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Rheumatology Advance Access originally published online on July 9, 2009
Rheumatology 2009 48(9):1114-1121; doi:10.1093/rheumatology/kep155
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

A pilot risk model for the prediction of rapid radiographic progression in rheumatoid arthritis

Nathan Vastesaeger1, Stephen Xu2, Daniel Aletaha3, E. William St Clair4 and Josef S. Smolen3

1Department of Medical Affairs, Centocor BV, Leiden, The Netherlands, 2Department of Biostatistics, Centocor Research & Development, Inc., Malvern, PA, USA, 3Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria and 4Department of Medicine, Duke University Medical Center, Durham, NC, USA.

Correspondence to: Nathan Vastesaeger, Stallestraat 73, 1180 Brussels, Belgium. E-mail: nathan.vastesaeger{at}spcorp.com


  Abstract

Objectives. Identifying patients with RA at high risk of rapid radiographic progression (RRP) is critical for making appropriate treatment decisions. We developed an exploratory prediction model for the risk of RRP using an RA study population undergoing either conservative or aggressive disease management.

Methods. Using data from the active-controlled study of patients receiving infliximab for the treatment of rheumatoid arthritis of early onset (ASPIRE) early RA study, RRP was defined as a threshold change in modified Sharp/van der Heijde score (SHS) of >=5 U/year. Spearman's rank analysis was used to identify baseline risk factors for RRP. Logistic regression was used to calculate the probability of RRP in 1 year. The results were combined into a matrix model that consisted of risk factors and initiated treatment arranged in increasing risk of RRP. Data from the anti-TNF trial in rheumatoid arthritis with concomitant therapy (ATTRACT) established RA study were applied to the model to test its generalizability in another population.

Results. The 28 swollen joint count, RF, CRP and ESR are included as trichotomous variables and initiated treatment (monotherapy or combination therapy) as a dichotomous variable. Two models, one incorporating all risk factors except CRP and another incorporating all risk factors except ESR, were developed to adjust for collinearity. These models identify subpopulations of RA patients at higher predicted risk for RRP.

Conclusions. These preliminary matrix models predict the risk of RRP using initiated treatment and easily accessible clinical and laboratory variables. Further testing in other populations and with other therapies is needed to obtain a definitive risk model that will guide rheumatologists in making treatment decisions for individual RA patients.

KEY WORDS: Risk model, Radiographic progression, Infliximab, TNF-{alpha}, RA, MTX

Submitted 23 December 2008; revised version accepted 14 May 2009.
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