The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
IMPACT FACTOR 2017: 0.840
5-year IMPACT FACTOR: 1.000
CiteScore 2017: 0.97
SCImago Journal Rank (SJR) 2017: 1.150
Source Normalized Impact per Paper (SNIP) 2017: 1.022
Mathematical Citation Quotient (MCQ) 2016: 0.09
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.