TY - JOUR
T1 - Prediction of cardiovascular events in rheumatoid arthritis using risk age calculations
T2 - Evaluation of concordance across risk age models
AU - Wibetoe, Grunde
AU - Sexton, Joseph
AU - Ikdahl, Eirik
AU - Rollefstad, Silvia
AU - Kitas, George D.
AU - Van Riel, Piet
AU - Gabriel, Sherine
AU - Kvien, Tore K.
AU - Douglas, Karen
AU - Sandoo, Aamer
AU - Arts, Elke E.
AU - Wållberg-Jonsson, Solveig
AU - Dahlqvist, Solbritt Rantapää
AU - Karpouzas, George
AU - Dessein, Patrick H.
AU - Tsang, Linda
AU - El-Gabalawy, Hani
AU - Hitchon, Carol A.
AU - Pascual-Ramos, Virginia
AU - Contreas-Yañes, Irazu
AU - Sfikakis, Petros P.
AU - González-Gay, Miguel A.
AU - Colunga-Pedraz, Iris J.
AU - Galarza-Delgado, Dionicio A.
AU - Azpiri-Lopez, Jose Ramon
AU - Crowson, Cynthia S.
AU - Semb, Anne Grete
N1 - Funding Information:
This work was supported by a collaborative agreement for independent research from Eli Lilly and grants from the Norwegian South East Health Authority (grant numbers 2013064, 2013010). Funding bodies had no role in the design of the study or the collection, analysis, or interpretation of data, nor in the writing of the manuscript.
Publisher Copyright:
© 2020 The Author(s).
PY - 2020/4/23
Y1 - 2020/4/23
N2 - 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.
AB - 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.
KW - Cardiovascular disease
KW - Cardiovascular risk age
KW - Rheumatoid arthritis
KW - Risk factors
KW - Vascular age
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U2 - 10.1186/s13075-020-02178-z
DO - 10.1186/s13075-020-02178-z
M3 - Article
C2 - 32326974
AN - SCOPUS:85084031428
SN - 1478-6354
VL - 22
JO - Arthritis Research and Therapy
JF - Arthritis Research and Therapy
IS - 1
M1 - 90
ER -