Microsimulation model to predict incremental value of biomarkers added to prognostic models.

Published

Journal Article

It is unclear to what extent simulated versions of real data can be used to assess potential value of new biomarkers added to prognostic risk models. Using data on 4522 women and 3969 men who contributed information to the Framingham CVD risk prediction tool, we develop a simulation model that allows assessment of the added contribution of new biomarkers. The simulated model matches closely the one obtained using real data: discrimination area under the curve (AUC) on simulated vs actual data is 0.800 vs 0.799 in women and 0.778 vs 0.776 in men. Positive correlation with standard risk factors decreases the impact of new biomarkers (ΔAUC 0.002-0.024), but negative correlation leads to stronger effects (ΔAUC 0.026-0.101) than no correlation (ΔAUC 0.003-0.051). We suggest that researchers construct simulation models similar to the one proposed here before embarking on larger, expensive biomarker studies based on actual data.

Full Text

Duke Authors

Cited Authors

  • Pencina, KM; D'Agostino, RB; Vasan, RS; Pencina, MJ

Published Date

  • October 1, 2018

Published In

Volume / Issue

  • 25 / 10

Start / End Page

  • 1382 - 1385

PubMed ID

  • 30169699

Pubmed Central ID

  • 30169699

Electronic International Standard Serial Number (EISSN)

  • 1527-974X

Digital Object Identifier (DOI)

  • 10.1093/jamia/ocy108

Language

  • eng

Conference Location

  • England