Cut-off estimation and medical decision making based on a continuous prognostic factor: the prediction of kidney graft failure.

The determination of a cut-off value for a continuous prognostic test is an important problem, which is statistically challenging and practically important for risk assessment. We propose in this paper a method to estimate the optimal cut-off from this type of longitudinal data with censored failure times. The principle is to combine the prognostic error rates of false positives and false negatives with a cost function, which has the advantages to be statistically convenient and to be directly associated with the decision-making. Simulations were performed and the results demonstrate the interest of our approach compared to a reference method. The method is also illustrated by predicting the long-term survival of kidney transplant recipients from the 1-year creatinine clearance.