Risk of harm in synthetic and biological intervention trials in patients with inflammatory arthritis: protocol for a metaepidemiological study focusing on contextual factors

Introduction Inflammatory arthritis (IA) conditions, including rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis, are characterised by inflammatory infiltration of the joints. Biological disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs), respectively, reduce the effects of proinflammatory cytokines and immune cells to ameliorate disease. However, immunosuppression can be associated with high rates of serious adverse events (SAEs), including serious infections, and maybe an increased risk of malignancies and cardiovascular events. Currently, there is no empirical evidence on the extent to which contextual factors and risk of bias (RoB) domains may modify these harm signals in randomised trials. Methods and analysis We will search MEDLINE (via PubMed) for systematic reviews published since April 2015 and all Cochrane reviews. From these reviews, randomised trials will be eligible if they include patients with an IA condition with at least one group randomly allocated to bDMARD and/or tsDMARD treatments. A predefined form will be used for extracting data on population characteristics (eg, baseline characteristics or eligibility criteria, such as medication background) and specific harm outcome measures, such as number of withdrawals, numbers of patients discontinuing due to adverse events and number of patients having SAEs. RoB in individual trials will be assessed using a modified Cochrane RoB tool. We will estimate the potentially causal harm effects related to the experimental intervention compared with control comparator as risk ratios, and heterogeneity across randomised comparisons will be assessed statistically and evaluated as inconsistency using the I2 Index. Our metaregression analyses will designate population and trial characteristics and each RoB domain as independent variables, whereas the three harm domains will serve as dependent variables. Ethics and dissemination Ethics approval is not required for this study. Results will be disseminated through publication in international peer-reviewed journals. PROSPERO registration number CRD42020171124.

[1]  P. Tugwell,et al.  Towards consensus in defining and handling contextual factors within rheumatology trials: an initial qualitative study from an OMERACT working group , 2020, Annals of the Rheumatic Diseases.

[2]  J. Kremer,et al.  Incidence of venous and arterial thromboembolic events reported in the tofacitinib rheumatoid arthritis, psoriasis and psoriatic arthritis development programmes and from real-world data , 2020, Annals of the Rheumatic Diseases.

[3]  T. Dilla,et al.  Cost-effectiveness analysis of ixekizumab versus secukinumab in patients with psoriatic arthritis and concomitant moderate-to-severe psoriasis in Spain , 2020, BMJ Open.

[4]  P. Tugwell,et al.  Assessing the effect of interventions for axial spondyloarthritis according to the endorsed ASAS/OMERACT core outcome set: a meta-research study of trials included in Cochrane reviews , 2020, Arthritis Research & Therapy.

[5]  B. Wieseler,et al.  Comparative effectiveness of biological medicines in rheumatoid arthritis: systematic review and network meta-analysis including aggregate results from reanalysed individual patient data , 2020, BMJ.

[6]  P. Tugwell,et al.  Population characteristics as important contextual factors in rheumatological trials: an exploratory meta-epidemiological study from an OMERACT Working Group , 2020, Annals of the Rheumatic Diseases.

[7]  R. Luqmani,et al.  SAT0619-HPR AN AUDIT OF GLUCOCORTICOID PRESCRIPTION IN PATIENTS WITH GIANT CELL ARTERITIS , 2020 .

[8]  R. Christensen,et al.  Causal inference from meta-epidemiology: a reasonable goal, or wishful thinking? , 2020, Journal of clinical epidemiology.

[9]  L. Mbuagbaw,et al.  Tumor Necrosis Factor Inhibitor Dose Reduction for Axial Spondyloarthritis: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials , 2020, Arthritis care & research.

[10]  M. Dougados,et al.  Safety of synthetic and biological DMARDs: a systematic literature review informing the 2019 update of the EULAR recommendations for the management of rheumatoid arthritis , 2020, Annals of the Rheumatic Diseases.

[11]  P. Sarzi-Puttini,et al.  Systemic rheumatic diseases: From biological agents to small molecules. , 2019, Autoimmunity reviews.

[12]  M. Boers,et al.  Adaptive Trial Designs in Rheumatology: Report from the OMERACT Special Interest Group , 2019, The Journal of Rheumatology.

[13]  O. Silvennoinen,et al.  Janus kinases to jakinibs: from basic insights to clinical practice. , 2019, Rheumatology.

