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.

Clinical Rheumatology
|January 20, 2025
PubMed

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.
Abstract

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