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External validation of the accuracy of cardiovascular risk prediction tools in psoriatic disease: a UK Biobank study
David M Hughes1, Zenas Z N Yiu2, Sizheng Steven Zhao3
1Department of Health Data Science, University of Liverpool, Liverpool, UK. dmhughes@liverpool.ac.uk.
Insights
Cardiovascular disease (CVD) risk prediction tools are less accurate for individuals with psoriatic arthritis (PsA) and rheumatoid arthritis (RA) compared to those with psoriasis or no inflammatory conditions.
Area of Science:
- Rheumatology
- Cardiology
- Epidemiology
Background:
- Cardiovascular disease (CVD) risk prediction is crucial for disease management.
- Standard CVD risk prediction tools may lack accuracy in individuals with inflammatory conditions.
Purpose of the Study:
- To evaluate the performance of four CVD risk prediction tools: QRISK3, Framingham Risk Score, Reynolds Risk Score, and SCORE.
- To compare tool accuracy in patients with psoriatic arthritis (PsA) and psoriasis versus those without inflammatory diseases and with rheumatoid arthritis (RA).
Main Methods:
- Utilized the UK Biobank Resource to identify participants with PsA, psoriasis, and RA.
- Calculated CVD risk using four distinct risk prediction tools.
- Assessed model calibration and discrimination (AUC, sensitivity, specificity, PPV, NPV) for 10-year risk.
Main Results:
- QRISK3 showed similar prediction accuracy for psoriasis (AUC 0.74) and no inflammatory conditions (AUC 0.74).
- Individuals with PsA (AUC 0.70) and RA (AUC 0.72) exhibited lower prediction accuracy with QRISK3.
- Framingham Risk Score also demonstrated lower accuracy for PsA (AUC 0.61) compared to controls (AUC 0.71).
Conclusions:
- CVD risk prediction accuracy is comparable for individuals with psoriasis and those without inflammatory conditions.
- Individuals with PsA and RA experience diminished accuracy in CVD risk prediction tools.
Introduction:
Risk prediction is important for preventing and managing cardiovascular disease (CVD). CVD risk prediction tools designed for the general population may be inaccurate in people with inflammatory diseases.
Objectives:
To investigate the performance of four cardiovascular risk prediction tools (QRISK3, Framingham Risk Score, Reynolds Risk Score and SCORE) in psoriatic arthritis (PsA) and psoriasis. We also compare performance in participants with no inflammatory conditions and in people with rheumatoid arthritis (RA).
Methods:
This research utilised the UK Biobank Resource. We identified participants with PsA, psoriasis and RA and calculated their cardiovascular risk using each risk tool. We assessed model calibration by comparing observed and predicted outcomes. Discrimination of 10-year risk prediction was assessed using time-dependent area under ROC curve (AUC), sensitivity, specificity, positive and negative predictive values.
Results:
We included 769 individuals with PsA, 8062 with psoriasis and 4772 with RA when assessing the QRISK3 tool. Predictions for individuals with psoriasis were roughly as accurate as those with no inflammatory conditions with time-dependent AUC of 0.74 (95%CI, 0.72, 0.76) and of 0.74 (95%CI, 0.72, 0.77) respectively. In contrast, individuals with PsA obtained the least accurate predictions with an AUC of 0.70 (95%CI, 0.64, 0.76). Individuals with RA also obtained less accurate predictions with AUC of 0.72 (0.69,0.74). For the Framingham risk score, AUCs varied between 0.61 (95%CI, 0.55, 0.68) for participants with PsA and 0.71 (95%CI, 0.68, 0.74) for individuals with no inflammatory condition.
Conclusions:
In general, CVD risk prediction accuracy was similar for individuals with psoriasis or no inflammatory condition, but lower for individuals with PsA or RA.
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