title: [Time related receiver operation characteristic curves and its application in clinical trials and diagnostic analysis].
abstract: By using R language to deal with practical problems, we introduce two methods of obtaining time related receiver operation characteristic [ROC(t)] curves from survival data: 1) nearest-neighbor estimator of bivariate distribution (NNE) estimation: to obtain cumulative/dynamic ROC(C/D) (t) curves; 2) Cox estimation: to obtain incident/dynamic ROC(I/D) (t) curves. The areas under the ROC(t) curves (AUC) obtained from the two methods fluctuate over time. The one obtained through NNE has bigger fluctuation than that obtained through Cox, while the mean of AUC of the two methods are similar. Time related ROC (t) can be effectively used to evaluate the diagnostic capacity of the marker in clinical trials, and help to select the best diagnostic time of the marker. According to the different scientific interests, researchers should select relevant methods for more accurate evaluation.
authors.affiliation: Division of Medical Research, National Center for Cardiovascular Disease, Beijing 102300, China.
authors.forename: Y Y
authors.initials: YY
authors.lastname: Zhao
authors.forename: W
authors.initials: W
authors.lastname: Zhao
authors.forename: Z Y
authors.initials: ZY
authors.lastname: Wang
authors.forename: W
authors.initials: W
authors.lastname: Li
authors.forename: Y
authors.initials: Y
authors.lastname: Wang
mesh_terms: D002986:Clinical Trials as Topic; D012372:ROC Curve; D013997:Time Factors