The predictive accuracy of cardiovascular disease risk prediction tools in inflammatory arthritis and psoriasis: an observational validation study using the Clinical Practice Research Datalink

Abstract

OBJECTIVES: Cardiovascular risk prediction tools developed for the general population often underperform for individuals with RA, and their predictive accuracy are unclear for other inflammatory conditions that also have increased cardiovascular risk. We investigated the performance of QRISK-3, the Framingham Risk Score (FRS) and the Reynolds Risk Score (RRS) in RA, psoriatic disease (PsA and psoriasis) and AS. We considered OA as a non-inflammatory comparator. METHODS: We utilized primary care records from the Clinical Practice Research Datalink (CPRD) Aurum database to identify individuals with each condition and calculated 10-year cardiovascular risk using each prediction tool. The discrimination and calibration of each tool was assessed for each disease. RESULTS: The time-dependent area under the curve (AUC) for QRISK3 was 0.752 for RA (95% CI 0.734-0.777), 0.794 for AS (95% CI 0.764-0.812), 0.764 for PsA (95% CI 0.741-0.791), 0.815 for psoriasis (95% CI 0.789-0.835) and 0.698 for OA (95% CI 0.670-0.717), indicating reasonably good predictive performance. The AUCs for the FRS were similar, and slightly lower for the RRS. The FRS was reasonably well calibrated for each condition but underpredicted risk for patients with RA. The RRS tended to underpredict CVD risk, while QRISK3 overpredicted CVD risk, especially for the most high-risk individuals. CONCLUSION: CVD risk for individuals with RA, AS and psoriatic disease was generally less accurately predicted using each of the three CVD risk prediction tools than the reported accuracies in the original publications. Individuals with OA also had less accurate predictions, suggesting inflammation is not the sole reason for underperformance. Disease-specific risk prediction tools may be required.