Objective. To report the primary (1-year) results from PREVENT, the first phase III study evaluating secukinumab in patients with active nonradiographic axial spondyloarthritis (SpA). Methods. A total of 555 patients were randomized (1:1:1) to receive subcutaneous secukinumab 150 mg with a loading dose (loading dose [LD] group), secukinumab 150 mg without a loading dose (non-loading dose [NL] group), or placebo weekly and then every 4 weeks starting at week 4. The NL group received placebo at weeks 1, 2, and 3 to maintain blinding. Switch to open-label secukinumab or standard of care was permitted after week 20. The study had 2 independent analysis plans, per European Union and non-US (plan A; week 16) and US (plan B; week 52) regulatory requirements. The primary end point was 40% improvement in disease activity according to the Assessment of SpondyloArthritis international Society (ASAS40) criteria at week 16 (in the LD group) and at week 52 (in the NL group) in tumor necrosis factor inhibitor (TNFi)-naive patients. Safety analyses included all patients who received ≥1 dose of study treatment. Results. Overall, 481 patients completed 52 weeks of treatment, including 84.3% (156 of 185) in the LD group, 89.7% (165 of 184) in the NL group, and 86.0% (160 of 186) in the placebo group. The proportion of patients who switched to open-label or standard of care between weeks 20 and 48 was 50.8% in the LD group, 47.3% in the NL group, and 64.0% in the placebo group. Both primary and all secondary end points were met at week 16. The proportion of TNFi-naive patients who met ASAS40 was significantly higher for LD at week 16 (41.5%) and NL at week 52 (39.8%) versus placebo (29.2% at week 16 and 19.9% at week 52; both P < 0.05). No new safety findings were reported. Conclusion. Our findings indicate that secukinumab 150 mg provides significant and sustained improvement in signs and symptoms of nonradiographic axial SpA through 52 weeks. Safety was consistent with previous reports.

A widely used method in classic random-effects meta-analysis is the DerSimonian-Laird method. An alternative meta-analytical approach is the Hartung-Knapp method. This article reports results of an empirical comparison and a simulation study of these two methods and presents corresponding analytical results. For the empirical evaluation, we took 157 meta-analyses with binary outcomes, analysed each one using both methods and performed a comparison of the results based on treatment estimates, standard errors and associated P-values. In several simulation scenarios, we systematically evaluated coverage probabilities and confidence interval lengths. Generally, results are more conservative with the Hartung-Knapp method, giving wider confidence intervals and larger P-values for the overall treatment effect. However, in some meta-analyses with very homogeneous individual treatment results, the Hartung-Knapp method yields narrower confidence intervals and smaller P-values than the classic random-effects method, which in this situation, actually reduces to a fixed-effect meta-analysis. Therefore, it is recommended to conduct a sensitivity analysis based on the fixed-effect model instead of solely relying on the result of the Hartung-Knapp random-effects meta-analysis. Copyright © 2016 John Wiley & Sons, Ltd.

BackgroundFatigue is one of the most debilitating symptoms in multiple sclerosis (MS) considerably interfering with patients’ daily functioning. Both researchers and clinicians need psychometrically robust methods to evaluate fatigue in MS.ObjectivesThe objective of this study was (i) to evaluate the psychometric properties of the Finnish version of the Fatigue Severity Scale (FSS) and (ii) to describe the results among patients with MS.MethodsIn total, 553 patients with MS (mean age, 53.8 years; standard deviation [SD], 11.4; 79% women: mean patient‐defined disease severity, Expanded Disability Status Scale [EDSS] 4.0, SD, 2.5) completed the self‐administered questionnaires including the FSS. A standard procedure was used for the translation of the FSS.ResultsThe mean (SD) score for the FSS was 4.5 (1.7); in 65% of the patients, the score was ≥4.0. The data quality of the FSS was excellent, with 99.6% of computable scale scores. Floor and ceiling effects were minimal. The FSS showed high internal consistency (Cronbach's alpha, 0.95). Unidimensionality was supported based on confirmatory factor analysis with the comparative fit index being 0.94. The FSS showed moderate/high correlations with the perceived burden of the disease, quality of life and disease severity, whereas, age or gender did not have a significant effect on the FSS score.ConclusionsThe Finnish version of the FSS showed satisfactory reliability and validity and thus can be regarded as a feasible measure of self‐reported fatigue.

Background To investigate the efficacy of secukinumab in patients with active non-radiographic axial spondyloarthritis (nr-axSpA) grouped by disease activity as assessed by C-reactive protein (CRP) levels and/or magnetic resonance imaging (MRI) scores, human leukocyte antigen (HLA)-B27 status, and sex. Methods The phase III PREVENT study randomized (1:1:1) 555 patients to receive subcutaneous secukinumab 150 mg with (LD) or without (NL) loading dose or placebo weekly, followed by every 4 weeks starting at week 4. Here, we report the results of a post hoc analysis reporting the efficacy outcomes (pooled secukinumab) to 16 weeks by CRP, MRI, HLA-B27, and sex. Results Efficacy differences between the secukinumab and the placebo groups were highest in the CRP+, MRI+, HLA-B27+, and male subgroups, particularly for Ankylosing Spondylitis Disease Activity Score-CRP inactive disease and Assessment of SpondyloArthritis international Society (ASAS) partial remission outcomes. ASAS40 response rates in the CRP+/MRI+ subgroup was 52.3% (secukinumab) versus 21.8% (placebo; P < 0.0001) at week 16. ASAS40 response rates (secukinumab versus placebo) were 43.9% versus 32.6% in HLA-B27+, 32.7% versus 16.4% in HLA-B27− subgroups, 51.2% versus 30.8% in male, and 31.7% versus 25.3% in female patients, respectively. Conclusions Secukinumab improved the signs and symptoms of nr-axSpA across patients grouped by CRP (+/−) and/or MRI (+/−) status, HLA-B27 (+/−) status, and sex. The highest treatment differences between secukinumab and placebo were observed in patients with both elevated CRP and evidence of sacroiliitis on MRI. Treatment difference was minimal between HLA-B27 (+) and (−) subgroups. Male patients had higher relative responses than female patients. Trial registration ClinicalTrials.gov, NCT02696031. Registered on 02 March 2016

Objectives: To develop efficient approaches for fitting network meta-analysis (NMA) models with time-varying hazard ratios (such as fractional polynomials and piecewise constant models) to allow practitioners to investigate a broad range of models rapidly and to achieve a more robust and comprehensive model selection strategy.Methods: We reformulated the fractional polynomial and piecewise constant NMA models using analysis of variance-like parameterization. With this approach, both models are expressed as generalized linear models (GLMs) with time-varying covariates. Such models can be fitted efficiently with standard frequentist techniques. We applied our approach to the example data from the study by Jansen et al, in which fractional polynomial NMA models were introduced.Results: Fitting frequentist fixed-effect NMAs for a large initial set of candidate models took less than 1 second with standard GLM routines. This allowed for model selection from a large range of hazard ratio structures by comparing a set of criteria including Akaike information criterion/Bayesian information criterion, visual inspection of goodness-of-fit, and long-term extrapolations. The "best" models were then refitted in a Bayesian framework. Estimates agreed very closely.Conclusions: NMA models with time-varying hazard ratios can be explored efficiently with a stepwise approach. A frequentist fixed-effect framework enables rapid exploration of different models. The best model can then be assessed further in a Bayesian framework to capture and propagate uncertainty for decision-making.