title: Combination of B cell biomarkers as independent predictors of response in patients with rheumatoid arthritis treated with rituximab.
abstract: OBJECTIVE
  Identification of B cell biomarkers predictive of response prior to therapy with rituximab (RTX) and evaluation of the efficacy of long-term treatment in patients with rheumatoid arthritis (RA).
  
  
  METHODS
  302 RA patients failing one TNFi were treated with two applications of 1000 mg RTX (FIRST study). During the follow-up study (ReFIRST) the patients were treated for up to three more courses if they showed measurable clinical response but RA was still active. In a substudy on 154 RA patients peripheral B cell subsets were determined by flow cytometry before starting RTX. Rheumatoid factor (RF), RF-isotypes and anti-citrullinated protein antibodies (ACPA) were also measured.
  
  
  RESULTS
  Based on multivariate analyses patients with positive RF and normal (>lower limit) levels of CD19⁺ B cells (RF⁺CD19⁺) showed better treatment effects compared to patients who had only one or none of those parameters. Considering the RF status of the patients, analysis of B cell subpopulations yielded a correlation between higher ER rates and "double negative" CD19+CD27⁻IgD⁻ B cells. Lowest ER rates were observed for RF negative patients in combination with low numbers of CD19⁺CD27⁻IgD⁻ B cells as independent risk factors, thus defining a group with lower responses. Conversely, higher CD19⁺CD27⁻IgD⁻ B cells identified a responder group within RF negative patients.
  
  
  CONCLUSIONS
  The data of this large biomarker study suggest that beyond RF positivity, normal levels of CD19⁺ B cells together with increased CD19⁺CD27⁻IgD⁻ B cells predict response to RTX in RA, in particular when all parameters were present.
authors.affiliation: Department of Rheumatology and Immunology, University of Würzburg, Germany. tony_h@medizin.uni-wuerzburg.de.
authors.forename: H-P
authors.initials: HP
authors.lastname: Tony
authors.affiliation: Department of Rheumatology and Immunology, University of Würzburg, Germany.
authors.forename: P
authors.initials: P
authors.lastname: Roll
authors.affiliation: Hospital for Rheumatology and Clinical Immunology Berlin, and DRFZ, Berlin, Germany.
authors.forename: H E
authors.initials: HE
authors.lastname: Mei
authors.affiliation: Ecron Acunova GmbH, Frankfurt, Germany.
authors.forename: E
authors.initials: E
authors.lastname: Blümner
authors.affiliation: Ecron Acunova GmbH, Frankfurt, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Straka
authors.affiliation: Roche Pharma AG, Grenzach-Wyhlen, Germany.
authors.forename: L
authors.initials: L
authors.lastname: Gnuegge
authors.affiliation: Hospital for Rheumatology and Clinical Immunology Berlin, and DRFZ, Berlin, Germany.
authors.forename: T
authors.initials: T
authors.lastname: Dörner
mesh_terms: D000328:Adult; D000368:Aged; D018941:Antigens, CD19 / Q000032:analysis / Q000276:immunology; D018501:Antirheumatic Agents / Q000008:administration & dosage / Q000009:adverse effects / Q000276:immunology; D001172:Arthritis, Rheumatoid / Q000097:blood / Q000175:diagnosis / Q000188:drug therapy; D016175:B-Lymphocyte Subsets / Q000276:immunology*; D015415:Biomarkers / Q000032:analysis; D016903:Drug Monitoring / Q000379:methods; D005260:Female; D005858:Germany; D006801:Humans; D008297:Male; D008875:Middle Aged; D015166:Monitoring, Immunologic; D011237:Predictive Value of Tests; D011379:Prognosis; D012217:Rheumatoid Factor / Q000097:blood; D000069283:Rituximab / Q000008:administration & dosage / Q000009:adverse effects / Q000276:immunology; D016896:Treatment Outcome; D018127:Tumor Necrosis Factor Receptor Superfamily, Member 7 / Q000032:analysis / Q000276:immunology
chemical_list: D018941:Antigens, CD19; D018501:Antirheumatic Agents; D015415:Biomarkers; D018127:Tumor Necrosis Factor Receptor Superfamily, Member 7; D000069283:Rituximab; D012217:Rheumatoid Factor