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Comparative efficacy of disease-modifying therapies for patients with relapsing remitting multiple sclerosis: Systematic review and network meta-analysis

Multiple Sclerosis and Related Disorders, Volume 9, September 2016, Pages 23 - 30

Abstract

Introduction

Randomised studies have demonstrated efficacy of disease-modifying therapies in relapsing remitting multiple sclerosis (RRMS). However it is unclear how the magnitude of treatment efficacy varies across all currently available therapies.

Objective

To perform a systematic review and network meta-analysis to evaluate the comparative efficacy of available therapies in reducing relapses and disability progression in RRMS.

Methods

A systematic review identified 28 randomised, placebo-controlled and direct comparative trials. A network meta-analysis was conducted within a Bayesian framework to estimate comparative annualised relapse rates (ARR) and risks of disability progression (defined by both a 3-month, and 6-month confirmation interval). Potential sources of treatment-effect modification from study-level covariates and baseline risk were evaluated through meta-regression methods. The Surface Under the Cumulative RAnking curve (SUCRA) method was used to provide a ranking of treatments for each outcome.

Results

The magnitude of ARR reduction varied between 15–36% for all interferon-beta products, glatiramer acetate and teriflunomide, and from 50 to 69% for alemtuzumab, dimethyl fumarate, fingolimod and natalizumab. The risk of disability progression (3-month) was reduced by 19–28% with interferon-beta products, glatiramer acetate, fingolimod and teriflunomide, by 38–45% for pegylated interferon-beta, dimethyl fumarate and natalizumab and by 68% with alemtuzumab. Broadly similar estimates for the risk of disability progression (6-month), with the exception of interferon-beta-1b 250 mcg which was much more efficacious based on this definition. Alemtuzumab and natalizumab had the highest SUCRA scores (97% and 95% respectively) for ARR, while ranking for disability progression varied depending on the definition of the outcome. Interferon-beta-1b 250 mcg ranked among the most efficacious treatments for disability progression confirmed after six months (92%) and among the least efficacious when the outcome was confirmed after three months (30%). No significant modification of relative treatment effects was identified from study-level covariates or baseline risk.

Conclusion

Compared with placebo, clear reductions in ARR with disease-modifying therapies were accompanied by more uncertain changes in disability progression. The magnitude of the reduction and the uncertainty associated with treatment effects varied between DMTs. While natalizumab and alemtuzumab demonstrated consistently high ranking across outcomes, with older interferon-beta and glatiramer acetate products ranking lowest, variation in disability progression definitions lead to variation in the relative ranking of treatments. Rigorously conducted comparative studies are required to fully evaluate the comparative treatment effects of disease modifying therapies for RRMS.

Highlights

  • Comparative efficacy of disease-modifying therapies in relapsing remitting multiple sclerosis was evaluated.
  • A systematic review and network meta-analysis of 26 randomised controlled trials was conducted.
  • Reductions in annualised relapse rate ranged from 15 to 69%, and from 19 to 68% in disability progression.
  • The magnitude of reductions varied between DMTs with variation in outcome definition leading to variation in treatment rankings.

Keywords: Network meta-analysis, Systematic review, Disease-modifying therapy, Multiple sclerosis, Disability progression, Relapse.

1. Introduction

Multiple sclerosis (MS) is a chronic, autoimmune, disabling disease of the central nervous system. Relapses and disability progression are the clinical hallmarks of MS and the two most commonly assessed clinical endpoints used to evaluate therapeutic interventions in clinical trials (European Medicines Agency (EMA) Committee for Medicinal Products for Human Use (CHMP), 2006). Relapses represent focal, acute, recurrent inflammation, and are characterised by a gradual onset of symptoms which stabilise over days or weeks and resolve gradually, either completely or partially (Coles, 2009). Progression refers to the steady and irreversible worsening of symptoms and signs independent of the occurrence of relapses resulting from diffuse, early, chronic, progressive neurodegeneration (Confavreux and Vukusic, 2006a). The efficacy of disease-modifying therapies (DMTs) on these clinical endpoints has been demonstrated in clinical trials over the last two decades, however few trials have assessed the comparative effectiveness of DMTs. We conducted a systematic review and Bayesian network meta-analysis considering all placebo-controlled and comparative trials of DMTs, to evaluate their comparative efficacy in reducing the risk of relapse and disability progression in MS.