[14]  M. Nørgaard,et al.  Risk of serious infections in patients with rheumatoid arthritis treated in routine care with abatacept, rituximab and tocilizumab in Denmark and Sweden , 2019, Annals of the rheumatic diseases.

[15]  Anthony So,et al.  An overview of biologic disease-modifying antirheumatic drugs in axial spondyloarthritis and psoriatic arthritis. , 2018, Best practice & research. Clinical rheumatology.

[16]  A. Gottlieb,et al.  Trial Characteristics as Contextual Factors When Evaluating Targeted Therapies in Patients With Psoriatic Disease: A Meta‐Epidemiologic Study , 2018, Arthritis care & research.

[17]  W. Lems,et al.  Harm, benefit and costs associated with low-dose glucocorticoids added to the treatment strategies for rheumatoid arthritis in elderly patients (GLORIA trial): study protocol for a randomised controlled trial , 2018, Trials.

[18]  P. Tugwell,et al.  Some Cochrane risk-of-bias items are not important in osteoarthritis trials: a meta-epidemiological study based on Cochrane reviews. , 2017, Journal of clinical epidemiology.

[19]  P. Tugwell,et al.  An OMERACT Initiative Toward Consensus to Identify and Characterize Candidate Contextual Factors: Report from the Contextual Factors Working Group , 2017, The Journal of Rheumatology.

[20]  A. Luster,et al.  LTB4 and BLT1 in inflammatory arthritis. , 2017, Seminars in immunology.

[21]  N. Snowden,et al.  Diagnosis and early management of inflammatory arthritis , 2017, British Medical Journal.

[22]  G. Wells,et al.  Celecoxib for rheumatoid arthritis. , 2017, The Cochrane database of systematic reviews.

[23]  M. Suarez‐Almazor,et al.  Biologics or tofacitinib for people with rheumatoid arthritis naive to methotrexate: a systematic review and network meta-analysis. , 2017, The Cochrane database of systematic reviews.

[24]  A. Ido,et al.  Efficacy, safety and pharmacokinetics of biosimilars of anti-tumor necrosis factor-α agents in rheumatic diseases; A systematic review and meta-analysis. , 2017, Journal of autoimmunity.

[25]  K. Winthrop The emerging safety profile of JAK inhibitors in rheumatic disease , 2017, Nature Reviews Rheumatology.

[26]  M. Suarez‐Almazor,et al.  Biologics or tofacitinib for people with rheumatoid arthritis unsuccessfully treated with biologics: a systematic review and network meta-analysis. , 2017, The Cochrane database of systematic reviews.

[27]  M. Boers,et al.  Risk of serious adverse effects of biological and targeted drugs in patients with rheumatoid arthritis: a systematic review meta-analysis , 2016, Rheumatology.

[28]  Marien González-Lorenzo,et al.  Risk of infections using anti-TNF agents in rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis: a systematic review and meta-analysis , 2016, Expert opinion on drug safety.

[29]  P. Tugwell,et al.  Biologic or tofacitinib monotherapy for rheumatoid arthritis in people with traditional disease-modifying anti-rheumatic drug (DMARD) failure: a Cochrane Systematic Review and network meta-analysis (NMA). , 2016, The Cochrane database of systematic reviews.

[30]  P. Shekelle,et al.  Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation , 2016, British Medical Journal.

[31]  J. Beyene,et al.  Modified intention-to-treat analysis did not bias trial results. , 2016, Journal of clinical epidemiology.

[32]  C. Oo,et al.  Leveraging the attributes of biologics and small molecules, and releasing the bottlenecks: a new wave of revolution in drug development , 2016, Expert review of clinical pharmacology.

[33]  D. Furst,et al.  Most Trial Eligibility Criteria and Patient Baseline Characteristics Do Not Modify Treatment Effect in Trials Using Targeted Therapies for Rheumatoid Arthritis: A Meta-Epidemiological Study , 2015, PloS one.

[34]  P. Tugwell,et al.  Risk of serious infection in biological treatment of patients with rheumatoid arthritis: a systematic review and meta-analysis , 2015, The Lancet.

[35]  P. Shekelle,et al.  Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation , 2015, BMJ : British Medical Journal.

[36]  J. Bae Meta-epidemiology , 2014, Epidemiology and health.

[37]  P. Tugwell,et al.  Developing core outcome measurement sets for clinical trials: OMERACT filter 2.0. , 2014, Journal of clinical epidemiology.

