Leflunomide in the treatment of rheumatoid arthritis. An analysis of predictors for treatment continuation
Roon, E.N. van and Hoekstra, M. and Tobi, H. and Jansen, T.L.Th.A. and Bernelot Moens, H.J. and Brouwers, J.R.B.J. and Laar, M.A.F.J. van de (2005) Leflunomide in the treatment of rheumatoid arthritis. An analysis of predictors for treatment continuation. British Journal of Clinical Pharmacology, 60 (3). pp. 319-325. ISSN 03065251
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To determine factors predictive for leflunomide drug survival in an outpatient population with rheumatoid arthritis in a setting of care-as-usual.
A standard dataset was collected from medical records of consecutive outpatients on leflunomide treatment for rheumatoid arthritis between January 2000 and June 2003. The dataset consisted of patient, disease and treatment characteristics at the start of leflunomide treatment, and data on leflunomide use.
Leflunomide was started in 279 patients and 173 patients (62.0%) withdrew from treatment during follow-up. From univariate analysis, concomitant systemic corticosteroid use [hazard ratio (HR) (95% confidence interval) 1.35 (1.00, 1.83)] and an erythrocyte sedimentation rate <35 mm h−1[HR 1.38 (1.01, 1.88)] at start of leflunomide were found to be predictive for better leflunomide survival. Furthermore, the attending rheumatologist was correlated with leflunomide drug survival. Hazard ratios varied, depending on the individual rheumatologist, from 0.60 to 2.66. Multivariate analysis suggested attending rheumatologist (HR varying from 0.54 to 2.30 depending on the individual rheumatologist), concomitant systemic corticosteroid use [HR 1.58 (1.14 2.21)] and erythrocyte sedimentation rate <35 mm h−1[HR 1.42 (1.03, 1.96)] at start of leflunomide to be associated with leflunomide survival.
Concomitant systemic corticosteroid use, erythrocyte sedimentation rate at the start of treatment and attending rheumatologist were found to be predictive for leflunomide survival. Information on these predictors at the start of leflunomide therapy may offer information on which patients are at an increased risk of withdrawal from leflunomide. Whether this information leads to optimization of leflunomide treatment outcomes remains to be studied.
|Copyright:||© 2005 Blackwell|
Faculty of Behavioural, Management and Social sciences (BMS)
|Link to this item:||http://purl.utwente.nl/publications/58417|
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