2. Methods

2.1. Literature search and study selection

A systematic search of the published literature was conducted from inception to March 2016 to identify eligible studies using EMBASE, MEDLINE (via PubMed) and CENTRAL (via Cochrane Library) databases. In addition, the Food and Drug Administration (FDA) and European Medicines Agency (EMA) websites were searched for reviews and assessment reports on interventions of interest. For inclusion in the analysis, randomised controlled trials (RCTs) were required to include adult patients with relapsing remitting MS (RRMS), report at least one of the primary outcome measures of interest, and compare DMTs which are authorised by US and/or European regulatory agencies for the treatment of RRMS. Eleven DMTs met this criterion including interferon beta-1b (IFN β-1b) subcutaneous (SC) 250 mcg, IFN β-1a SC 22 mcg and IFN β-1a SC 44 mcg, IFN β-1a intramuscular (IM) 30 mcg, pegylated IFN β-1a SC 125 mcg, glatiramer acetate 20 mg, glatiramer acetate 40 mg, natalizumab, alemtuzumab, fingolimod, teriflunomide, and dimethyl fumarate. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was followed for our network-meta analysis protocol (Moher et al., 2009). The full search strategy, inclusion and exclusion criteria are detailed in Additional File 1.

2.2. Outcome measures

Annualised relapse rate (ARR) and confirmed disability progression were selected as the most commonly reported clinical outcomes in RRMS trials. ARR is defined as the mean number of confirmed relapses per patient adjusted for the duration of follow-up. Definitions of relapse and disability progression were as per the individual trial(s), and are detailed in Additional File 2. The definition of ‘relapse’ was subject to slight variation across trials but it was commonly defined as new or worsening symptoms that last 24 h, occurring in the absence of fever or infection (Schumacher et al., 1965). Definitions of disability progression varied between trials, but it was commonly defined as at least 1 point increase on the Expanded Disability Status Scale (EDSS, an ambulation-centred scale from 0 to 10), or a 0.5 point increase if the baseline EDSS was ≥5.5, confirmed during two subsequent neurological examinations separated by an interval of at least three to six months free of relapses (Kurtzke, 1983). Disability progression confirmed after three months and after six months were included in the analysis as two separate outcomes.

2.3. Data extraction and quality assessment

Total number of treated patients, duration of follow-up, intervention and control details, ARR, proportion of patients free of disability progression (confirmed after three months and/or six months) at the end of the study-period, and key population baseline characteristics (age, gender, baseline EDSS score, duration of disease, pre-trial relapse rate, and proportion of patients previously treated with DMT) were extracted from all studies, where reported. FDA and EMA reports were used as the primary data sources, where available. Where ARR and/or patient years of follow-up were not reported, rates were derived from total number of patients recruited, total number of relapses, mean number of relapses per person and total patient years of follow-up, where reported. The quality of included RCTs was assessed using Cochrane Collaboration's Risk of bias tool focussing on sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting and ‘other issues’ (Higgins and Green, 2011). The overall risk of bias associated with each study was classified as low, medium or high. High risk of bias was attributed to trials with lack of blinding among participants, personnel or outcome assessors, open treatment allocation, significant attrition bias due to incomplete outcome reporting. Medium risk of bias was attributed to trials with unclear methods of random sequence generation, and moderate attrition bias due to incomplete outcome reporting. Low risk of bias was attributed to trials without any bias detected in any of the seven domains, and in trials with unclear methods of allocation concealment which were otherwise judged to have been randomised appropriately.

