Assessing Dynamic Breast Cancer Screening Policies

Questions regarding the relative value and frequency of mammography screening for premenopausal women versus postmenopausal women remain open due to the conflicting age–based dynamics of both the disease (increasing incidence, decreasing aggression) and the accuracy of the test results (increasing sensitivity and specificity). To investigate these questions, we formulate a partially observed Markov chain model that captures several of these age–based dynamics not previously considered simultaneously. Using sample–path enumeration, we evaluate a broad range of policies to generate the set of ‘efficient’ policies, as measured by a lifetime breast cancer mortality risk metric and an expected mammogram count, from which a patient may select a policy based on individual circumstance. We demonstrate robustness with respect to small changes in the input data and conclude that, in general, to efficiently achieve a lifetime risk comparable to the current risk among U.S. women, screening should start relatively early in life and continue relatively late in life regardless of the screening interval(s) adopted. The frontier also exhibits interesting patterns with respect to policy type, where policy type is defined by the relationship between the screening interval prescribed in younger years and that prescribed later in life.