Dimethyl fumarate for multiple sclerosis

  • Protocol
  • Intervention

Authors


Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the absolute and comparative efficacy and safety of dimethyl fumarate as monotherapy or combination therapy versus placebo or other approved disease-modifying drugs (IFN-β, glatiramer acetate, natalizumab, mitoxantrone, fingolimod, teriflunomide, alemtuzumab) for patients with MS. 

Background

Description of the condition

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system. It is pathologically characterised by inflammation, demyelination, and axonal and neuronal loss. Clinically it is characterised by recurrent relapses or progression, or both, typically striking adults during the primary productive time of their lives and ultimately leading to severe neurological disability.

There are four clinical phenotypes of MS. Initially, more than 80% of individuals with MS experience a relapsing-remitting disease course (RRMS), characterised by clinical exacerbations of neurological symptoms followed by complete or incomplete remission (Lublin 1996). After 10 to 20 years, or a median age of 39.1 years, about half of these people gradually accumulate irreversible neurological deficits, with or without clinical relapses (Confavreux 2006), which is known as secondary progressive MS (SPMS). Another 10% to 20% of individuals with MS are diagnosed with primary progressive MS (PPMS), clinically defined as a disease course without any clinical attacks or remission from onset (Lublin 1996). A significantly rarer form is progressive relapsing MS (PRMS), which initially presents as PPMS; however, during the course of the disease these individuals develop true neurological exacerbations (Tullman 2004).

MS causes a major socioeconomic burden, both for the individual patient and for society. Increasing costs and decreasing quality of life are associated with advancing disease severity, disease progression and relapses (Karampampa 2012a; Karampampa 2013). From a patient's perspective, a MS relapse is associated with a significant increase in economic costs as well as a decline in health-related quality of life and functional ability (Oleen-Burkey 2012). Effective treatment that reduces relapse frequency and prevents progression could have an impact both on costs and quality of life, and may help to reduce the social burden of MS (Karampampa 2012b).

Natalizumab and interferon (IFN) β-1a (IFNβ-1a) (Rebif) have been shown to be superior to mitoxantrone, glatiramer acetate, IFNβ-1b (Betaseron) and IFNβ-1a (Avonex) for preventing clinical relapses in RRMS in the short term (24 months) compared to placebo, based on high-quality evidence. However, they are associated with long-term serious adverse events and their benefit-risk balance might be unfavourable (Filippini 2013). Furthermore, administration of IFNβ is not associated with a reduction in the progression of disability among patients with RRMS (Shirani 2012). Therefore, there is a need for safer and more effective drugs with new modes of action that lead to anti-inflammation and neuroprotection in MS.

Inflammation and oxidative stress are thought to cause tissue damage in MS. Therefore, oxidative stress and antioxidative pathways are important in MS pathophysiology (Gilgun-Sherki 2004; Lee 2012), and novel therapeutics that enhance cellular resistance to free radicals could prove useful for MS treatment. Recent data support this important role of antioxidative pathways for tissue protection in progressive MS, particularly by activation of the transcription factor nuclear factor (erythroid-derived 2)-related factor 2 (Nrf2) antioxidant pathway (Johnson 2010), which is not yet targeted by other disease-modifying therapies for MS (Linker 2011).

Description of the intervention

Several lines of research have demonstrated immunomodulatory but also neuroprotective effects of fumaric acid esters, as shown in vitro as well as in experimental models of MS (Lukashev 2007). Fumaric acid esters include methyl hydrogen fumarate and dimethyl fumarate. Immunomodulatory concentrations of dimethyl fumarate can reduce oxidative stress without altering neuronal network activity (Albrecht 2012). In the acute phase of experimental autoimmune encephalomyelitis, treatment with dimethyl fumarate resulted in a significant reduction of macrophage/microglia infiltration in inflamed lesions (Schilling 2006). In an in vitro model of brain inflammation, dimethyl fumarate inhibited microglial and astrocytic inflammation by suppressing the synthesis of nitric oxide, interleukin (IL)-1β, tumour necrosis factor (TNF)-α and IL-6 (Wilms 2010). Dimethyl fumarate and its primary metabolite, monomethyl fumarate, are cytoprotective of neurons and astrocytes against oxidative stress-induced cellular injury and loss, potentially by induction of the transcription factor Nrf-2 and up-regulation of an Nrf2-dependent antioxidant response (Scannevin 2012). In addition, dimethyl fumarate treatment for type 1 helper T cells (Th1) and T helper type 17 (Th17)-mediated MS induces IL-4-producing Th2 cells in vivo and generates type II dendritic cells that produce IL-10 instead of IL-12 and IL-23 (Ghoreschi 2011). Dimethyl fumarate inhibits maturation of dendritic cells and subsequently Th1 and Th17 cell differentiation by suppression of both nuclear factor κB (NF-κB) and extracellular signal-regulated kinase 1 and 2 (ERK1/2) and mitogen stress-activated kinase 1 (MSK1) (ERK1/2-MSK1) signalling (Peng 2012).

