Assessing risk prediction models using individual participant data from multiple studies

Else-Marie Bladbjerg; Jørgen Jespersen

doi:10.1093/aje/kwt298

Assessing risk prediction models using individual participant data from multiple studies

Authors:

Bladbjerg, Else-Marie ;
Close
Thrombosis Research, Institute of Regional Health Research, Faculty of Health Sciences, SDU
Jespersen, Jørgen
Close
Thrombosis Research, Institute of Regional Health Research, Faculty of Health Sciences, SDU

DOI:

10.1093/aje/kwt298

Abstract:

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

Type:

Journal article

Language:

English

Published in:

American Journal of Epidemiology, 2014, Vol 179, Issue 5, p. 621-632

Keywords:

C-Reactive Protein; Coronary Disease; Data Interpretation, Statistical; Female; Humans; Male; Meta-Analysis as Topic; Middle Aged; Models, Statistical; Proportional Hazards Models; Prospective Studies; Risk Assessment; Risk Factors; Journal Article; Research Support, Non-U.S. Gov't

Main Research Area:

Medical science

Publication Status:

Published

Review type:

Peer Review

Submission year:

2014

Scientific Level:

Scientific

ID:

260220016

Assessing risk prediction models using individual participant data from multiple studies

Full text access

On-site access

At institutions

Metrics

Example	Finds records
water{}	containing the word "water".
water supplies"{}"	containing the phrase "water supplies".
author:"Doe, John"author:"{}"	containing the prase "Doe, John" in the author field.
title:IEEEtitle:{}	containing the word "IEEE" in the title field.
Need more help?	Advanced search tutorial