Document Detail


A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data.
MedLine Citation:
PMID:  23037800     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Risk prediction procedures can be quite useful for the patient's treatment selection, prevention strategy, or disease management in evidence-based medicine. Often, potentially important new predictors are available in addition to the conventional markers. The question is how to quantify the improvement from the new markers for prediction of the patient's risk in order to aid cost-benefit decisions. The standard method, using the area under the receiver operating characteristic curve, to measure the added value may not be sensitive enough to capture incremental improvements from the new markers. Recently, some novel alternatives to area under the receiver operating characteristic curve, such as integrated discrimination improvement and net reclassification improvement, were proposed. In this paper, we consider a class of measures for evaluating the incremental values of new markers, which includes the preceding two as special cases. We present a unified procedure for making inferences about measures in the class with censored event time data. The large sample properties of our procedures are theoretically justified. We illustrate the new proposal with data from a cancer study to evaluate a new gene score for prediction of the patient's survival.
Authors:
Hajime Uno; Lu Tian; Tianxi Cai; Isaac S Kohane; L J Wei
Publication Detail:
Type:  Journal Article     Date:  2012-10-05
Journal Detail:
Title:  Statistics in medicine     Volume:  32     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2013 Jun 
Date Detail:
Created Date:  2013-06-04     Completed Date:  2014-01-06     Revised Date:  2014-05-30    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  2430-42     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 John Wiley & Sons, Ltd.
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MeSH Terms
Descriptor/Qualifier:
Biostatistics
Breast Neoplasms / genetics,  mortality
Computer Simulation
Evidence-Based Medicine / statistics & numerical data
Female
Humans
Proportional Hazards Models
ROC Curve
Risk*
Survival Analysis*
Tumor Markers, Biological / genetics
Grant Support
ID/Acronym/Agency:
P30 CA124435/CA/NCI NIH HHS; R01 AI024643/AI/NIAID NIH HHS; R01 GM079330/GM/NIGMS NIH HHS; R01 GM085047/GM/NIGMS NIH HHS; RC4 CA155940/CA/NCI NIH HHS; U54 LM008748/LM/NLM NIH HHS
Chemical
Reg. No./Substance:
0/Tumor Markers, Biological
Comments/Corrections

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