Baseline ADAS-cog is a significant covariate affecting the rate of disease progression, and it describes or at least explains the different rates of deterioration evident in early or late stages of the disease. There was no significant impact of publication year in the model, suggesting that disease progression has not slowed in more recent trials.

BackgroundTofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). Tofacitinib modulates the signaling of cytokines that are integral to lymphocyte activation, proliferation, and function. Thus, tofacitinib therapy may result in suppression of multiple elements of the immune response. Serious infections have been reported in tofacitinib RA trials. However, limited head-to-head comparator data were available within the tofacitinib RA development program to directly compare rates of serious infections with tofacitinib relative to biologic agents, and specifically adalimumab (employed as an active control agent in two randomized controlled trials of tofacitinib).MethodsA systematic literature search of data from interventional randomized controlled trials and long-term extension studies with biologics in RA was carried out. Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) consensus was followed for reporting results of the review and meta-analysis. Incidence rates (unique patients with events/100 patient-years) for each therapy were estimated based on data from randomized controlled trials and long-term extension studies using a random-effects model. Relative and absolute risk comparisons versus placebo used Mantel-Haenszel methods.ResultsThe search produced 657 hits. In total, 66 randomized controlled trials and 22 long-term extension studies met the selection criteria. Estimated incidence rates (95 % confidence intervals [CIs]) for abatacept, rituximab, tocilizumab, and tumor necrosis factor inhibitors were 3.04 (2.49, 3.72), 3.72 (2.99, 4.62), 5.45 (4.26, 6.96), and 4.90 (4.41, 5.44), respectively. Incidence rates (95 % CIs) for tofacitinib 5 and 10 mg twice daily (BID) in phase 3 trials were 3.02 (2.25, 4.05) and 3.00 (2.24, 4.02), respectively. Corresponding incidence rates in long-term extension studies were 2.50 (2.05, 3.04) and 3.19 (2.74, 3.72). The risk ratios (95 % CIs) versus placebo for tofacitinib 5 and 10 mg BID were 2.21 (0.60, 8.14) and 2.02 (0.56, 7.28), respectively. Risk differences (95 % CIs) versus placebo for tofacitinib 5 and 10 mg BID were 0.38 % (−0.24 %, 0.99 %) and 0.40 % (−0.22 %, 1.02 %), respectively.ConclusionsIn interventional studies, the risk of serious infections with tofacitinib is comparable to published rates for biologic disease-modifying antirheumatic drugs in patients with moderate to severely active RA.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0880-2) contains supplementary material, which is available to authorized users.

Aggregate data model‐based meta‐analysis is a regression approach to compare the dose–response and/or time‐course across different treatments using summary level data from the literature. Literature search and systematic review following the Cochrane approach yielded 912 sources for investigational and approved treatments for psoriasis. In addition, data for tofacitinib were obtained from an internal database. Tofacitinib is an oral Janus kinase inhibitor. Two mathematical models were developed for Psoriasis Area and Severity Index (PASI) response in moderate to severe psoriasis patients to quantify the time to maximum effect for PASI75 and to evaluate the dose–response relationship for PASI responders (PASI50, PASI75, PASI90, PASI100) at Week 12. Body weight exhibited an inverse effect on the placebo component of both models, suggesting that body weight affects the overall PASI response regardless of drug. This analysis provides a quantitative framework for efficacy comparisons across psoriasis treatments.

Although well developed to assess efficacy questions, meta-analyses and, more generally, systematic reviews, have received less attention in application to safety-related questions. As a result, many open questions remain on how best to apply meta-analyses in the safety setting. This appraisal attempts to: (i) summarize the current guidelines for assessing individual studies, systematic reviews, and network meta-analyses; (ii) describe several publications on safety meta-analytic approaches; and (iii) present some of the questions and issues that arise with safety data. A number of gaps in the current quality guidelines are identified along with issues to consider when performing a safety meta-analysis. While some work is ongoing to provide guidance to improve the quality of safety meta-analyses, this review emphasizes the critical need for better reporting and increased transparency regarding safety data in the systematic review guidelines. Copyright © 2016 John Wiley & Sons, Ltd.