Dimethyl fumarate, the active component of BG00012 (BG-12), is absorbed almost exclusively in the small intestine within two hours after oral administration and is rapidly hydrolysed by esterases to its metabolite, monomethyl fumarate, in the intestinal mucosa (Litjens 2004). Dimethyl fumarate possesses a pharmacological half-life of about 12 minutes and does not show any binding activity to serum proteins, which may further contribute to its rapid turnover in the circulation (Lee 2008). There is no evidence for a cytochrome P450-dependent metabolism of fumaric acid esters in the liver (Lee 2008).

How the intervention might work

An oral formulation of dimethyl fumarate (BG-12) has shown promising results for RRMS in clinical trials, combining anti-inflammatory and possibly clinically relevant neuroprotective effects with the convenience of oral administration. An exploratory, prospective, open-label pilot study showed that fumaric acid esters produced significant reductions from baseline in the number and volume of gadolinium-enhancing lesions in patients with RRMS (Schimrigk 2006). A phase II study with oral BG-12 revealed a dose-dependent, significant reduction in brain lesion activity. Oral BG-12 at a dose of 240 mg three times daily significantly reduced the number of new gadolinium-enhancing lesions, new or enlarging T2-hyperintense and new T1-hypointense lesions, and the annualised relapse rate (ARR) in patients with RRMS (Kappos 2008; Kappos 2012; MacManus 2011). A randomised, double-blind, placebo-controlled phase III study (DEFINE) showed that both oral BG-12 doses (at a dose of 240 mg twice daily and 240 mg three times daily) significantly reduced the proportion of patients who had a relapse, the ARR, the rate of disability progression and the number of lesions in patients with RRMS (Bar-Or 2013; Gold 2012) when compared with placebo. Another phase III study (CONFIRM) showed that both oral BG-12 doses and glatiramer acetate (subcutaneous daily injections of 20 mg) significantly reduced the ARR and the numbers of new or enlarging T2-weighted hyperintense lesions and new T1-weighted hypointense lesions in patients with RRMS, compared with placebo, but the reductions in disability progression with twice-daily BG-12, thrice-daily BG-12 and glatiramer acetate were not significant (Fox 2012). Post hoc comparisons of BG-12 with glatiramer acetate showed significant differences in the ARR (thrice-daily BG-12) (Hutchinson 2013), new or enlarging T2-weighted hyperintense lesions (both BG-12 doses) and new T1-weighted hypointense lesions (thrice-daily BG-12). Furthermore, BG-12 had positive effects on health-related quality of life in patients with RRMS (Kappos 2014; Kita 2014).

Why it is important to do this review

A recent non-Cochrane review based on indirect comparison has shown that dimethyl fumarate offers an effective oral treatment option for patients with RRMS, with an overall promising efficacy and safety profile, compared to IFNβ-1a, IFNβ-1b, glatiramer acetate, fingolimod, natalizumab and teriflunomide (Hutchinson 2014). However, the authors did not perform a comprehensive analysis of study quality. No systematic review based on direct comparison, which solely evaluates the absolute and comparative efficacy and safety of dimethyl fumarate for MS, currently exists in the peer-reviewed literature.

Objectives

To assess the absolute and comparative efficacy and safety of dimethyl fumarate as monotherapy or combination therapy versus placebo or other approved disease-modifying drugs (IFN-β, glatiramer acetate, natalizumab, mitoxantrone, fingolimod, teriflunomide, alemtuzumab) for patients with MS. 

Methods

Criteria for considering studies for this review

Types of studies

All randomised, double-blind, controlled, parallel-group clinical trials (RCTs) evaluating dimethyl fumarate, as monotherapy or combination therapy, versus placebo or other approved disease-modifying drugs for patients with MS. We will exclude trials with follow-up of less than one year.

Types of participants

We will include patients aged 18 to 60 years with a definite diagnosis of MS as defined according to Poser's (Poser 1983) or McDonald's (McDonald 2001; Polman 2005; Polman 2011) criteria, any clinical phenotypes categorised according to the classification of Lublin and Reingold (Lublin 1996), and an Expanded Disability Status Scale (EDSS) (Kurtzke 1983) score of 6.0 or lower.