2.4. Data analysis

A network meta-analysis was conducted combining data from trials comparing DMTs with placebo, as well as direct comparative trials. Combining direct and indirect (via a common comparator) evidence in this way increases the precision of relative effect estimates and allows treatments to be ranked for each of the outcomes studied. The network meta-analysis was conducted using Bayesian Markov Chain Monte Carlo methods and fitted in R to WinBUGS (Sturtz et al, 2005 and Lunn et al, 2000). Vague or non-informative priors were used. Convergence and lack of autocorrelation were confirmed with autocorrelation plots after a 150,000-simulation burn-in phase. Posterior means were based on an additional 400,000 simulation phase. The model assumed fixed effects as the network largely consisted of single-study connections. A non-informative vague prior was used for means and a uniform prior on the standard deviation parameter was assumed for the baseline effects (Gelman, 2006). For all pairwise comparisons the model estimates relative hazard rates (HR) of disability progression (assuming progression-free survival follows an exponential distribution) and relative ARR (assuming a poisson distribution for the number of relapses within one study arm). The probabilistic analysis does not rely on statistical significance; rather comparative effectiveness is based on probabilities of being among the best treatments for each outcome. The Surface under the cumulative ranking curve (SUCRA) is used to provide a hierarchy of treatments for each outcome, accounting for both the location and the variance of all relative treatment effects (Salanti et al., 2011). Values are expressed as a percentage and show the cumulative probability of a treatment being among the top r treatments. The larger the SUCRA value the better the treatment (Salanti et al., 2011). A ranking plot may be used to illustrate the treatments’ hierarchy and the differences in SUCRA values (Chaimani et al., 2013). Potential sources of treatment-effect modification from baseline population differences were investigated by extending the model to a meta-regression including age, gender, baseline EDSS, duration of disease, number of relapses in the previous two years, and proportion of patients previously treated with DMT. Treatment effects were estimated at the study-mean covariate level. By modelling relative effect differences, the model accounts for random variation in baseline risks. However, to explain a potential systematic impact of baseline risk on response, baseline risk i.e. outcome in the placebo arm, was included alongside other potential confounders as a covariate. Only trials which include a placebo arm contribute to the estimation of this regression parameter. Inconsistency between direct and indirect evidence for each mean treatment effect was examined by comparing the model to a model relaxing the consistency assumption. The Deviance Information Criterion was used to assess model fit.

3. Results

3.1. Evidence base

The systematic search identified 6086 potentially relevant publications, of which 28 trials met the inclusion criteria (Fig. 1) ((Cohen et al, 2010), (Confavreux et al, 2014), (Vermersch et al, 2013), (O’Connor et al, 2011), (Saida et al, 2012), (Mikol et al, 2008), (PRISMS Prevention of Relapses and Disability by Interferon beta-1a Subcutaneously in Multiple Sclerosis Study Group, 1998), (Jacobs et al, 1996), (Kappos et al, 2011), (Johnson et al, 1995), (Durelli et al, 2002), (Duquette et al, 1993), (Calabresi et al, 2014a), (Kappos et al, 2010), (Panitch et al, 2002), (Etemadifar et al, 2006), (Gold et al, 2012), (Fox et al, 2012), (Comi et al, 2001), (Lublin et al, 2013), (Coles et al, 2012), (Cohen et al, 2012a), (Coles et al, 2008), (Vollmer et al, 2014), (O’Connor et al, 2009), (Polman et al, 2006), (Calabresi et al, 2014b), and (Khan et al, 2013)). Trials were published between 1993 and 2014, were of 1.75 years mean duration and comprised a total of 17,040 patients. The evidence network is illustrated in Fig. 2. ARR outcomes were obtained from all 28 trials, while data on disability progression confirmed after three months and six months were available from 16 trials. Overall the included studies were broadly comparable in terms of mean age (31.8–40.4 years), percentage female (63–79%), and mean baseline EDSS score (1.9–3.2). Greater variation was observed in the mean number of relapses in the previous two years (1.7–3.5), mean duration of disease prior to recruitment (1.2–10.5 years), and in the proportion of patients who had received prior treatment with a DMT (0–100%) (see Additional file 3 for full details of the baseline characteristics of the study populations). The overall risk of bias within included studies was judged to be low in 14 studies (50%), medium in one study (4%) and high in 13 studies (46%). High risk of bias was predominantly due to the single-blind nature of many trials. All but one study employed outcome-assessor blinding (Durelli et al., 2002) but participants were not blinded to treatment allocation in a further 12 RCTs (Vermersch et al, 2013, Mikol et al, 2008, Kappos et al, 2011, Durelli et al, 2002, Panitch et al, 2002, Etemadifar et al, 2006, Fox et al, 2012, Coles et al, 2012, Cohen et al, 2012a, Coles et al, 2008, Vollmer et al, 2014, and O’Connor et al, 2009). Incomplete outcome data due to loss to follow-up or imbalance in discontinuations across treatment groups was identified in three studies, (Jacobs et al, 1996, Coles et al, 2012, and Coles et al, 2008) with high attrition bias identified in one study (Jacobs et al., 1996) (see Additional file 4 for full details of quality assessment).

