This chapter describes and critiques methods for evaluating the performance of markers to predict risk of a current or future clinical outcome. We consider three criteria that are important for evaluating a risk model: calibration, benefit for decision making and accurate classification. We also describe and discuss a variety of summary measures in common use for quantifying predictive information such as the area under the ROC curve and R-squared. The roles and problems with recently proposed risk reclassification approaches are discussed in detail.
Pepe, Margaret and Janes, Holly, "Methods for Evaluating Prediction Performance of Biomarkers and Tests" (October 2012). UW Biostatistics Working Paper Series. Working Paper 384.