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Extended report
Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms
  1. E E A Arts1,
  2. C D Popa1,2,
  3. A A Den Broeder3,
  4. R Donders4,
  5. A Sandoo5,
  6. T Toms5,
  7. S Rollefstad6,
  8. E Ikdahl6,
  9. A G Semb6,
  10. G D Kitas5,
  11. P L C M Van Riel2,7,
  12. J Fransen1
  1. 1Department of Rheumatology, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2Department of Rheumatology, Bernhoven Hospital, Uden, The Netherlands
  3. 3Department of Rheumatology, Sint Maartenskliniek, Nijmegen, The Netherlands
  4. 4Department of Epidemiology, Biostatistics and Health Technology Assessment, Radboud University Medical Center, Nijmegen, The Netherlands
  5. 5Department of Rheumatology, Dudley Group NHS Foundation Trust, Dudley, UK
  6. 6Preventive Cardio-Rheuma Clinic, Diakonhjemmet Hospital, Oslo, Norway
  7. 7Radboud Institute for Health Sciences, IQ healthcare, Radboud University Medical Center, Nijmegen, The Netherlands
  1. Correspondence to E E A Arts, Department of Rheumatology, Radboud University Medical Center, Nijmegen 6500 HB, The Netherlands; elke.arts{at}radboudumc.nl

Abstract

Objectives Predictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm.

Methods Data from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated.

Results Of the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer–Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups.

Conclusions This study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA.

  • Cardiovascular Disease
  • Rheumatoid Arthritis
  • Disease Activity

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