Mammographic density and risk of breast cancer by tumor characteristics: a case-control study

BMC Cancer

Research Article

Kavitha Krishnan¹  Dallas R. English²  Graham G. Giles³  Laura Baglietto⁴  Jennifer Stone⁵  John L. Hopper⁶  Melissa C. Southey⁷  Catriona McLean⁸ 

[1] Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia;Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia;Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France;Gustave Roussy, F-94805, Villejuif, France;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Centre for Genetic Origins of Health and Disease, University of Western Australia, Perth, Australia;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, 3053, Carlton, VIC, Australia;Seoul Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea;Institute of Health and Environment, Seoul National University, Seoul, South Korea;Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Melbourne, Australia;The Alfred Hospital, Melbourne, Australia;

关键词: Mammographic density;    Breast cancer;    Detection mode;    Tumor characteristics;   

DOI  :  10.1186/s12885-017-3871-7

 received in 2016-11-06, accepted in 2017-12-04,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundIn a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection.MethodsWe conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis.ResultsFor screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor.ConclusionsBoth DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis, such as larger and node positive tumours, is intrinsically associated with increased mammographic density and not through delay of diagnosis due to masking.

【 授权许可】

CC BY   
© The Author(s). 2017