Types of interventions

Experimental intervention

Treatment with dimethyl fumarate orally, as monotherapy or combination therapy, without restrictions regarding dosage, administration frequency or duration of treatment.

Control intervention

Placebo or an approved disease-modifying drug.

Types of outcome measures

Primary outcomes

We will assess the following primary outcomes, measured in the treatment phase and at the completion of follow-up versus baseline.

Efficacy
  1. The proportion of patients with at least one relapse at one year, two years or at the end of follow-up if longer than two years. Confirmed relapse is defined as the occurrence of new symptoms or worsening of previously stable or improving symptoms and signs, not associated with fever or infection, occurring at least 30 days after the onset of a preceding relapse, lasting longer than 24 hours and that were accompanied by new objective neurological findings according to a neurologist's evaluation.

  2. The proportion of patients with disability progression as assessed by the EDSS at one year, two years or at the end of follow-up if longer than two years. Disability progression was defined as an increase in the EDSS score of at least 1.0 point in patients with a baseline score of 1.0 or higher or an increase of at least 1.5 points in patients with a baseline score of 0, with the increased score sustained for six months. We will use the data if disability progression is confirmed in less than six months, however we will downgrade the study for indirectness when we perform the GRADE assessment.

Safety

The proportion of patients with at least one adverse event, the proportion of patients with at least one serious adverse event and the proportion of patients who withdrew or dropped out from the study because of adverse events at one year, two years or at the end of follow-up if longer than two years.   

Secondary outcomes

We will assess the following secondary outcomes, measured in the treatment phase and at the completion of follow-up versus baseline.

  1. The ARR at one year, two years or at the end of follow-up if longer than two years, defined as the mean number of confirmed relapses per patient, adjusted for the duration of follow-up to annualise it.

  2. The number of gadolinium-enhancing T1-weighted lesions at one year, two years or at the end of follow-up if longer than two years.

  3. The number of new or enlarging T2-weighted hyperintense lesions at one year, two years or at the end of follow-up if longer than two years.

  4. The percentage brain volume change at one year, two years or at the end of follow-up if longer than two years.

  5. Mean change in health-related quality of life. We will accept the following scales: the Medical Outcomes Study (MOS) 36-Item Short-Form Health Survey (SF-36) (Ware 1992), the Multiple Sclerosis Quality of Life-54 (MSQOL-54) (Vickrey 1995), the Multiple Sclerosis Quality of Life Inventory (MSQLI) (Fischer 1999) or the Functional Assessment of Multiple Sclerosis (FAMS) (Cella 1996) at one year, two years or at the end of follow-up if longer than two years.

Search methods for identification of studies

Electronic searches

The Review Group's Trials Search Co-ordinator will search the Cochrane Multiple Sclerosis and Rare Diseases of the Central Nervous System Group Trials Register which, among other sources, contains CENTRAL, MEDLINE, EMBASE, CINAHL, LILACS, PEDRO, as well as clinical trials registries (http://clinicaltrials.gov/ and the World Health Organization (WHO) International Clinical Trials Registry Portal (ICTRP) (apps.who.int/trialsearch/)). Information on the Group's Trials Register and details of the search strategies used to identify trials can be found in the 'Specialised Register' section within the Cochrane Multiple Sclerosis and Rare Diseases of the Central Nervous System Group's module.

The keywords used to search for trials for this review are listed in Appendix 1. We will apply no language restrictions to the search.

Searching other resources

We will check reference lists of published reviews and retrieved articles for additional trials. We will search reports (2004 onwards) from the MS Societies (National Multiple Sclerosis Society (United States, United Kingdom)) and the Congress of the European and Americas Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS and ACTRIMS). We will communicate personally with investigators participating in trials of dimethyl fumarate. We will also contact the biotechnology company Biogen Idec in an effort to identify further studies (http://www.biogenidec.com).

Data collection and analysis

Selection of studies

Two review authors (Xu and He) will independently screen titles and abstracts of the citations retrieved by the literature search for inclusion or exclusion. We will obtain the available full texts of potentially relevant studies for further assessment. We will independently evaluate the eligibility of these studies (on the basis of information available in the published data) and will list papers that did not meet the inclusion criteria in the 'Characteristics of excluded studies' table with the reasons for exclusion. We will resolve any disagreement regarding inclusion by discussion or by referral to a third review author (Dong) if necessary.

Data extraction and management

Two review authors (Xu, He) will independently extract data from the selected trials using standardised forms, and will extract information about study design, participants, interventions and outcome measures. We will contact the principal investigators of included studies in order to request additional data or confirmation of methodological aspects of the study. We will discuss and resolve disagreements by consensus among the review authors.

