Adaptive decision-making of breast cancer mammography screening: A heuristic-based regression model

The American Cancer Society (ACS) updated their breast cancer screening guidelines in late 2015 and recommends that all women have the choice to start annual mammography screenings beginning at age 40. For women ages 45-54, the ACS explicitly recommends annual mammograms. However, due to the potential harms associated with screening mammography, such as overdiagnosis and unnecessary work-ups, the best strategy to design an appropriate breast cancer mammography screening schedule remains controversial. Instead of recommending a one-size-fits-all screening schedule, this study identifies a personalized mammography screening strategy adaptive to each woman's age-specific breast cancer risk. We present a two-stage decision framework: (1) age-specific breast cancer risk estimation and (2) annual mammography screening decision-making based on estimated risk. The results suggest that the optimal combinations of independent variables used in risk estimation are not the same across age groups. Our optimal decision models outperform the existing mammography screening guidelines in terms of the average loss of life expectancy. While most earlier studies improved the breast cancer screening decisions by offering lifetime screening schedules, our proposed model provides an adaptive screening decision aid by age. Since whether or not a woman should receive a mammogram is determined based on her breast cancer risk at her current age, our "on-line" screening policy adapts to a woman's latest health status, which reflects the current individual risk of each woman more accurately. (C) 2017 Elsevier Ltd. All rights reserved.