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.

Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy / Barbati, Giulia; Farcomeni, Alessio. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - 27:(2018), pp. 545-557. [10.1007/s10260-017-0410-2]

Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy

BARBATI, GIULIA;Farcomeni, Alessio
2018

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.
2018
auc; nri; prognostic scores; roc; statistics and probability; statistics, probability and uncertainty
01 Pubblicazione su rivista::01a Articolo in rivista
Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy / Barbati, Giulia; Farcomeni, Alessio. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - 27:(2018), pp. 545-557. [10.1007/s10260-017-0410-2]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1135996
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