Predictive Accuracy of a Polygenic Risk Score–Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease
Main finding · Incident CADResult — go to the resultOverall net reclassification improvement 4.0% 95% CI 3.1%–4.9%Authors' conclusion
The addition of a polygenic risk score for CAD to pooled cohort equations was associated with a statistically significant, yet modest, improvement in the predictive accuracy for incident CAD and improved risk stratification for only a small proportion of individuals.
Study context
- Population
- UK Biobank participants enrolled 2006–20106,272 incident coronary artery disease (CAD) events
- Participants
- 352,660 participants
- Exposure
- PRS-enhanced model vs pooled cohort equations for CAD risk prediction
- Outcome
- Incident CAD (MI and its related sequelae): discrimination, calibration and reclassification (risk threshold 7.5%)
- Follow-up
- Median 8 years
Methodological detailsUK Biobank, case-control sample for score optimisation, separate cohort for evaluation
- UK Biobank
- Case-control sample for score optimisation
- Separate cohort for evaluation
Main finding
Incident CAD
Overall net reclassification improvement
4.0%
95% CI 3.1%–4.9%
By group
Polygenic risk score
0.61
C statistic · 95% CI 0.60–0.62
Pooled cohort equations
0.76
C statistic · 95% CI 0.75–0.77
Both combined
0.78
C statistic · 95% CI 0.77–0.79
As reported in the abstract
Observational data: associations, not effects.
Original publication
Predictive Accuracy of a Polygenic Risk Score–Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease. JAMA. Published 18 February 2020. doi:10.
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