Paper Info
Title
Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy.
Abstract
We propose new time-dependent sensitivity, specificity, ROC curves and net reclassification indices that can take into account biomarkers or scores that are repeatedly measured at different time-points. Inference proceeds through inverse probability weighting and resampling. The newly proposed measures exploit the information contained in biomarkers measured at different visits, rather than using only the measurements at the first visits. The contribution is illustrated via simulations and an original application on patients affected by dilated cardiomiopathy. The aim is to evaluate if repeated binary measurements of right ventricular dysfunction bring additive prognostic information on mortality/urgent heart transplant. It is shown that taking into account the trajectory of the new biomarker improves risk classification, while the first measurement alone might not be sufficiently informative. The methods are implemented in an R package (longROC), freely available on CRAN.
Year
DOI
Venue
2018
10.1007/s10260-017-0410-2
Statistical Methods and Applications
Keywords
Field
DocType
AUC,NRI,ROC,Prognostic scores
Dilated cardiomyopathy,Inverse probability weighting,Receiver operating characteristic,Internal medicine,Inference,Cardiology,Right ventricular dysfunction,Biomarker (medicine),Statistics,Resampling,Mathematics,R package
Journal
Volume
Issue
ISSN
27
3
1618-2510
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Giulia Barbati172.60
Alessio Farcomeni26111.28