Assessing the incremental predictive performance of novel biomarkers over standard predictors. (9th April 2014)

• Record Type: Journal Article
• Authors: Xanthakis, Vanessa; Sullivan, Lisa M.; Vasan, Ramachandran S.; Benjamin, Emelia J.; Massaro, Joseph M.; D'Agostino, Ralph B.; Pencina, Michael J.
• Is Part Of: Statistics in medicine. Volume 33:Number 15(2014)
• Page Start: 2577
• Page End: 2584
• Publication Date: 2014-04-09
• Subjects: Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.6165
• Languages: English
• ISSNs: 0277-6715

Abstract

<abstract abstract-type="main" id="sim6165-abs-0001"> <title>Abstract</title> <p id="sim6165-para-0001">It is unclear to what extent the incremental predictive performance of a novel biomarker is impacted by the method used to control for standard predictors. We investigated whether adding a biomarker to a model with a published risk score overestimates its incremental performance as compared to adding it to a multivariable model with individual predictors (or a composite risk score estimated from the sample of interest) and to a null model. We used 1000 simulated datasets (with a range of risk factor distributions and event rates) to compare these methods, using the continuous net reclassification index (NRI), the integrated discrimination index (IDI), and change in the <italic>C</italic>‐statistic as discrimination metrics. The new biomarker was added to the following: <italic>null</italic> model, model including a <italic>published risk score</italic>, model including a <italic>composite risk score</italic> estimated from the sample of interest, and multivariable model with <italic>individual predictors</italic>. We observed a gradient in the incremental performance of the biomarker, with the null model resulting in the highest predictive performance of the biomarker and the model using individual predictors resulting in the lowest (mean increases in <italic>C</italic>‐statistic between models without and with the biomarker: 0.261, 0.085, 0.030, and 0.031; NRI: 0.767, 0.621, 0.513, and 0.530; IDI: 0.153, 0.093, 0.053 and 0.057, respectively). These findings were supported by the Framingham Study data predicting atrial fibrillation using novel biomarkers. We recommend that authors report the effect of a new biomarker after controlling for standard predictors modeled as individual variables. Copyright © 2014 John Wiley & Sons, Ltd.</p> </abstract>