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Assessing the incremental predictive performance of novel biomarkers over standard predictors.

Publication ,  Journal Article
Xanthakis, V; Sullivan, LM; Vasan, RS; Benjamin, EJ; Massaro, JM; D'Agostino, RB; Pencina, MJ
Published in: Stat Med
July 10, 2014

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.

Duke Scholars

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Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

July 10, 2014

Volume

33

Issue

15

Start / End Page

2577 / 2584

Location

England

Related Subject Headings

  • Statistics & Probability
  • Risk Assessment
  • Predictive Value of Tests
  • Natriuretic Peptide, Brain
  • Models, Statistical
  • Models, Cardiovascular
  • Male
  • Humans
  • Female
  • C-Reactive Protein
 

Citation

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Xanthakis, V., Sullivan, L. M., Vasan, R. S., Benjamin, E. J., Massaro, J. M., D’Agostino, R. B., & Pencina, M. J. (2014). Assessing the incremental predictive performance of novel biomarkers over standard predictors. Stat Med, 33(15), 2577–2584. https://doi.org/10.1002/sim.6165
Xanthakis, Vanessa, Lisa M. Sullivan, Ramachandran S. Vasan, Emelia J. Benjamin, Joseph M. Massaro, Ralph B. D’Agostino, and Michael J. Pencina. “Assessing the incremental predictive performance of novel biomarkers over standard predictors.Stat Med 33, no. 15 (July 10, 2014): 2577–84. https://doi.org/10.1002/sim.6165.
Xanthakis V, Sullivan LM, Vasan RS, Benjamin EJ, Massaro JM, D’Agostino RB, et al. Assessing the incremental predictive performance of novel biomarkers over standard predictors. Stat Med. 2014 Jul 10;33(15):2577–84.
Xanthakis, Vanessa, et al. “Assessing the incremental predictive performance of novel biomarkers over standard predictors.Stat Med, vol. 33, no. 15, July 2014, pp. 2577–84. Pubmed, doi:10.1002/sim.6165.
Xanthakis V, Sullivan LM, Vasan RS, Benjamin EJ, Massaro JM, D’Agostino RB, Pencina MJ. Assessing the incremental predictive performance of novel biomarkers over standard predictors. Stat Med. 2014 Jul 10;33(15):2577–2584.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

July 10, 2014

Volume

33

Issue

15

Start / End Page

2577 / 2584

Location

England

Related Subject Headings

  • Statistics & Probability
  • Risk Assessment
  • Predictive Value of Tests
  • Natriuretic Peptide, Brain
  • Models, Statistical
  • Models, Cardiovascular
  • Male
  • Humans
  • Female
  • C-Reactive Protein