Cynthia S Crowson1, Sherine E Gabriel2, Anne Grete Semb3, Piet L C M van Riel4, George Karpouzas5, Patrick H Dessein6,7, Carol Hitchon8, Virginia Pascual-Ramos9, George D Kitas10. 1. Department of Health Sciences Research and Department of Medicine, Mayo Clinic, Rochester, MN. 2. Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA. 3. Department of Rheumatology, Diakonhjemmet Hospital, Preventive Cardio-Rheuma Clinic, Oslo, Norway. 4. Department of Rheumatic Diseases, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands. 5. Division of Rheumatology, Los Angeles Biomedical Research Institute, Harbor UCLA Medical Center RHU, Torrance, CA, USA. 6. Cardiovascular Pathophysiology and Genomics Research Unit, University of Witwatersrand, Johannesburg, South Africa. 7. Rheumatology Division, Universitair Ziekenhuis and Vrije Universiteit, Brussels, Belgium. 8. Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada. 9. Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, México. 10. Clinical Research, Unit, Dudley Group NHS Foundation Trust, West Midlands, UK.
Abstract
Objectives: Cardiovascular disease (CVD) risk calculators developed for the general population do not accurately predict CVD events in patients with RA. We sought to externally validate risk calculators recommended for use in patients with RA including the EULAR 1.5 multiplier, the Expanded Cardiovascular Risk Prediction Score for RA (ERS-RA) and QRISK2. Methods: Seven RA cohorts from UK, Norway, Netherlands, USA, South Africa, Canada and Mexico were combined. Data on baseline CVD risk factors, RA characteristics and CVD outcomes (including myocardial infarction, ischaemic stroke and cardiovascular death) were collected using standardized definitions. Performance of QRISK2, EULAR multiplier and ERS-RA was compared with other risk calculators [American College of Cardiology/American Heart Association (ACC/AHA), Framingham Adult Treatment Panel III Framingham risk score-Adult Treatment Panel (FRS-ATP) and Reynolds Risk Score] using c-statistics and net reclassification index. Results: Among 1796 RA patients without prior CVD [mean ( s . d .) age: 54.0 (14.0) years, 74% female], 100 developed CVD events during a mean follow-up of 6.9 years (12430 person-years). Estimated CVD risk by ERS-RA [mean ( s . d .) 8.8% (9.8%)] was comparable to FRS-ATP [mean ( s . d .) 9.1% (8.3%)] and Reynolds [mean ( s . d .) 9.2% (12.2%)], but lower than ACC/AHA [mean ( s . d .) 9.8% (12.1%)]. QRISK2 substantially overestimated risk [mean ( s . d .) 15.5% (13.9%)]. Discrimination was not improved for ERS-RA (c-statistic = 0.69), QRISK2 or EULAR multiplier applied to ACC/AHA compared with ACC/AHA (c-statistic = 0.72 for all) or for FRS-ATP (c-statistic = 0.75). The net reclassification index for ERS-RA was low (-0.8% vs ACC/AHA and 2.3% vs FRS-ATP). Conclusion: The QRISK2, EULAR multiplier and ERS-RA algorithms did not predict CVD risk more accurately in patients with RA than CVD risk calculators developed for the general population.
Objectives:Cardiovascular disease (CVD) risk calculators developed for the general population do not accurately predict CVD events in patients with RA. We sought to externally validate risk calculators recommended for use in patients with RA including the EULAR 1.5 multiplier, the Expanded Cardiovascular Risk Prediction Score for RA (ERS-RA) and QRISK2. Methods: Seven RA cohorts from UK, Norway, Netherlands, USA, South Africa, Canada and Mexico were combined. Data on baseline CVD risk factors, RA characteristics and CVD outcomes (including myocardial infarction, ischaemic stroke and cardiovascular death) were collected using standardized definitions. Performance of QRISK2, EULAR multiplier and ERS-RA was compared with other risk calculators [American College of Cardiology/American Heart Association (ACC/AHA), Framingham Adult Treatment Panel III Framingham risk score-Adult Treatment Panel (FRS-ATP) and Reynolds Risk Score] using c-statistics and net reclassification index. Results: Among 1796 RApatients without prior CVD [mean ( s . d .) age: 54.0 (14.0) years, 74% female], 100 developed CVD events during a mean follow-up of 6.9 years (12430 person-years). Estimated CVD risk by ERS-RA [mean ( s . d .) 8.8% (9.8%)] was comparable to FRS-ATP [mean ( s . d .) 9.1% (8.3%)] and Reynolds [mean ( s . d .) 9.2% (12.2%)], but lower than ACC/AHA [mean ( s . d .) 9.8% (12.1%)]. QRISK2 substantially overestimated risk [mean ( s . d .) 15.5% (13.9%)]. Discrimination was not improved for ERS-RA (c-statistic = 0.69), QRISK2 or EULAR multiplier applied to ACC/AHA compared with ACC/AHA (c-statistic = 0.72 for all) or for FRS-ATP (c-statistic = 0.75). The net reclassification index for ERS-RA was low (-0.8% vs ACC/AHA and 2.3% vs FRS-ATP). Conclusion: The QRISK2, EULAR multiplier and ERS-RA algorithms did not predict CVD risk more accurately in patients with RA than CVD risk calculators developed for the general population.
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