Risk of harm in synthetic and biological intervention trials in patients with inflammatory arthritis: protocol for a metaepidemiological study focusing on contextual factors release_ba2n26cikze6xjxsi4b3ghkkre

Abstract

<jats:sec><jats:title>Introduction</jats:title>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.</jats:sec><jats:sec><jats:title>Methods and analysis</jats:title>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 I<jats:sup>2</jats:sup> 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.</jats:sec><jats:sec><jats:title>Ethics and dissemination</jats:title>Ethics approval is not required for this study. Results will be disseminated through publication in international peer-reviewed journals.</jats:sec><jats:sec><jats:title>PROSPERO registration number</jats:title>CRD42020171124.</jats:sec>
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