A Prognostic Model for Functional Outcome in Early Rheumatoid Arthritis
NICK BANSBACK, ADAM YOUNG, ALAN BRENNAN, and JOSH DIXEY
Objective. To construct a prognostic algorithm to predict 5-year functional outcome in rheumatoid arthritis (RA), based on the Health Assessment Questionnaire (HAQ).
Methods. Data from all patients with 5-year followup (n = 985) were used from an inception cohort, the Early Rheumatoid Arthritis Study (ERAS). Possibly relevant prognostic factors considered in the initial stage of the model-building process were standard clinical, radiological, and laboratory features measured at baseline and at 1 year. Multivariate analysis was performed using logistic regression, and the predictive performance of the model was tested using measures of discrimination and calibration.
Results. Bootstrap resampling identified 6 variables that consistently predicted severe functional outcome. Functional grade III/IV (odds ratio 6.7) and HAQ at 1 year (odds ratio 2.4) were the most important. Other variables included socioeconomic status, hemoglobin, and radiographic and disease activity scores. Estimates of the regression coefficients and performance were corrected for over-fitting. Reasonably large values for the c-index (0.82) and the Nagelkerke R2 (0.39) indicate that the set of prognostic factors explains the variation in outcome to a degree that implies good prediction for individual patients.
Conclusion. The algorithm identifies patients in the first year of RA who are likely to have poor function by 5 years and who could potentially benefit from aggressive drug therapy. A nomogram is produced for simple application of the model in clinical practice. While further external validation is necessary, this model could allow clinicians to target aggressive therapy earlier in a patient's disease course. (First Release July 1 2006; J Rheumatol 2006;33:1503–10)
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From the Early Rheumatoid Arthritis Study Group (ERAS), Department of Rheumatology, City Hospital, St. Albans, UK.
Supported by an ARC Academic Secretary Grant and a BUPA Foundation Research Grant.
N. Bansback, BSc, Senior Operational Research Analyst; A. Brennan, PhD, Director, Operational Research Health Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK; A. Young, MD, Consultant Rheumatologist; J. Dixey, MD, Consultant Rheumatologist, ERAS, Department of Rheumatology, City Hospital.
Address reprint requests to Dr. A. Young, Department of Rheumatology, City Hospital, St. Albans, AL3 5PN, UK. E-mail: email@example.com
Accepted for publication March 29, 2006.