Background: Framingham-based and Reynolds Risk scores for cardiovascular disease (CVD) prediction have not been directly compared in an independent validation cohort.
Methods and results: We selected a case-cohort sample of the multiethnic Women's Health Initiative Observational Cohort, comprising 1722 cases of major CVD (752 myocardial infarctions, 754 ischemic strokes, and 216 other CVD deaths) and a random subcohort of 1994 women without prior CVD. We estimated risk using the Adult Treatment Panel III (ATP-III) score, the Reynolds Risk Score, and the Framingham CVD model, reweighting to reflect cohort frequencies. Predicted 10-year risk varied widely between models, with ≥10% risk in 6%, 10%, and 41% of women with the ATP-III, Reynolds, and Framingham CVD models, respectively. Calibration was adequate for the Reynolds model, but the ATP-III and Framingham CVD models overestimated risk for coronary heart disease and major CVD, respectively. After recalibration, the Reynolds model demonstrated improved discrimination over the ATP-III model through a higher c statistic (0.765 versus 0.757; P=0.03), positive net reclassification improvement (NRI; 4.9%; P=0.02), and positive integrated discrimination improvement (4.1%; P<0.0001) overall, excluding diabetics (NRI=4.2%; P=0.01), and in white (NRI=4.3%; P=0.04) and black (NRI=11.4%; P=0.13) women. The Reynolds (NRI=12.9%; P<0.0001) and ATP-III (NRI=5.9%; P=0.0001) models demonstrated better discrimination than the Framingham CVD model.
Conclusions: The Reynolds Risk Score was better calibrated than the Framingham-based models in this large external validation cohort. The Reynolds score also showed improved discrimination overall and in black and white women. Large differences in risk estimates exist between models, with clinical implications for statin therapy.