Cost saving and predictive factors of response to rituximab in rheumatoid arthritis, including the IL-6 promoter gene polymorphism

Authors

  • Luca Quartuccio Clinic of Rheumatology, Department of Medical and Biological Sciences (DSMB), Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Sara Salvin Clinic of Rheumatology, Department of Medical and Biological Sciences (DSMB), Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Martina Fabris Insitute of Clinical Pathology, Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Maurizio Benucci Unit of Rheumatology, Ospedale San Giovanni di Dio, Florence, Italy
  • Raffaele Pellerito Unit of Rheumatology, Ospedale Mauriziano, Turin, Italy
  • Cristina Furian Hospital Direction, Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Paola Masolini Clinic of Rheumatology, Department of Medical and Biological Sciences (DSMB), Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Marco Cimmino Clinic of Rheumatology, University of Genova, Italy
  • Maria Grazia Troncon Pharmacy, Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Giovanni Maria Guarrera Hospital Direction, Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy
  • Salvatore De Vita Clinic of Rheumatology, Department of Medical and Biological Sciences (DSMB), Azienda Ospedaliero Universitaria “S. Maria della Misericordia”, Udine, Italy

DOI:

https://doi.org/10.2427/8696

Keywords:

Rheumatoid arthritis, Rituximab, Pharmacogenetic, Quality of life, Biologics

Abstract

Background: to evaluate quality of life (QoL) and cost/utility when using predictors of response in a real-life cohort of rheumatoid arthritis (RA) patients treated with rituximab and followed for one year. A recently reported pharmacogenetic predictor of response was included.

Methods: this was a retrospective study in patients with established RA. The goal of this study was to understand the possible economic usefulness of the predictors of response in RA treated with rituximab. Information on QoL was collected at baseline, at month +6 and +12. Cost/QoL gained were also derived. Rheumatoid factor, number of TNF blockers previously failed (positive predictors) and the -174 CC interleukin-6 (IL-6) promoter genotype (negative predictor) were considered as predictive factors of response to rituximab.

Results: 66 patients (54 females, 12 males) with RA were treated with rituximab at standard regimen. Retreatment with rituximab was given at clinical relapse. Rituximab was generally used after failure of anti-TNFalpha agents (81.8%). 96 courses of rituximab were administered during 12 months. Cost/QoL gained was € 56 589.50 at month +12. Patients carrying predictors (≥2 out of 3) (28/66 patients) showed a cost/QoL gained of € 44 279.10 at month +12. Thirty-four courses of rituximab were administered in this group (1.21±0.42). Patients without predictors (≤1 out of 3) (38/66 patients) showed a cost/QoL gained of € 66 769.23 at month +12. 62 courses of rituximab were administered in this group (1.63±0.59). The number of courses of rituximab during one year significantly differed between the two groups (p=0.003).

Conclusion: predictors of response to rituximab selected those patients who need a lesser amount of rituximab during the first year after treatment. Cost/utility of rituximab in established RA may be optimized by using predictors of response, possibly including pharmacogenetic markers.

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Published

2024-03-12

Issue

Vol. 9 No. 4 (2012)

Section

Theme Papers