Categorization is a crucial step for clinical decision making when dealing with diagnostic (or prognostic) biomarkers. We extend the use of three cut-point finding methods widely used in the absence of censoring, i.e., Youden index, concordance probability and point closest to-(0,1) corner in the ROC plane, to the case of censored failure time outcome. Further, we investigate the performance of the three methods by a simulation protocol. A motivating application of cut-point finding of a molecular biomarker in acute lymphoblastic leukemia is also presented
Rota, M., Antolini, L., Valsecchi, M. (2013). Cut-point identification in biomarkers for a censored failure time outcome. In Statistics in Life and Environment Sciences (pp.43-46). Bressanone : Società Italiana di Biometria.
Cut-point identification in biomarkers for a censored failure time outcome
ROTA, MATTEO;ANTOLINI, LAURA;VALSECCHI, MARIA GRAZIA
2013
Abstract
Categorization is a crucial step for clinical decision making when dealing with diagnostic (or prognostic) biomarkers. We extend the use of three cut-point finding methods widely used in the absence of censoring, i.e., Youden index, concordance probability and point closest to-(0,1) corner in the ROC plane, to the case of censored failure time outcome. Further, we investigate the performance of the three methods by a simulation protocol. A motivating application of cut-point finding of a molecular biomarker in acute lymphoblastic leukemia is also presentedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.