Assessing the incremental predictive performance of novel biomarkers over standard predictors.
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 C-statistic as discrimination metrics. The new biomarker was added to the following: null model, model including a published risk score, model including a composite risk score estimated from the sample of interest, and multivariable model with individual predictors. 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 C-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.
Framingham Heart Study, Framingham, MA, U.S.A.; Department of Biostatistics, Boston University School of Public Health, Boston, MA, U.S.A.; Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, U.S.A.
Vanessa
V
Xanthakis
Lisa M
LM
Sullivan
Ramachandran S
RS
Vasan
Emelia J
EJ
Benjamin
Joseph M
JM
Massaro
Ralph B
RB
D'Agostino
Michael J
MJ
Pencina
D001281:Atrial Fibrillation / Q000175:diagnosis; D015415:Biomarkers / Q000032:analysis*; D002097:C-Reactive Protein / Q000032:analysis; D005260:Female; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D015233:Models, Statistical; D020097:Natriuretic Peptide, Brain / Q000032:analysis; D011237:Predictive Value of Tests; D018570:Risk Assessment / Q000379:methods*
D015415:Biomarkers; D020097:Natriuretic Peptide, Brain; D002097:C-Reactive Protein
biomarkers; model discrimination; risk model; risk prediction