Fig. 1.

Fig. 1

PRISMA flowchart – Identification and selection of randomised controlled trials of disease-modifying therapies in patients with relapsing remitting multiple sclerosis.

 

Fig. 2.

Fig. 2

Network diagram of trials – Each node in the network represents a disease-modifying therapy. Links between nodes represent pairwise treatment comparisons extracted from randomised controlled trials. Nodes are weighted according to the number of studies included for respective therapies. IFN β=interferon beta, IM=intramuscular, SC=subcutaneous.

 

3.2. Network meta-analysis

Fig. 3a–c presents the network meta-analysis results for each DMT versus placebo for the three outcomes analysed. Each of the DMTs reduced ARR versus placebo. The magnitude of ARR reduction varied between 15–36% for all IFN β products, glatiramer acetate and teriflunomide, and from 50 to 69% for alemtuzumab, dimethyl fumarate, fingolimod and natalizumab. The risk of disability progression confirmed after three months was reduced by 19–28% with IFN β products, glatiramer acetate, fingolimod and teriflunomide, by 38–45% for pegylated IFN β, dimethyl fumarate and natalizumab and by 68% with alemtuzumab. Superiority over placebo was less certain for IFN β−1a 30 mcg, IFN β−1a 22 mcg, IFN β−1b 250 mcg and glatiramer acetate 20 mg compared with other therapies. Results for disability progression confirmed after six months varied slightly from disability progression confirmed after three months for each DMT, with the exception of IFN β−1b 250 mcg which was much more efficacious when the outcome was defined by a six-month confirmation interval (HR 0.31, 95% CI 0.15–0.62 versus HR 0.83, 95% CI 0.62–1.12). A cumulative ranking analysis (Fig. 3df) revealed that alemtuzumab and natalizumab had the highest SUCRA scores for ARR and disability progression confirmed after three months, while IFN β−1a 30 mcg ranked lowest and second-lowest among active treatments for these outcomes (SUCRA scores of 9% and 32% respectively). Ranking of treatments was affected by the definition of disability progression largely due to the conflicting results of IFN β−1b 250 mcg, ranking as the most efficacious treatment for disability progression confirmed after six months (92%) and as the least efficacious for disability progression confirmed after three months (30%). Alemtuzumab and natalizumab both scored relatively highly for disability progression confirmed after six months. Notable variation in ranking across outcomes was observed for fingolimod (81% for ARR, 39–46% for the disability progression outcomes).

Fig. 3.

