Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study

Abstract

Objectives To develop a breast cancer risk prediction model for Chamorro and Filipino women of the Mariana Islands and compare its performance to that of the Breast Cancer Risk Assessment Tool (BCRAT).Design Case–control study.Setting Clinics/facilities and other community-based settings on Guam and Saipan (Northern Mariana Islands).Participants 245 women (87 breast cancer cases and 158 controls) of Chamorro or Filipino ethnicity, age 25–80 years, with no prior history of cancer (other than skin cancer), residing on Guam or Saipan for at least 5 years.Primary and secondary outcome measures Breast cancer risk models were constructed using combinations of exposures previously identified to affect breast cancer risk in this population, population breast cancer incidence rates and all-cause mortality rates for Guam.Results Models using ethnic-specific relative risks performed better than those with relative risks estimated from all women. The model with the best performance among both ethnicities (the Breast Cancer Risk Model (BRISK) model; area under the receiver operating characteristic curve (AUC): 0.64 and 0.67 among Chamorros and Filipinos, respectively) included age at menarche, age at first live birth, number of relatives with breast cancer and waist circumference. The 10-year breast cancer risk predicted by the BRISK model was 1.28% for Chamorros and 0.89% for Filipinos. Performance of the BCRAT was modest among both Chamorros (AUC: 0.60) and Filipinos (AUC: 0.55), possibly due to incomplete information on BCRAT risk factors.Conclusions The ability to develop breast cancer risk models for Mariana Islands women is constrained by the small population size and limited availability of health services and data. Nonetheless, we have demonstrated that breast cancer risk prediction models with adequate discriminatory performance can be built for small populations such as in the Mariana Islands. Anthropometry, in particular waist circumference, was important for estimating breast cancer risk in this population.