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OP0276 Risk of Serious Adverse Effects Associated with Different Biological and Targeted Synthetic Disease-Modifying Anti-Rheumatic Drugs in Patients with Rheumatoid Arthritis: A Systematic Review and Meta-Analysis of Randomised Trials
  1. S. Tarp1,
  2. D.E. Furst2,
  3. G. Luta3,
  4. M. Boers4,
  5. U. Tarp5,
  6. K.H. Asmussen6,
  7. H. Bliddal1,
  8. B. Brock7,
  9. A. Døssing1,
  10. T.S. Jørgensen1,
  11. S. Thirstrup8,
  12. R. Christensen1
  1. 1The Parker Institute, Department of Rheumatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark
  2. 2David Geffen School of Medicine, University of California, Los Angeles
  3. 3Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, DC, United States
  4. 4Department of Epidemiology and Biostatistics, and Amsterdam Rheumatology and Immunology Center, VU University Medical Center, Amsterdam, Netherlands
  5. 5Department of Rheumatology, Aarhus University Hospital, Aarhus
  6. 6Department of Rheumatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg
  7. 7Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus
  8. 8Institute for Pharmacology and Pharmacotherapy, University of Copenhagen, Copenhagen, Denmark

Abstract

Background Large pivotal randomised controlled trials (RCTs) in rheumatoid arthritis (RA) increasingly employ “adaptive” designs that allow early dropout in the comparator group (effectively placebo). Such designs frequently result in unbalanced and high dropout rates that compromise inference from meta-analysis, especially on adverse events.

Objectives To evaluate and compare risk of serious adverse effects associated with treatment of currently EMA and/or FDA approved biologics and targeted synthetic DMARDs for RA based on data from randomised trials with an explicit goal of adjusting for the skewed dropout between groups1.

Methods Through a systematic literature search, RA RCTs evaluating biologics or targeted synthetic DMARDs were identified. Major outcome was risk of serious adverse events (SAEs) adjusted for follow-up time based on the number of subjects experiencing an event and person-years – expressed as rate ratios with 95% confidence intervals. If person-years were not reported, it was estimated by assuming a linear dropout rate from baseline to follow-up. A network meta-analysis was performed with a mixed effects Poisson regression model (with study as a random and treatment as a fixed effect). As a sensitivity analysis, we explored the effect of dose (recommended/low/high), as well as the impact of concomitant use of conventional synthetic DMARDs (y/n), and adjusted for these factors in the model.

Results From 176 identified RCTs meeting our eligibility criteria, 46 RCTs did not report data on SAEs and 15 were unpublished. Thus, the meta-analysis included 115 trials (319 trial-arms; 47,327 patients; approx. 30,045 person-years): abatacept (16), adalimumab (36), anakinra (2), certolizumab (16), etanercept (27), golimumab (21), infliximab (17), rituximab (13), and tocilizumab (29), tofacitinib (36), and placebo/control (106) arms. The risk of SAEs was statistically significantly higher (P<0.05) for certolizumab compared with: placebo/control, abatacept, adalimumab, etanercept, golimumab, rituximab, and tofacitinib (see table). The risk for SAEs was statistically significantly lower for etanercept compared to tocilizumab. Confidence in the estimates was downgraded because of indirectness (lack of head-2-head trials) and risk of bias due to selective outcome reporting (i.e. low quality evidence).

Conclusions This network meta-analysis of available RCTs (accounting for person-years) provides empirical evidence that certolizumab is associated with an increased risk of SAEs compared with placebo/control, several biologics, and tofacitinib for RA; although our confidence in the estimates is limited (i.e. the true effects may be substantially different).

References

  1. PROSPERO CRD42014014842

Acknowledgements This study was supported by unrestricted grants from The Oak Foundation and indirectly by The Danish Health and Medicines Authority

Disclosure of Interest S. Tarp Grant/research support from: paid to institute: AbbVie and Roche, Speakers bureau: paid to institute: Pfizer and MSD, D. Furst Grant/research support from: AbbVie, Actelion, Amgen, BMS, Gilead, GSK, NIH, Novartis, Pfizer, Roche/Genentech, UCB, Consultant for: AbbVie, Actelion, Amgen, BMS, Janssen, Gilead, GSK, NIH, Novartis, Pfizer, Roche/Genentech, UCB, Speakers bureau: AbbVie, Actelion, UCB, G. Luta: None declared, M. Boers: None declared, U. Tarp Grant/research support from: paid to the institute: MSD, Speakers bureau: Pfizer, UCB, Roche, MSD, K. Asmussen Consultant for: MSD, Pfizer, AbbVie, Novartis, UCB, H. Bliddal Grant/research support from: AbbVie, BMS, AstraZeneca, Daiichi Sankyo, GSK, Grünenthal, Lilly, MSD, Mundipharma, Nycomed, NOVO, Piere Fabre, Pfizer, Roche, Sanofi Aventis, Schering-Plough, Takeda, Wyeth, Consultant for: AbbVie, Hospira, Celgene AstraZeneca, Grünenthal, Lilly, Mundipharma, Nycomed, Pfizer, Roche, Wyeth, B. Brock Grant/research support from: paid to institution: Novo, Consultant for: Novo, Allergen, Speakers bureau: Pfizer, A. Dossing: None declared, T. Jørgensen Grant/research support from: paid to institute: Roche, AbbVie, S. Thirstrup Employee of: works as a regulatory consultant at NDA Regulatory Services Ltd, but does not receive fees directly from pharmaceutical companies, R. Christensen Grant/research support from: paid to institute AbbVie, Janssen, MSD, MundiPharma, Roche, Consultant for: paid to institute AbbVie, BMS, Eli Lilly, MSD, Norpharma, Pfizer, Roche, Speakers bureau: paid to institute AbbVie, Bayer HealthCare Pharmaceuticals, BMS, Janssen, MSD, MundiPharma, Novartis, Pfizer, Roche, Wyeth

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