BIOPSY OR SHORT INTERVAL FOLLOW-UP? A MARKOV DECISION PROCESS MODEL FOR EARLY DIAGNOSIS OF BREAST CANCER

Purpose: A 2% threshold has traditionally being used for biopsy recommendation based on the available literature without taking into consideration patient characteristics. Our objective was to create a personalized sequential decision model that determines whether to recommend: biopsy, short interval imaging follow-up, or routine annual mammography based on patient's current breast cancer risk.

Methods: We constructed a mathematical model using Markov Decision Processes (MDP), a decision-analytical tool used for sequential decision making under uncertainty, which maximizes a patient's total quality-adjusted expected life years (QALYs). Our MDP model provides the optimal recommendations that are based on patients' probability of breast cancer, estimated from demographic risk factors (age, family history, and hormone use) and mammographic findings (using BI-RADS) using a logistic regression (LR) model. Both the LR and MDP model were constructed using data from literature and prospectively collected 48,744 consecutive mammograms from a breast imaging practice between 1999-2004. We checked the robustness of the MDP model by performing sensitivity analyses on its parameters.

Results: The MDP model provides optimal decision rules (policy) that maximize patients' total QALYs. Our preliminary results are shown in the figure below. For example, the optimal decision rule for a 42-year old woman would be: follow-up and biopsy, if her risk of breast cancer is above 1% and 2%, respectively; otherwise, wait until next annual mammogram. . For an 82-year old woman, the thresholds to recommend follow-up and biopsy increase to 2% and 4%, respectively. Our model recommended a higher biopsy threshold for older patients suggesting less aggressive management in older women.

Conclusions: Given a patient's mammographic features and demographic risk factors, our model provides a threshold for biopsy, short interval follow-up, or annual mammography that maximizes QALYs in order to personalize these decision thresholds.