Prediction of cardiovascular events in rheumatoid arthritis using risk age calculations: Evaluation of concordance across risk age models

Grunde Wibetoe, Joseph Sexton, Eirik Ikdahl, Silvia Rollefstad, George D. Kitas, Piet Van Riel, Sherine Gabriel, Tore K. Kvien, Karen Douglas, Aamer Sandoo, Elke E. Arts, Solveig Wållberg-Jonsson, Solbritt Rantapää Dahlqvist, George Karpouzas, Patrick H. Dessein, Linda Tsang, Hani El-Gabalawy, Carol A. Hitchon, Virginia Pascual-Ramos, Irazu Contreas-YañesPetros P. Sfikakis, Miguel A. González-Gay, Iris J. Colunga-Pedraz, Dionicio A. Galarza-Delgado, Jose Ramon Azpiri-Lopez, Cynthia S. Crowson, Anne Grete Semb

Research output: Contribution to journalArticlepeer-review

Abstract

Background: In younger individuals, low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD. Calculation of risk age is proposed as an adjuvant to absolute CVD risk estimation in European guidelines. We aimed to compare the discriminative ability of available risk age models in prediction of CVD in rheumatoid arthritis (RA). Secondly, we also evaluated the performance of risk age models in subgroups based on RA disease characteristics. Methods: RA patients aged 30-70 years were included from an international consortium named A Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis (ATACC-RA). Prior CVD and diabetes mellitus were exclusion criteria. The discriminatory ability of specific risk age models was evaluated using c-statistics and their standard errors after calculating time until fatal or non-fatal CVD or last follow-up. Results: A total of 1974 patients were included in the main analyses, and 144 events were observed during follow-up, the median follow-up being 5.0 years. The risk age models gave highly correlated results, demonstrating R 2 values ranging from 0.87 to 0.97. However, risk age estimations differed > 5 years in 15-32% of patients. C-statistics ranged 0.68-0.72 with standard errors of approximately 0.03. Despite certain RA characteristics being associated with low c-indices, standard errors were high. Restricting analysis to European RA patients yielded similar results. Conclusions: The cardiovascular risk age and vascular age models have comparable performance in predicting CVD in RA patients. The influence of RA disease characteristics on the predictive ability of these prediction models remains inconclusive.

Original languageEnglish (US)
Article number90
JournalArthritis Research and Therapy
Volume22
Issue number1
DOIs
StatePublished - Apr 23 2020

All Science Journal Classification (ASJC) codes

  • Rheumatology
  • Immunology and Allergy
  • Immunology

Keywords

  • Cardiovascular disease
  • Cardiovascular risk age
  • Rheumatoid arthritis
  • Risk factors
  • Vascular age

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