Abstract
An important aspect of modern cancer research is identifying molecular and genetic markers that predict an individual's risk of recurrence and response to treatment. Increasingly, a large number of biomarkers are included in studies, even though at most a small proportion of them will be prognostic. This article considers the selection and validation of prognostic biomarkers, and proposes a method for building and validating a prognostic index based on potentially many markers. We use simulation to show that our proposed method controls false-positive rate while retaining reasonable power. The prognostic index gets its power from combining prognostic biomarkers. It can be very powerful even when there are few markers that are predictive.