Fig. 3

a-c. Forest plots of treatments versus placebo for a) Annualised relapse rate, b) Disability progression confirmed at three months c) Disability progression confirmed at six months. Relative treatment effects (rate ratios for annualised relapse rate, hazard ratios for disability progression) are represented by coloured nodes, and corresponding 95% credible intervals are represented by solid lines. Bars to the left of the central vertical line of no difference indicate superiority of the treatment over placebo. Hollow nodes represent pairwise comparisons where the 95% credible interval spans the central vertical line of no difference. d-f. Network ranking plots for d) Annualised relapse rate, e) Disability progression confirmed at three months c) Disability progression confirmed at six months. Treatments are ranked according to the surface under the cumulative ranking curve (SUCRA). SUCRA values provide the hierarchy for the treatments and placebo, and show the cumulative probability (expressed as a percentage) of a treatment being among the best options. The y-axis shows the possible ranks from r=1 up to r=11 and the x-axis shows the cumulative probabilities that the corresponding treatment is among the top r treatments. The larger the SUCRA value the better the treatment. IFN β=interferon beta; IM=intramuscular; SC=subcutaneous; RR=rate ratio; HR=hazard ratio; CI=credible interval.

 

3.3. Covariate analysis

Meta-regression models including seven study-level covariates were used to evaluate the impact of potential treatment effect modifiers. Six covariates represented population baseline characteristics (age, gender, baseline EDSS, duration of disease, number of relapses in the previous two years, and proportion of patients previously treated with DMT), and one covariate represented baseline risk. The different meta-regression analyses suggested negligible covariate effects from each of the included covariates (See additional file 6). Adjustment of the models for baseline risk (based on trial-specific placebo arms in each trial) similarly had negligible impact on the results and the overall ranking of therapies (See additional file 7).

DIC statistics were lower for the consistency model than the inconsistency model for all outcomes indicating a better fit to the data and no evidence of inconsistency between the direct and indirect data (See Additional File 5).

4. Discussion

The last decade has seen major breakthroughs in the development of new therapeutic strategies for RRMS. However, the extent to which they present efficacy advantages compared to established treatments has been unclear, as many trials are placebo-controlled, or don’t include all comparators of interest. The Bayesian network meta-analysis framework allows the estimation of relative treatment effects through the combination of placebo-controlled and direct comparative studies while preserving within-trial randomised treatment comparisons (Lunn et al., 2000). The objective of this study was to compare the efficacy of individual DMTs for patients with RRMS in terms of the most commonly used clinical trial outcomes, relapse and disability progression. Both relapses and progression are the clinical hallmarks of the MS disease process. However evidence from natural history studies has shown dissociation between relapses and disability progression pathologies (Confavreux and Vukusic, 2006b). This dissociation has been borne out in individual clinical trials and in this network meta-analysis where clear reductions in ARR are accompanied by more uncertain changes in disability progression. For many patients relapses are the initial defining feature of their disease. Relapses can have a significant physical, psychological and social impact on patients, and place a substantial cost burden on patients, their families and healthcare systems (O’B(rien) et al,, Kalb, 2007, and Halper, 2007). However, it is the accumulation of disability which has the greatest long-term clinical, social and economic impact on patients and society (Fogarty et al, 2014 and Fogarty et al, 2013).

Generally, DMTs were superior to placebo in reducing MS relapse rates and disability progression. However the magnitude of the reduction and the uncertainty associated with treatment effects varied between DMTs, and between the different outcomes included in the analysis, leading to variation in the relative ranking of treatments. The monoclonal antibody therapies alemtuzumab and natalizumab were generally among the highest ranked treatments for all outcomes. Among the oral therapies, fingolimod and dimethyl fumarate ranked higher than other therapies for ARR, while there was little difference between teriflunomide and other first-line DMTs for this outcome. Dimethyl fumarate, pegylated IFN β and IFN β 44 mcg occupied higher rankings than other DMTs for disability progression confirmed after three months and there was little to distinguish between the rankings of other treatments.

