BACKGROUND: Biological distinctions between histologic subtypes of breast cancer suggest etiologic differences, although few studies have been powered to examine such differences. We compared associations between several factors and risk of ductal, lobular, and mixed ductal-lobular breast cancers. METHODS: We used risk factor data from the Breast Cancer Surveillance Consortium for 3,331,744 mammograms on 1,211,238 women, including 19,119 women diagnosed with invasive breast cancer following mammography (n = 14,818 ductal, 1,602 lobular, and 1,601 mixed ductal-lobular). Histologic subtype-specific risk factor associations were evaluated using Cox regression. RESULTS: Significant positive associations with family history and breast density were similar across subtypes. Hormone therapy use was associated with increased risk of all subtypes, but was most strongly associated with lobular cancer [hazard ratio (HR) = 1.46; 95% confidence interval (CI), 1.25-1.70]. Relative to nulliparous women, parous women had lower risk of ductal and mixed but not lobular cancers (HR = 0.80; 95% CI, 0.76-0.84; HR = 0.79; 95% CI, 0.68-0.93; HR = 0.96; 95% CI, 0.81-1.15, respectively). Late age at first birth was associated with increased risk of all subtypes. CONCLUSIONS: Similarities in risk factor associations with ductal, lobular, and mixed breast cancer subtypes were more pronounced than differences. Distinctions between subtype-specific associations were limited to analyses of hormone therapy use and reproductive history. IMPACT: The results of this study indicate that the strongest risk factors for breast cancer overall (that is, family history and breast density) are not histologic subtype specific. Additional studies are needed to better characterize subtype-specific associations with genetic, hormonal, and nonhormonal factors. Copyright 2010 AACR.
BACKGROUND: Biological distinctions between histologic subtypes of breast cancer suggest etiologic differences, although few studies have been powered to examine such differences. We compared associations between several factors and risk of ductal, lobular, and mixed ductal-lobular breast cancers. METHODS: We used risk factor data from the Breast Cancer Surveillance Consortium for 3,331,744 mammograms on 1,211,238 women, including 19,119 women diagnosed with invasive breast cancer following mammography (n = 14,818 ductal, 1,602 lobular, and 1,601 mixed ductal-lobular). Histologic subtype-specific risk factor associations were evaluated using Cox regression. RESULTS: Significant positive associations with family history and breast density were similar across subtypes. Hormone therapy use was associated with increased risk of all subtypes, but was most strongly associated with lobular cancer [hazard ratio (HR) = 1.46; 95% confidence interval (CI), 1.25-1.70]. Relative to nulliparous women, parous women had lower risk of ductal and mixed but not lobular cancers (HR = 0.80; 95% CI, 0.76-0.84; HR = 0.79; 95% CI, 0.68-0.93; HR = 0.96; 95% CI, 0.81-1.15, respectively). Late age at first birth was associated with increased risk of all subtypes. CONCLUSIONS: Similarities in risk factor associations with ductal, lobular, and mixed breast cancer subtypes were more pronounced than differences. Distinctions between subtype-specific associations were limited to analyses of hormone therapy use and reproductive history. IMPACT: The results of this study indicate that the strongest risk factors for breast cancer overall (that is, family history and breast density) are not histologic subtype specific. Additional studies are needed to better characterize subtype-specific associations with genetic, hormonal, and nonhormonal factors. Copyright 2010 AACR.
Authors: Louise A Brinton; Douglas Richesson; Michael F Leitzmann; Gretchen L Gierach; Arthur Schatzkin; Traci Mouw; Albert R Hollenbeck; James V Lacey Journal: Cancer Epidemiol Biomarkers Prev Date: 2008-11 Impact factor: 4.254
Authors: Elisabeth F Beaber; Victoria L Holt; Kathleen E Malone; Peggy L Porter; Janet R Daling; Christopher I Li Journal: Cancer Epidemiol Biomarkers Prev Date: 2008-12 Impact factor: 4.254
Authors: Eugenia E Calle; Heather Spencer Feigelson; Janet S Hildebrand; Lauren R Teras; Michael J Thun; Carmen Rodriguez Journal: Cancer Date: 2009-03-01 Impact factor: 6.860
Authors: Marco Macchini; Martina Ponziani; Andrea Prochowski Iamurri; Mirco Pistelli; Mariagrazia De Lisa; Rossana Berardi; Gian Marco Giuseppetti Journal: Radiol Med Date: 2018-06-05 Impact factor: 3.469
Authors: Lusine Yaghjyan; Rulla M Tamimi; Kimberly A Bertrand; Christopher G Scott; Matthew R Jensen; V Shane Pankratz; Kathy Brandt; Daniel Visscher; Aaron Norman; Fergus Couch; John Shepherd; Bo Fan; Yunn-Yi Chen; Lin Ma; Andrew H Beck; Steven R Cummings; Karla Kerlikowske; Celine M Vachon Journal: Breast Cancer Res Treat Date: 2017-06-17 Impact factor: 4.872
Authors: Lindsay A Williams; Hazel B Nichols; Katherine A Hoadley; Chiu Kit Tse; Joseph Geradts; Mary Elizabeth Bell; Charles M Perou; Michael I Love; Andrew F Olshan; Melissa A Troester Journal: Cancer Causes Control Date: 2017-11-09 Impact factor: 2.506
Authors: Lindsay A Williams; Jun J Yang; Betsy A Hirsch; Erin L Marcotte; Logan G Spector Journal: Cancer Epidemiol Biomarkers Prev Date: 2019-02-15 Impact factor: 4.254
Authors: Bar Chikman; Tima Davidson; Hasan Kais; Igor Jeroukhimov; Ari Leshno; Judith Sandbank; Ariel Halevy; Ron Lavy Journal: Fam Cancer Date: 2016-01 Impact factor: 2.375
Authors: Lusine Yaghjyan; Graham A Colditz; Laura C Collins; Stuart J Schnitt; Bernard Rosner; Celine Vachon; Rulla M Tamimi Journal: J Natl Cancer Inst Date: 2011-07-27 Impact factor: 13.506
Authors: Polly A Newcomb; Amy Trentham-Dietz; John M Hampton; Kathleen M Egan; Linda Titus-Ernstoff; Shaneda Warren Andersen; E Robert Greenberg; Walter C Willett Journal: Cancer Date: 2010-11-10 Impact factor: 6.860
Authors: Louise A Brinton; Llewellyn Smith; Gretchen L Gierach; Ruth M Pfeiffer; Sarah J Nyante; Mark E Sherman; Yikyung Park; Albert R Hollenbeck; Cher M Dallal Journal: Cancer Causes Control Date: 2014-05-09 Impact factor: 2.506