OBJECTIVES: To develop a matrix model for the prediction of rapid radiographic progression (RRP) in subpopulations of patients with recent-onset rheumatoid arthritis (RA) receiving different dynamic treatment strategies. METHODS: Data from 465 patients with recent-onset RA randomised to receive initial monotherapy or combination therapy were used. Predictors for RRP (increase in Sharp-van der Heijde score > or =5 after 1 year) were identified by multivariate logistic regression analysis. For subpopulations, the estimated risk of RRP per treatment group and the number needed to treat (NNT) were visualised in a matrix. RESULTS: The presence of autoantibodies, baseline C-reactive protein (CRP) level, erosion score and treatment group were significant independent predictors of RRP in the matrix. Combination therapy was associated with a markedly reduced risk of RRP. The positive and negative predictive values of the matrix were 62% and 91%, respectively. The NNT with initial combination therapy to prevent one patient from RRP with monotherapy was in the range 2-3, 3-7 and 7-25 for patients with a high, intermediate and low predicted risk, respectively. CONCLUSION: The matrix model visualises the risk of RRP for subpopulations of patients with recent-onset RA if treated dynamically with initial monotherapy or combination therapy. Rheumatologists might use the matrix for weighing their initial treatment choice.
RCT Entities:
OBJECTIVES: To develop a matrix model for the prediction of rapid radiographic progression (RRP) in subpopulations of patients with recent-onset rheumatoid arthritis (RA) receiving different dynamic treatment strategies. METHODS: Data from 465 patients with recent-onset RA randomised to receive initial monotherapy or combination therapy were used. Predictors for RRP (increase in Sharp-van der Heijde score > or =5 after 1 year) were identified by multivariate logistic regression analysis. For subpopulations, the estimated risk of RRP per treatment group and the number needed to treat (NNT) were visualised in a matrix. RESULTS: The presence of autoantibodies, baseline C-reactive protein (CRP) level, erosion score and treatment group were significant independent predictors of RRP in the matrix. Combination therapy was associated with a markedly reduced risk of RRP. The positive and negative predictive values of the matrix were 62% and 91%, respectively. The NNT with initial combination therapy to prevent one patient from RRP with monotherapy was in the range 2-3, 3-7 and 7-25 for patients with a high, intermediate and low predicted risk, respectively. CONCLUSION: The matrix model visualises the risk of RRP for subpopulations of patients with recent-onset RA if treated dynamically with initial monotherapy or combination therapy. Rheumatologists might use the matrix for weighing their initial treatment choice.
Authors: K Albrecht; A Richter; Y Meissner; D Huscher; L Baganz; K Thiele; M Schneider; A Strangfeld; A Zink Journal: Z Rheumatol Date: 2017-06 Impact factor: 1.372
Authors: K Krüger; J Wollenhaupt; K Albrecht; R Alten; M Backhaus; C Baerwald; W Bolten; J Braun; H Burkhardt; G Burmester; M Gaubitz; A Gause; E Gromnica-Ihle; H Kellner; J Kuipers; A Krause; H-M Lorenz; B Manger; H Nüßlein; H-G Pott; A Rubbert-Roth; M Schneider; C Specker; H Schulze-Koops; H-P Tony; S Wassenberg; U Müller-Ladner Journal: Z Rheumatol Date: 2012-09 Impact factor: 1.372
Authors: Maria-Antonietta D'Agostino; Maarten Boers; John Kirwan; Désirée van der Heijde; Mikkel Østergaard; Georg Schett; Robert B Landewé; Walter P Maksymowych; Esperanza Naredo; Maxime Dougados; Annamaria Iagnocco; Clifton O Bingham; Peter M Brooks; Dorcas E Beaton; Frederique Gandjbakhch; Laure Gossec; Francis Guillemin; Sarah E Hewlett; Margreet Kloppenburg; Lyn March; Philip J Mease; Ingrid Moller; Lee S Simon; Jasvinder A Singh; Vibeke Strand; Richard J Wakefield; George A Wells; Peter Tugwell; Philip G Conaghan Journal: J Rheumatol Date: 2014-03-01 Impact factor: 4.666