Combining European and U.S. risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study
Authors' conclusion
Combining a PRS with clinical risk scores significantly improved the reclassification of risk for incident ASCVD for subjects in the clinically determined intermediate-risk category.
Study context
- Population
- Population-based European cohort (CoLaus|PsyCoLaus), baseline 2003–20063,383 analysed for prediction
- Participants
- 6,733 participants
- Exposure
- Clinical risk scores combined with polygenic risk score (PRS) vs clinical risk scores alone
- Outcome
- Prediction of ASCVD (discrimination, calibration, reclassification)
- Follow-up
- Median 14.4 years
Methodological detailspopulation-based
- Population-based
Main finding
As reported in the abstract
Change in C statistic, incident ASCVD (190 events)
Change in C statistic
0.008
95% CI −0.00008–0.02P = 0.05
SCORE2 + metaGRS_CAD vs SCORE2
Change in C statistic
0.007
95% CI 0.005–0.01P = 0.03
Pooled Cohort Equation (PCE) + metaGRS_CAD vs PCE
Observational data: associations, not effects.
Further findings
| Outcome | NRI (95% CI) |
|---|---|
| Reclassification, clinically intermediate-risk subjectsSCORE2 + metaGRS_CAD vs SCORE2 | 9.6% (0.3–18.8) |
| Reclassification, clinically intermediate-risk subjectsPCE + metaGRS_CAD vs PCE | 12.0% (1.5–22.6) |
PRS comparison: metaGRS_CAD best predictive capacity (4 PRSs, 4218 subjects, 363 prevalent and incident atherosclerotic cardiovascular disease (ASCVD))
- metaGRS_CAD AUROC
- 0.77
Original publication
Combining European and U.S. risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study. Eur J Prev Cardiol. Published 18 January 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →