Evaluating Prognostic Accuracy of Biomarkers under Competing Risk

DOI10.1111/j.1541-0420.2011.01671.xzbMath1251.62054OpenAlexW2056718591WikidataQ36961055 ScholiaQ36961055MaRDI QIDQ2912330

Yuying Jin, Ziding Feng, Yingye Zheng, Tianxi Cai

Publication date: 14 September 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3694786

zbMATH Keywords

survival analysiscause-specific hazardbiomarker evaluationnegative predictive valuespositive predictive valuesreceiver operating characteristics curve (ROC curve)

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Related Items (8)

Prognostic accuracy for predicting ordinal competing risk outcomes using ROC surfaces ⋮ A direct method to evaluate the time‐dependent predictive accuracy for biomarkers ⋮ Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time‐to‐event in presence of censoring and competing risks ⋮ Optimal cutoffs for continuous biomarkers for survival data under competing risks ⋮ Gaussian copula regression modeling for marker classification metrics with competing risk outcomes ⋮ Time-dependent ROC methodology to evaluate the predictive accuracy of semiparametric multi-state models in the presence of competing risks: An application to peritoneal dialysis programme ⋮ Assessing diagnostic accuracy improvement for survival or competing‐risk censored outcomes ⋮ Time-Dependent AUC with Right-Censored Data: A Survey

Uses Software

• cmprsk

Cites Work

• ROC analysis with multiple classes and multiple tests: methodology and its application in microarray studies
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• The Analysis of Failure Times in the Presence of Competing Risks
• Regression modeling of competing crude failure probabilities
• Semiparametric Estimation of Regression Quantiles with Application to Standardizing Weight for Height and Age in US Children
• A Proportional Hazards Model for the Subdistribution of a Competing Risk
• Prediction of Cumulative Incidence Function under the Proportional Hazards Model
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
• Prospective Accuracy for Longitudinal Markers
• Survival Model Predictive Accuracy and ROC Curves

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