A multi-parameter response prediction model for rituximab in rheumatoid arthritis

被引:19
作者
de Jong, Tamarah D. [1 ]
Sellam, Jeremie [2 ]
Agca, Rabia [1 ,3 ]
Vosslamber, Saskia [4 ]
Witte, Birgit I. [5 ]
Tsang-A-Sjoe, Michel [1 ]
Mantel, Elise [1 ]
Bijlsma, Johannes W. [1 ,3 ]
Voskuyl, Alexandre E. [1 ]
Nurmohamed, Mike T. [1 ,3 ]
Verweij, Cornelis L. [4 ]
Mariette, Xavier [6 ]
机构
[1] Vrije Univ Amsterdam, Med Ctr, Amsterdam Rheumatol & Immunol Ctr, POB 7057, NL-1007 MB Amsterdam, Netherlands
[2] Univ Paris 06, St Antoine Hosp, AP HP, Inserm UMRS 938,Rheumatol Dept,DHU i2B, 184 Rue Faubourg St Antoine, F-75012 Paris, France
[3] Reade, Amsterdam Rheumatol & Immunol Ctr, POB 58271, NL-1040 HG Amsterdam, Netherlands
[4] Vrije Univ Amsterdam, Med Ctr, Dept Pathol, POB 7057, NL-1040 HG Amsterdam, Netherlands
[5] Vrije Univ Amsterdam, Med Ctr, Dept Epidemiol & Biostat, POB 7057, NL-1007 MB Amsterdam, Netherlands
[6] Univ Paris Sud, Hop Univ Paris Sud, AP HP, Inserm U1184,Rheumatol Dept,Ctr Immunol Viral Inf, 78 Rue Gen Leclerc, F-94275 Le Kremlin Bicetre, France
关键词
Rheumatoid arthritis; Rituximab; Prediction; Type I interferon; PLASMACYTOID DENDRITIC CELLS; I INTERFERON SIGNATURE; MEMORY B-CELLS; CONTROLLED-TRIAL; GENE-EXPRESSION; DOUBLE-BLIND; TNF AGENTS; EFFICACY; RETREATMENT; THERAPY;
D O I
10.1016/j.jbspin.2017.02.015
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives: To validate the IFN response gene (IRG) set for the prediction of non-response to rituximab in rheumatoid arthritis (RA) and assess the predictive performance upon combination of this gene set with clinical parameters. Methods: In two independent cohorts of 93 (cohort I) and 133 (cohort II) rituximab-starting RA patients, baseline peripheral blood expression of eight IRGs was determined, and averaged into an IFN score. Predictive performance of IFN score and clinical parameters was assessed by logistic regression. A multivariate prediction model was developed using a forward stepwise selection procedure. Patients with a decrease in disease activity score (Delta DAS28) >= 1.8 after 6 months of therapy were considered responders. Results: The mean IFN score was higher in non-responders compared to responders in both cohorts, but this difference was most pronounced in patients who did not use prednisone, as described before. Univariate analysis in cohort I showed that baseline DAS28, IFN score, DMARD use and negativity for IgMRF and/or ACPA were associated with rituximab non-response. The multivariate model consisted of DAS28, IFN score and DMARD use, which showed an area under the curve (AUC) of 0.82. In cohort II, this model revealed a comparable AUC in PREDN-negative patients (0.78), but AUC in PREDN-positive patients was significantly lower (0.63), which seemed due to effect modification of the IFN score by prednisone. Conclusions: Combination of predictive parameters provided a promising model for the prediction of non-response to rituximab, with possibilities for optimization via definition of the exact interfering effect of prednisone on IFN score. (c) 2017 Published by Elsevier Masson SAS on behalf of Societe francaise de rhumatologie.
引用
收藏
页码:219 / 226
页数:8
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