cancer risk around age at menopause.
Document Type
Academic Journal
Author
Von Holle A; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.; Adami HO; Clinical Effectiveness Group, Institute of Health and Society, University of Oslo, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinksa Institutet, Stockholm, Sweden.; Baglietto L; Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.; Berrington de Gonzalez A; Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.; Bertrand KA; Slone Epidemiology Center, Boston University, Boston, MA, USA.; Blot W; Vanderbilt University Medical Center, Nashville, TN, USA.; Chen Y; Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.; DeHart JC; School of Community and Global Health, Claremont Graduate University, Claremont, CA, USA.; Dossus L; Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.; Eliassen AH; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.; Fournier A; Centre for Research in Epidemiology and Statistics, Paris, France.; Garcia-Closas M; Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.; Giles G; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Guevara M; Instituto de Salud Pública y Laboral de Navarra, Pamplona, Spain.; Hankinson SE; Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA.; Heath A; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Jones ME; Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.; Joshu CE; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Kaaks R; Division of Cancer Epidemiology, German Cancer Research Center, DKFZ, Heidelberg, Germany.; Kirsh VA; Ontario Institute for Cancer Research, Toronto, ON, Canada.; Kitahara CM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.; Koh WP; Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore.; Linet MS; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.; Park HL; Department of Pathology and Laboratory Medicine, Department of Epidemiology, UC Irvine School of Medicine, Irvine, CA, USA.; Masala G; Institute for the Study and Prevention of Cancer, Florence, Italy.; Mellemkjaer L; Diet, Cancer and Health, Danish Cancer Institute, Copenhagen, Denmark.; Milne RL; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.; O'Brien KM; Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.; Palmer JR; Slone Epidemiology Center, Boston University, Boston, MA, USA.; Riboli E; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Rohan TE; Albert Einstein College of Medicine, Bronx, NY, USA.; Shrubsole MJ; Vanderbilt University Medical Center, Nashville, TN, USA.; Sund M; Department of Surgical and perioperative Sciences/Surgery, Umea University, Sweden.; Tamimi R; Department of Population Health Sciences, Weill Cornell Medical College, NY, USA.; Tin Tin S; Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, United Kingdom.; Visvanathan K; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Vermeulen RC; Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.; Weiderpass E; International Agency for Research on Cancer, World Health Organization, Lyon, France.; Willett WC; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Yuan JM; Division of Cancer Control and Population Science, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, PA, USA; Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.; Zeleniuch-Jacquotte A; Department of Population Health, NYU Grossman School of Medicine, NY, USA.; Nichols HB; Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA.; Sandler DP; Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.; Swerdlow AJ; Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom; Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom.; Schoemaker MJ; Real World Solutions, IQVIA, the Netherlands.; Weinberg CR; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA. Electronic address: weinberg@niehs.nih.gov.
Source
Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101508793 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1877-783X (Electronic) Linking ISSN: 18777821 NLM ISO Abbreviation: Cancer Epidemiol Subsets: MEDLINE
Subject
Language
English
Abstract
Background: A high body mass index (BMI, kg/m 2 ) is associated with decreased risk of breast cancer before menopause, but increased risk after menopause. Exactly when this reversal occurs in relation to menopause is unclear. Locating that change point could provide insight into the role of adiposity in breast cancer etiology.
Methods: We examined the association between BMI and breast cancer risk in the Premenopausal Breast Cancer Collaborative Group, from age 45 up to breast cancer diagnosis, loss to follow-up, death, or age 55, whichever came first. Analyses included 609,880 women in 16 prospective studies, including 9956 who developed breast cancer before age 55. We fitted three BMI hazard ratio (HR) models over age-time: constant, linear, or nonlinear (via splines), applying piecewise exponential additive mixed models, with age as the primary time scale. We divided person-time into four strata: premenopause; postmenopause due to natural menopause; postmenopause because of interventional loss of ovarian function (bilateral oophorectomy (BO) or chemotherapy); postmenopause due to hysterectomy without BO. Sensitivity analyses included stratifying by BMI in young adulthood, or excluding women using menopausal hormone therapy.
Results: The constant BMI HR model provided the best fit for all four menopausal status groups. Under this model, the estimated association between a five-unit increment in BMI and breast cancer risk was HR=0.87 (95% CI: 0.85, 0.89) before menopause, HR=1.00 (95% CI: 0.96, 1.04) after natural menopause, HR=0.99 (95% CI: 0.93, 1.05) after interventional loss of ovarian function, and HR=0.88 (95% CI: 0.76, 1.02) after hysterectomy without BO.
Conclusion: The BMI breast cancer HRs remained less than or near one during the 45-55 year age range indicating that the transition to a positive association between BMI and risk occurs after age 55.
Competing Interests: Declaration of Competing Interest none.
(Published by Elsevier Ltd.)
Methods: We examined the association between BMI and breast cancer risk in the Premenopausal Breast Cancer Collaborative Group, from age 45 up to breast cancer diagnosis, loss to follow-up, death, or age 55, whichever came first. Analyses included 609,880 women in 16 prospective studies, including 9956 who developed breast cancer before age 55. We fitted three BMI hazard ratio (HR) models over age-time: constant, linear, or nonlinear (via splines), applying piecewise exponential additive mixed models, with age as the primary time scale. We divided person-time into four strata: premenopause; postmenopause due to natural menopause; postmenopause because of interventional loss of ovarian function (bilateral oophorectomy (BO) or chemotherapy); postmenopause due to hysterectomy without BO. Sensitivity analyses included stratifying by BMI in young adulthood, or excluding women using menopausal hormone therapy.
Results: The constant BMI HR model provided the best fit for all four menopausal status groups. Under this model, the estimated association between a five-unit increment in BMI and breast cancer risk was HR=0.87 (95% CI: 0.85, 0.89) before menopause, HR=1.00 (95% CI: 0.96, 1.04) after natural menopause, HR=0.99 (95% CI: 0.93, 1.05) after interventional loss of ovarian function, and HR=0.88 (95% CI: 0.76, 1.02) after hysterectomy without BO.
Conclusion: The BMI breast cancer HRs remained less than or near one during the 45-55 year age range indicating that the transition to a positive association between BMI and risk occurs after age 55.
Competing Interests: Declaration of Competing Interest none.
(Published by Elsevier Ltd.)