Predictive accuracy of markers or risk scores for interval censored survival data.

TitlePredictive accuracy of markers or risk scores for interval censored survival data.
Publication TypeJournal Article
Year of Publication2020
AuthorsWu, Yuan, Xiaofei Wang, Jiaxing Lin, Beilin Jia, and Kouros Owzar
JournalStat Med
Volume39
Issue18
Pagination2437-2446
Date Published2020 08 15
ISSN1097-0258
KeywordsBiomarkers, Computer Simulation, Humans, Likelihood Functions, Risk Factors, ROC Curve
Abstract

Methods for the evaluation of the predictive accuracy of biomarkers with respect to survival outcomes subject to right censoring have been discussed extensively in the literature. In cancer and other diseases, survival outcomes are commonly subject to interval censoring by design or due to the follow up schema. In this article, we present an estimator for the area under the time-dependent receiver operating characteristic (ROC) curve for interval censored data based on a nonparametric sieve maximum likelihood approach. We establish the asymptotic properties of the proposed estimator and illustrate its finite-sample properties using a simulation study. The application of our method is illustrated using data from a cancer clinical study. An open-source R package to implement the proposed method is available on Comprehensive R Archive Network.

DOI10.1002/sim.8547
Alternate JournalStat Med
Original PublicationPredictive accuracy of markers or risk scores for interval censored survival data.
PubMed ID32293745
PubMed Central IDPMC7806230
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States