Literature DB >> 9583712

Population attributable fraction estimation for established breast cancer risk factors: considering the issues of high prevalence and unmodifiability.

B Rockhill1, C R Weinberg, B Newman.   

Abstract

Established breast cancer risk factors, in addition to being relatively unmodifiable, are highly prevalent among US women. Previous reports of population attributable fraction for the established risk factors have used definitions that resulted in 75-100% of women in the source population labeled exposed. The practical value of such estimates has not been discussed; further, the estimates have frequently been misinterpreted. In the context of examining the interpretation and public health value of such estimates, the authors demonstrate the sensitivity of the population attributable fraction to changes in exposure cutpoints. They use data from the Carolina Breast Cancer Study, a case-control study of breast cancer conducted in North Carolina between 1993 and 1996. For the four established risk factors (menarche before age 14 years, first birth at age 20 years or later/nulliparity, family history of breast cancer, and history of benign breast biopsy), the estimated population attributable fraction was 0.25 (95% confidence interval 0.06-0.48). Over 98% of the source population was exposed to at least one of these risk factors. The population attributable fraction estimate was reduced to 0.15 when more restrictive definitions of early menarche (less than age 12 years) and late age at first full-term pregnancy (30 years or more) were used (proportion exposed, 0.62). Population attributable fractions for established breast cancer risk factors probably have little public health value because of both the high proportions exposed and the relative unmodifiability of the risk factor distributions.

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Year:  1998        PMID: 9583712     DOI: 10.1093/oxfordjournals.aje.a009535

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  36 in total

1.  A heuristic approach to the formulas for population attributable fraction.

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Journal:  J Epidemiol Community Health       Date:  2001-07       Impact factor: 3.710

2.  The relation between projected breast cancer risk, perceived cancer risk, and mammography use. Results from the National Health Interview Survey.

Authors:  C P Gross; G Filardo; H S Singh; A N Freedman; M H Farrell
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Review 3.  Interaction between APC and Fen1 during breast carcinogenesis.

Authors:  Satya Narayan; Aruna S Jaiswal; Brian K Law; Mohammad A Kamal; Arun K Sharma; Robert A Hromas
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4.  Impact of the 2009 influenza pandemic on pneumococcal pneumonia hospitalizations in the United States.

Authors:  Daniel M Weinberger; Lone Simonsen; Richard Jordan; Claudia Steiner; Mark Miller; Cécile Viboud
Journal:  J Infect Dis       Date:  2011-12-07       Impact factor: 5.226

Review 5.  Breast cancer among immigrants: a systematic review and new research directions.

Authors:  Valentina A Andreeva; Jennifer B Unger; Mary Ann Pentz
Journal:  J Immigr Minor Health       Date:  2007-10

6.  Epidemiology of basal-like breast cancer.

Authors:  Robert C Millikan; Beth Newman; Chiu-Kit Tse; Patricia G Moorman; Kathleen Conway; Lynn G Dressler; Lisa V Smith; Miriam H Labbok; Joseph Geradts; Jeannette T Bensen; Susan Jackson; Sarah Nyante; Chad Livasy; Lisa Carey; H Shelton Earp; Charles M Perou
Journal:  Breast Cancer Res Treat       Date:  2007-06-20       Impact factor: 4.872

Review 7.  The normal and malignant mammary gland: a fresh look with ER beta onboard.

Authors:  M Warner; S Saji; J A Gustafsson
Journal:  J Mammary Gland Biol Neoplasia       Date:  2000-07       Impact factor: 2.673

8.  Exposure to phthalates and breast cancer risk in northern Mexico.

Authors:  Lizbeth López-Carrillo; Raúl U Hernández-Ramírez; Antonia M Calafat; Luisa Torres-Sánchez; Marcia Galván-Portillo; Larry L Needham; Rubén Ruiz-Ramos; Mariano E Cebrián
Journal:  Environ Health Perspect       Date:  2010-04       Impact factor: 9.031

9.  The role of conventional risk factors in explaining social inequalities in coronary heart disease: the relative and absolute approaches to risk.

Authors:  Archana Singh-Manoux; Hermann Nabi; Martin Shipley; Alice Guéguen; Séverine Sabia; Aline Dugravot; Michael Marmot; Mika Kivimaki
Journal:  Epidemiology       Date:  2008-07       Impact factor: 4.822

10.  Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity.

Authors:  Prithvi Raj; Ekta Rai; Ran Song; Shaheen Khan; Benjamin E Wakeland; Kasthuribai Viswanathan; Carlos Arana; Chaoying Liang; Bo Zhang; Igor Dozmorov; Ferdicia Carr-Johnson; Mitja Mitrovic; Graham B Wiley; Jennifer A Kelly; Bernard R Lauwerys; Nancy J Olsen; Chris Cotsapas; Christine K Garcia; Carol A Wise; John B Harley; Swapan K Nath; Judith A James; Chaim O Jacob; Betty P Tsao; Chandrashekhar Pasare; David R Karp; Quan Zhen Li; Patrick M Gaffney; Edward K Wakeland
Journal:  Elife       Date:  2016-02-15       Impact factor: 8.140

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