Markers for treatment selection are being developed in many areas of medicine. Technological advances are rapidly producing an abundance of candidates for study. Clinicians hope to use these markers to identify which individuals will benefit from a given treatment, with the goal of maximizing good outcomes and minimizing side effects, treatment burden, and medical costs.It is essential that we have appropriate methods for evaluating treatment selection markers, in order to make informed decisions regarding marker advancement and, ultimately, clinical application. However, existing statistical methods for evaluating treatment selection markers are largely inadequate. This paper proposes several novel statistical measures of marker performance aimed at addressing key questions in marker evaluation: 1) Does the marker help patients choose amongst treatment options?; 2) How should treatment decisions be made based on a continuous marker measurement?; 3) What is the impact on the population of using the marker to select treatment?; and 4) What proportion of patients will have different treatment recommendations following marker measurement? The proposed approach is contrasted with existing methods for marker evaluation, including assessing a marker’s prognostic value, evaluating treatment effects in a subset of the population who are marker-positive, and testing for a statistical interaction between marker value and treatment. The approach is illustrated in the context of choosing adjuvant chemotherapy treatment for women with estrogen-receptor positive and node-positive breast cancer. The results have important implications for the design of marker evaluation studies, and can serve as the basis for further development of standards for assessing treatment selection markers.
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