Assessment of risk of bias in included studies

We will base the methodological criteria on theCochrane Handbook for Systematic Review of Interventions Version 5.1.0 (Higgins 2011). Two review authors (Xu and He) will independently evaluate the methodological quality of the studies using the 'Risk of bias' tool under the domains of sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome and other biases. We will judge a study to have a high risk of attrition bias when it has a dropout rate higher than 20%. We will judge a study to have a high overall risk of bias if there is at least one high risk of bias among the seven domains.

Measures of treatment effect

The pre-set outcomes in this protocol involve counts and rates, dichotomous and continuous data, and ordinal data (measurement scales).

The numbers of relapses, new gadolinium-enhancing T1-weighted lesions and new or enlarging T2-weighted hyperintense lesions are count data. Analyses of counts of rare events (Poisson data) often focus on rates (rates relate the counts to the amount of time during which they could have happened). The rate ratio, which compares the rate of events in the two groups by dividing one by the other, can be used to measure the treatment effect on counts of rare events. The mean difference (MD), which compares the difference in the mean number of events (possibly standardised to a unit time period) experienced by participants in the intervention group compared with participants in the control group, can be used to measure the treatment effect on counts of common events. The two methods are equivalent when all patients have an equal follow-up in terms of person-years, but this is very unlikely in this case. We will use rate ratio instead of MD as the measure of treatment effect for count data.

For continuous outcomes, we will calculate the MD or the standardised mean difference (SMD) with 95% confidence intervals (CI). We will calculate the standard deviation from the CI or t-tests, when the CI is not reported. The percentage brain volume change is a continuous outcome and we will use the MD as the measure of treatment effect.

For dichotomous outcomes, we will calculate individual and pooled statistics as risk ratios (RR) or odds ratios (OR), risk difference (RD) (also called the absolute risk reduction) and the number needed to treat to benefit (NNTB). The proportion of patients with at least one relapse, disability progression and at least one adverse event are dichotomous outcomes and we will use the RR as the measure of treatment effect.

We will treat the data on health-related quality of life scales as continuous because they are longer ordinal rating scales and have a reasonably large number of categories. Therefore we will use the MD if trials used the same rating scale to assess outcome. Where different rating scales are used, we will express the measure of the treatment difference as the SMD.

Unit of analysis issues

Most RCTs on dimethyl fumarate for MS are multi-arm studies with two experimental intervention groups (BG-12 240 mg twice daily, 240 mg three times daily) and a common control group, involving repeated observations on participants. The pre-set outcome measures in this protocol involve events that may re-occur. If studies with multiple intervention groups are included, we will create a single pair-wise comparison by combining groups if appropriate, or we will select one pair of interventions and exclude the others. Meanwhile, we will perform separate analyses based on the pre-set outcomes in this protocol and different periods of follow-up.

Dealing with missing data

If data are not available from published reports, we will contact the study authors for further details. We will analyse the available data when the data are assumed to be missing at random, but for data not missing at random, we will perform a sensitivity analysis according to a likely scenario where we assume that both the participants who dropped out in each group and the participants who were not included in the study analysis had the outcome. We will use the intention-to-treat principle for analyses. We will address the potential impact of missing data on the findings of the review in the 'Discussion' section.

Assessment of heterogeneity

We will assess clinical heterogeneity by examining the characteristics of the studies, the similarity between the types of participants, the interventions and the outcomes as specified in the criteria for included studies. We also evaluate the variability in study design and risk of bias (methodological heterogeneity). We will evaluate statistical heterogeneity where clinical and methodological heterogeneity are not obvious across the included studies. When pooling trials in meta-analyses, we will calculate the I2 statistic to identify heterogeneity across studies. When the I2 value is higher than 30% there is some level of heterogeneity (Higgins 2011). If tests for heterogeneity are statistically significant and inspection of the individual results suggests that it still logical to combine results, we will calculate the overall effects using a random-effects model.

Assessment of reporting biases

If sufficient RCTs are identified, we will examine potential publication bias using a funnel plot. For continuous outcomes, we will use the standard error as the vertical axis and MDs as the horizontal axis in funnel plots. For dichotomous outcomes, we will plot ORs or RRs on a logarithmic scale as the horizontal axis and will use the standard error as the vertical axis.

