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A simplified baseline prediction model for joint damage progression in rheumatoid arthritis: a step toward
Yvonne M R de Punder1, Piet L C M van Riel1, Jaap Fransen2
1From the Department of Rheumatology, Radboud University Medical Centre, Nijmegen, the Netherlands.Y.M.R. de Punder, MD; P.L.C.M. van Riel, MD, PhD, Professor of Rheumatology; J. Fransen, PhD, Department of Rheumatology, Radboud University Medical Centre.
Objective:
To compare the performance of an extended model and a simplified prognostic model for joint damage in rheumatoid arthritis (RA) based on 3 baseline risk factors: anticyclic citrullinated peptide antibodies (anti-CCP), erosions, and acute-phase reaction.
Methods:
Data were used from the Nijmegen early RA cohort. An extended model and a simplified baseline prediction model were developed to predict joint damage progression between 0 and 3 years. Joint damage progression was assessed using the Ratingen score. In the extended model, prediction factors were positivity for anti-CCP and/or rheumatoid factor, the level of erythrocyte sedimentation rate, and the quantity of erosions. The prediction score was calculated as the sum of the regression coefficients. In the simplified model, the prediction factors were dichotomized and the number of risk factors was counted. Performances of both models were compared using discrimination and calibration. The models were internally validated using bootstrapping.
Results:
The extended model resulted in a prediction score between 0 and 5.6 with an area under the receiver-operation characteristic (ROC) curve of 0.77 (95% CI 0.72-0.81). The simplified model resulted in a prediction score between 0 and 3. This model had an area under the ROC curve of 0.75 (95% CI 0.70-0.80). In internal validation, the 2 models showed reasonably well the agreement between observed and predicted probabilities for joint damage progression (Hosmer-Lemeshow test p > 0.05 and calibration slope near 1.0).
Conclusion:
A simple prediction model for joint damage progression in early RA, by only counting the number of risk factors, has adequate performance. This facilitates the translation of the theoretical prognostic models to daily clinical practice.