[38]  D. Symmons,et al.  Development of EULAR recommendations for the reporting of clinical trial extension studies in rheumatology , 2014, Annals of the rheumatic diseases.

[39]  J. Listing,et al.  Efficacy of TNFα blockers in patients with ankylosing spondylitis and non-radiographic axial spondyloarthritis: a meta-analysis , 2014, Annals of the rheumatic diseases.

[40]  A. Deodhar,et al.  The classification and diagnostic criteria of ankylosing spondylitis. , 2014, Journal of autoimmunity.

[41]  J. Gómez-Reino,et al.  Safety profile of protein kinase inhibitors in rheumatoid arthritis: systematic review and meta-analysis , 2013, Annals of the rheumatic diseases.

[42]  Gordon H Guyatt,et al.  GRADE guidelines: 12. Preparing summary of findings tables-binary outcomes. , 2013, Journal of clinical epidemiology.

[43]  T. Barnetche,et al.  Effect of tumour necrosis factor blockers on radiographic progression of psoriatic arthritis: a systematic review and meta-analysis of randomised controlled trials , 2013, Annals of the rheumatic diseases.

[44]  Ethan M Balk,et al.  Influence of Reported Study Design Characteristics on Intervention Effect Estimates From Randomized, Controlled Trials , 2012, Annals of Internal Medicine.

[45]  J. Sterne,et al.  The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials , 2011, BMJ : British Medical Journal.

[46]  Isabelle Boutron,et al.  Single-Center Trials Show Larger Treatment Effects Than Multicenter Trials: Evidence From a Meta-epidemiologic Study , 2011, Annals of Internal Medicine.

[47]  Mahboob Rahman,et al.  Changes in patient characteristics in anti-tumour necrosis factor clinical trials for rheumatoid arthritis: results of an analysis of the literature over the past 16 years , 2011 .

[48]  G. Guyatt,et al.  Adverse effects of biologics: a network meta-analysis and Cochrane overview. , 2011, The Cochrane database of systematic reviews.

[49]  Douglas G Altman,et al.  Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study , 2010, BMJ : British Medical Journal.

[50]  A. Koch The pathogenesis of rheumatoid arthritis. , 2007, American journal of orthopedics.

[51]  I. Buchan,et al.  Anti-TNF antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in randomized controlled trials. , 2006, JAMA.

[52]  L. Gluud Bias in clinical intervention research. , 2006, American journal of epidemiology.

[53]  Simon G Thompson,et al.  Can meta-analysis help target interventions at individuals most likely to benefit? , 2005, The Lancet.

[54]  Larry V Hedges,et al.  The power of statistical tests for moderators in meta-analysis. , 2004, Psychological methods.

[55]  J. Ioannidis,et al.  Better Reporting of Harms in Randomized Trials: An Extension of the CONSORT Statement , 2004, Annals of Internal Medicine.

[56]  Alexander J Sutton,et al.  What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. , 2004, Statistics in medicine.

[57]  D. Altman,et al.  Measuring inconsistency in meta-analyses , 2003, BMJ : British Medical Journal.

[58]  S. Thompson,et al.  How should meta‐regression analyses be undertaken and interpreted? , 2002, Statistics in medicine.

[59]  Douglas G Altman,et al.  Statistical methods for assessing the influence of study characteristics on treatment effects in ‘meta‐epidemiological’ research , 2002, Statistics in medicine.

[60]  Theo Stijnen,et al.  Advanced methods in meta‐analysis: multivariate approach and meta‐regression , 2002, Statistics in medicine.

[61]  Harold I Feldman,et al.  Individual patient‐ versus group‐level data meta‐regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head , 2002, Statistics in medicine.

[62]  Christian Gluud,et al.  Reported Methodologic Quality and Discrepancies between Large and Small Randomized Trials in Meta-Analyses , 2001, Annals of Internal Medicine.

[63]  L. Hedges,et al.  The power of statistical tests in meta-analysis. , 2001, Psychological methods.

[64]  S L Normand,et al.  Meta-analysis: formulating, evaluating, combining, and reporting. , 1999, Statistics in medicine.

[65]  W. G. Cochran The combination of estimates from different experiments. , 1954 .

[66]  Sergio Sismondo,et al.  Industry sponsorship and research outcome. , 2012, The Cochrane database of systematic reviews.

[67]  Katja Jasinskaja,et al.  Elaboration and Explanation ⋆ , 2011 .