Data synthesis

When clinically and methodologically homogeneous RCTs are identified and heterogeneity tests suggest an I2 value lower than 30%, or inspection of the individual results suggests that it still seems logical to combine results even though tests for heterogeneity are statistically significant, we will conduct formal meta-analysis using Review Manager software (Review Manager 2012). We will calculate treatment effect estimates for each study and the weighted average of the treatment effects estimated in the individual studies (as a pooled treatment effect estimate), and select a random-effects model or fixed-effect model according to the results of the heterogeneity tests. If it is assumed that each study is estimating exactly the same quantity, we will use a fixed-effect model, otherwise we will use a random-effects model. For the outcomes treated as dichotomous data with the rate ratio (the proportion of patients with at least one relapse, disability progression and at least one adverse event, the ARR, the mean number of gadolinium-enhancing T1-weighted lesions and new or enlarging T2-weighted hyperintense lesions), we will select three fixed-effect methods (Mantel-Haenszel, Peto or inverse variance) and one random-effects method (DerSimonian and Laird) (the Peto method can only pool ORs whilst the other three methods can pool ORs, RRs and RDs). For the outcomes treated as continuous data (the percentage brain volume change and mean change in health-related quality of life), we will select the inverse-variance fixed-effect method and the inverse-variance random-effects method.

Subgroup analysis and investigation of heterogeneity

If possible, we plan to carry out subgroup analyses according to:

  1. different MS patients (e.g. patients with RRMS, patients with progressive MS);

  2. duration of follow-up (e.g. at one year, at two years, at the end of follow-up if longer than two years);

  3. baseline EDSS scores (e.g. equal to or lower than 3.5, between 3.5 and 6);

  4. administration frequency (e.g. 240 mg twice daily, 240 mg three times daily);

  5. different durations of MS (e.g. five years, longer than five years).   

Sensitivity analysis

Where possible, we will undertake sensitivity analysis to assess the influence on the results of fixed-effect versus random-effects model assumptions and of including trials at high risk of bias. We will also assess the effects of analysing by intention-to-treat and the effect measure (for dichotomous outcomes and rate ratio, the RR versus OR; for continuous outcomes, the MD versus SMD).

'Summary of findings' table

We will create a 'Summary of findings' table using the following outcomes:

  1. The proportion of patients with at least one relapse at one year, two years or at the end of follow-up if longer than two years.

  2. The proportion of patients with disability progression as assessed by the EDSS at one year, two years or at the end of follow-up if longer than two years.

  3. The ARR at one year, two years or at the end of follow-up if longer than two years.

  4. The proportion of patients with at least one adverse event at one year, two years or at the end of follow-up if longer than two years.

  5. The proportion of patients with at least one serious adverse event at one year, two years or at the end of follow-up if longer than two years.

  6. The mean number of gadolinium-enhancing T1-weighted lesions at one year, two years or at the end of follow-up if longer than two years.

  7. The mean number of new or enlarging T2-weighted hyperintense lesions at one year, two years or at the end of follow-up if longer than two years.

We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of the body of evidence as it relates to the studies that contribute data to the meta-analyses for the prespecified outcomes. We will use the methods and recommendations in Section 8.5 and Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) and the GRADEpro software (GRADEpro 2008). We will justify all decisions to downgrade or upgrade the quality of studies using footnotes and we will make comments to aid the reader's understanding of the review where necessary.

Acknowledgements

We wish to thank Andrea Fittipaldo, Trials Search Co-ordinator, and Liliana Coco, Managing Editor of the Cochrane Multiple Sclerosis and Rare Diseases of the Central Nervous System Group, for their help and support in developing this protocol. We thank all peer reviewers, and Graziella Filippini, the Co-ordinating editor of the Cochrane Multiple Sclerosis and Rare Diseases of the Central Nervous System Group, for their constructive comments and suggestions for this protocol.

Appendices

Appendix 1. Keywords

{dimethylfumarate} OR {Fumaderm} OR {FAG 201} OR {FAG201} OR {FAG-201} OR {BG 00012} OR {BG00012} OR {BG-00012} OR {BG 12 compound} OR {BG12 compound} OR {BG-12 compound} OR {BG-12} OR {tecfidera} OR {Nrf2 activator} OR {oral fumarate} OR {fumaric acid eaters}

Contributions of authors

All correspondence: Dian He
Drafting of review versions: Zhu Xu and Dian He
Search for trials: Feng Zhang and FangLi Sun
Obtaining copies of trial reports: KeFeng Gu and Shuai Dong
Selection of trials for inclusion/exclusion: Zhu Xu and Dian He
Extraction of data: Zhu Xu and Dian He
Entry of data: Zhu Xu and Dian He
Interpretation of data analyses: Dian He

Declarations of interest

HD - none

XZ - none

ZF - none

SFL - none

GKF- none

DS - none

Ancillary