European guidelines on the clinical investigation of medicinal products for the treatment of MS recommend a six month confirmation interval for an accurate and reliable definition of sustained worsening as studies have shown that improvement in EDSS scores after relapse can continue beyond three months ((European Medicines Agency EMA Committee for Medicinal Products for Human Use CHMP, 2006) and (Cohen et al, 2012b)). Despite this, disability progression is often defined in RCTs on the basis of a three-month confirmation interval rather than six months. For this reason, disability progression defined on the basis of both three and six month confirmation intervals were included as two separate outcomes in the analysis. With the exception of IFN β−1b 250 mcg SC, point estimates for the efficacy of DMTs versus placebo in reducing disability progression were similar between both definitions with credible intervals for the two outcomes overlapping in all cases. A significant improvement in efficacy was observed for IFN β−1b 250 mcg SC when disability progression was defined on the basis of a six-month confirmation interval, ranking highest for this outcome compared with being among the lowest ranked treatments on the basis of a three-month confirmation interval. Just one study, the INCOMIN study, contributed evidence for the efficacy of IFN β−1b 250 mcg SC on disability progression confirmed after six months, finding it to be superior to IFN β−1a 30 mcg IM for this outcome (Durelli et al., 2002). This is in contrast to two studies, one placebo controlled and one versus glatiramer acetate which did not show significant improvements with IFN β−1b 250 mcg SC in disability progression confirmed after three months (Duquette et al, 1993 and O’Connor et al, 2009). It has been suggested that differences in baseline disease characteristics indicate that patients treated with IFN β−1a 30 mcg IM in the INCOMIN study may have had a poorer prognosis than IFN β−1b 250 mcg SC treated patients (Vartanian, 2003). Bias may also have been introduced to the INCOMIN study by the lack of blinding as this was the only study included in the analysis which was not assessor-blinded.

The relevance of the clinical outcomes investigated in this study in the setting of a chronic, heterogeneous condition which evolves over time, is uncertain. While the mechanisms that underlie relapses and gradual progression may be distinct, they may sometimes present concurrently (Cohen et al., 2012b). Improvement in EDSS scores after relapses may continue beyond three to six months and variable recovery from relapses may lead to the accrual of relapse-related disability. Relapses decrease over time and disappear in many patients with the onset of secondary progression (Tremlett et al., 2008). The EDSS is an ordinal rather than linear measure and differences between each level (e.g. a one point change between 1.5 and 2.5, and between 3.5 and 4.5 may not comparable. Other inadequacies of the EDSS scale have been highlighted, and it is not clear whether either of the definitions of progression assessed in this analysis truly represents irreversible sustained disability progression and reliably reflect long-term changes in disease progression (Cohen et al., 2012b). Despite its limitations, at the moment the EDSS remains the only validated outcome measurement to determine disability (determined by the European Medicines Agency) and its use is recommended to continue in the future alongside improved measures of disability progression to facilitate comparison with other studies. Research is ongoing into novel approaches to demonstrating efficacy. RCTs are increasingly incorporating adjunctive imaging outcomes and composite measures such as disease-activity-free-status (Bevan and Cree, 2014). These and other novel outcomes will provide additional evidence on the comparative efficacy of treatments but are not developed sufficiently to serve as substitutes for the outcomes investigated in this analysis.

The long-term relevance of treatment effects estimated on the basis of short-term trials (6–33 months follow-up) may be limited. RRMS may require treatment with DMT for many years, but there is little evidence on the long-term efficacy of these agents. The development of neutralising antibodies can complicate prolonged IFN β therapy (Giovannoni et al., 2002). Results from some long-term open-label extension studies suggest maintained efficacy of DMTs on relapse rate over extended periods of use, however the lack of a comparator arm limits the conclusions on clinical efficacy which can be drawn from these studies (Khatri et al, 2011, Confavreux et al, 2012, Kappos et al, 2012a, Gold et al, 2014, Kappos et al, 2012b, and Ford et al, 2010). Conflicting results have been reported for the long-term efficacy of first line DMTs on reducing disability progression (Goodin et al, 2011 and Shirani et al, 2012).

