Commentary: Reporting standards are needed for evaluations of risk reclassification.

New approaches have been developed in recent years to quantify the improvement in prediction performance gained by adding a novel marker to a set of baseline predictors of risk. The paper by Tzoulaki et al. concerns risk reclassification techniques and focuses specifically on the net reclassification improvement (NRI) index. Their review shows that use of risk reclassification analysis is extremely common in practice, with 51 papers using the technique published in only 3 years since its introduction. Unfortunately and alarmingly, the review shows that the quality of reporting is dismal. Investigators seem confused about the roles and interpretations of risk reclassification metrics. Guidance on how to report results of risk reclassification analysis would be helpful to authors, reviewers and the field in general. The risk reclassification table was first introduced by Cook. The table is constructed by choosing clinically meaningful risk categories and cross-classifying individuals according to their risks calculated with the baseline risk model and with the expanded risk model. The top panel of Table 1 provides an illustration. Cook and Ridker developed a whole analysis strategy around the risk reclassification table including new hypothesis tests and a new metric called ‘percent correct reclassification’. However, the value of these analysis techniques is doubtful and results can be misleading. Pencina et al. argued that the reclassification table itself was problematic, at least as proposed by Cook, because it did not distinguish between subjects with events (cases) and subjects without events (controls). They suggested constructing separate event and non-event reclassification tables as shown in the middle and bottom panels of Table 1. Entries above the diagonal correspond to risks that are higher with the expanded vs baseline model, representing improved prediction for subjects with events. Correspondingly, entries below the diagonal represent worse prediction for them. The event-NRI is the difference between the proportions of subjects above vs below the diagonal in the event reclassification table. Using a similar logic, the non-event-NRI is calculated from the non-event reclassification table by taking the difference between the proportions of subjects below vs above the diagonal. The NRI summary index that gained immediate popularity in the literature following Pencina’s paper is the sum,