The study has a number of limitations. As with traditional pairwise meta-analysis, the model requires that individual studies are sufficiently similar, so as to generate exchangeable treatment effects. The trials included in the analysis were conducted over a period of over 25 years. Slight variation in outcome definitions between studies and changes in patient populations were evident in duration of disease, proportion of trial populations who had received prior DMT, and also in the downward trend in relapse rates over time. We explored potential sources of heterogeneity from several known covariates to adjust for baseline imbalance in underlying risk across studies. No significant association between efficacy and baseline risk or other covariates were identified. Although no significant confounding of treatment effect was identified, meta-regression based on aggregate study-level data is prone to ecological bias and the risk of unknown imbalances in treatment effect modifiers cannot be excluded (Cooper et al., 2009). Consistency between the direct and indirect evidence is dependent on the distribution of effect modifiers and where both direct and indirect evidence was available no evidence of inconsistency was identified. There was variation in study quality among the included trials. In particular, concerns regarding the open-label design may affect our level of confidence in the estimates of effect from some trials, as the potential for bias cannot be excluded. In this study we did not investigate the relative acceptability or tolerability of the various treatment strategies. Consideration of safety outcomes alongside treatment efficacy is central to decision-making in healthcare and has been addressed elsewhere (Saidha et al, 2012 and Smith et al, 2010 Aug). Cost-effectiveness, likewise, was not considered. This is increasingly a critical determinant of reimbursement in many countries, due to the high acquisition cost of many of these treatments.

5. Conclusion

The network meta-analysis approach is not a substitute for large, well-designed RCTs comparing the comparators of interest. However, given the current limitations in the evidence base, this study provides an alternative framework within which comparative effectiveness can be estimated. This analysis integrated evidence from a comprehensive network of trials of DMT in RRMS, using both direct and indirect data to simultaneously evaluate treatment effects of interventions not previously studied in head-to-head trials. Treatment rankings have been presented for separate outcomes, based on cumulative probabilities of being among the most effective treatments. There is little difference (indicating similarity in treatment effects) between these probabilities for many treatments, with newer agents natalizumab and alemtuzumab demonstrating consistently high ranking across outcomes. Health policy and resource allocation decision-making frequently requires quantification of comparative efficacy. Evidence synthesis within this network meta-analysis framework is a powerful approach to dealing with complex evidence structures to facilitate coherent, evidence-based decision-making.

Author contributions

EF conceived and designed the study, identified and acquired trials, extracted data, contributed to data analysis, interpreted the results drafted the manuscript and is guarantor. SS identified trials, extracted data, performed statistical analysis and critically revised the manuscript for important intellectual content. CW provided statistical advice and critically revised the manuscript for important intellectual content. NT and MB critically revised the manuscript for important intellectual content. All authors approved the final version of the manuscript.

Conflict of interest statement

EF, SS, CW and MB report no conflict of interest. Prof. Tubridy has received unrestricted educational and research grants on behalf of the Department Of Neurology at St. Vincent’s University Hospital from Bayer Schering, Biogen Idec and Novartis.

Ethical approval

Not required for this study.

Funding

No funding was received for this study.

Data sharing

Statistical code is available from the corresponding author.

Appendix A. Supplementary material

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Footnotes

a National Centre for Pharmacoeconomics, Dublin, Ireland

b Health Economics and Evidence Synthesis Research Unit, Department of Population Health, Luxembourg Institute of Health, Luxembourg

c Department of Neurology, St. Vincent's University Hospital, Dublin, Ireland

d Department of Mathematics and Statistics, University of Limerick, Ireland

e National Centre for Pharmacoeconomics, Dublin, Ireland

* Corresponding author.


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  • Prof Timothy Vartanian

    Timothy Vartanian, Professor at the Brain and Mind Research Institute and the Department of Neurology, Weill Cornell Medical College, Cornell...
  • Dr Claire S. Riley

    Claire S. Riley, MD is an assistant attending neurologist and assistant professor of neurology in the Neurological Institute, Columbia University,...
  • Dr Rebecca Farber

    Rebecca Farber, MD is an attending neurologist and assistant professor of neurology at the Neurological Institute, Columbia University, in New...

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