Azathioprine for people with multiple sclerosis
Abstract
Objectives
This is a protocol for a Cochrane Review (intervention). The objectives are as follows:
The objectives of the review are to estimate the benefits and harms of:
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azathioprine (AZA) compared with placebo or other disease ‐modifying treatments (DMTs) as first‐choice treatment for relapsing forms of multiple sclerosis (MS);
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AZA compared with placebo or other DMTs for relapsing forms of MS when switching from another DMT;
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AZA compared with placebo or other DMTs as first‐choice treatment for progressive forms of MS; and
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AZA compared with placebo or other DMTs for progressive forms of MS when switching from another DMT.
Background
Description of the condition
Multiple sclerosis (MS) is the most common immune‐mediated, chronic inflammatory demyelinating disease of the central nervous system (CNS). Its typical pathological features include multifocal areas of inflammation, demyelination, and axonal and neuronal loss, with astroglial scarring.
Although clinical features are typical of MS, the disease course is variable. MS is commonly characterized by recurrent relapses or progression, or both, and typically affects young adults (predominantly women in childbearing age). The condition ultimately leads to severe disability. Relapses are considered to be the clinical expression of focal inflammation and subsequent loss of the myelin sheath surrounding axons in the CNS. Relapses may be followed by complete or incomplete recovery.
In 85% of affected people, relapse is the only clinical expression during the early years of MS (the relapsing–remitting phase) (Lublin 2014). Subsequently, in a proportion of patients that increases with time the disease course becomes progressive, with no recovery between relapses and constant worsening of disability. In about 10% to 15% of people affected by MS, the progressive course is not preceded by relapses (Miller 2007); this is known as primary progressive MS (PPMS). Approximately 40% of people with primary or secondary progressive MS show relapses during the course of the disease (Paz 2015). After the introduction of disease‐modifying drugs the risk of conversion to a progressive course has been shown to be reduced compared to untreated patients (Confavreux 2000; Brown 2019; Miller 2007).
The classification of MS into relapsing‐remitting MS (RRMS), secondary progressive MS (SPMS), PPMS and progressive relapsing MS (PRMS) (Lublin 1996) has been used for over 20 years in clinical research and regulatory procedures of disease ‐modifying treatments (DMTs) for relapsing MS. Such classification has recently been reviewed (Lublin 2014) and the concept of “disease activity” was introduced, based on the presence of clinical relapse or new lesions identified by magnetic resonance imaging (MRI). Active forms of MS occur when the inflammatory process is ongoing, sometimes without corresponding clinical manifestations if the inflamed region of the CNS is clinically silent. The 2013 updated classification of MS includes: active or inactive relapsing MS (RMS), with or without worsening; and active or inactive primary or secondary progressive MS, with or without progression. Two new forms were also added: clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS), and the definition of PRMS was abandoned.
Although it is not considered a common condition, MS represents a substantial health burden at a global level, since it affects young people during their productive life (the mean age of diagnosis being 32 years (Walton 2020)). The global incidence and prevalence of MS are increasing. From 1990 to 2016 the age‐standardized prevalence of MS increased by 10.4% due to an increase in its prevalence (GBD 2016). About 2.8 million people worldwide are affected by MS (35.9 per 100,000 population) and this figure increased by about 500,000 since 2013. The global pooled incidence rate is 2.1 per 100,000 persons/year (GBD 2019; Walton 2020).
Currently, no treatment is available to stop the natural course of MS towards progressive disability. Available MS treatments are based on immune‐modulating or immune‐suppressing drugs, also called DMTs, to distinguish them from symptomatic drugs for the treatment of specific symptoms of MS (e.g. urinary incontinence/retention, muscular spasms, painful sensitive symptoms). Relatively few studies directly compare different DMTs or assess the sequential use of specific DMT combinations, therefore clinical practice guidelines on MS treatment usually do not recommend one DMT over the other. The variability of recommendations among guidelines concerning specific drugs in part reflects differences in the decisions by regulatory drug agencies and in regional and local health policies (Ghezzi 2018). Recent approvals of ocrelizumab, siponimod, ozanimod and cladribine mean that, for the first time, people with progressive forms of MS have different treatment options.
A previous Cochrane Review (Casetta 2007) appraised the available evidence from randomized controlled trials (RCTs) on the efficacy and safety of azathioprine (AZA) compared to placebo in MS. A possible risk of malignancy may exist if cumulative doses of 600 g are exceeded. The authors concluded that AZA is an appropriate maintenance treatment for frequently relapsing patients with MS and may be a fair alternative to interferon beta for treating MS.
Description of the intervention
Azathioprine belongs to the class of thiopurines. It is a purine analogue affecting DNA replication through inhibition of the synthesis of nucleic acids. AZA is metabolized by the enzyme thiopurine methyltransferase (TPMT). Some people have very low or absent TPMT levels due to a homozygous mutation of the gene coding for the enzyme; these individuals should not be treated with AZA because the drug is not metabolized, which exposes them to the risk of severe bone marrow suppression. Genetic screening for TPMT deficiency is therefore warranted before starting treatment.
Azathioprine was produced in the mid‐1950s (Elion 1993), and by 1960 it was used in clinical practice (Rundles 1961). Because of its favourable therapeutic index over other traditional immunosuppressants, AZA is frequently used as a corticosteroid‐sparing agent and as monotherapy to treat several chronic inflammatory and autoimmune diseases (e.g. rheumatoid arthritis, inflammatory bowel disease, Crohn’s disease, systemic lupus erythematous, myasthenia gravis, malignancies, and other autoimmune conditions) (McWilliam 2020).
Azathioprine is administered orally as 25 mg or 50 mg tablets. The starting dose in MS is 1 mg per kilogram of body weight per day (mg/kg/day), given as a single dose once or twice daily, gradually increased over four to six weeks to a maintenance dose of 2.5 mg/kg/day to 3 mg/kg/day (100 mg/day to 150 mg/day) and adjusted according to regular monitoring (every two to three months) of white blood cell count. In case of a decrease in white blood cell count or lymphocyte count, a dose reduction of between 25 g and 50 mg is required. AZA is a slow‐acting agent, with therapeutic response being observed after at least three months (and up to six months) of treatment. Side effects are reported in about 10% to 28% of patients treated with AZA, 50% to 80% of whom discontinue the treatment. The most common clinical side effects occurring during treatment, particularly at the beginning of treatment, are gastrointestinal (anorexia, nausea, vomiting). These affect about 12% of patients with MS treated with AZA (Invernizzi 2008) and can be prevented by taking the drug close to meals.
Dose‐dependent, reversible leukopenia and thrombocytopenia may be a consequence of bone marrow suppression in 27% and 5% of people treated with AZA, respectively. Bacterial, viral and fungal infections associated with immunosuppression occur with a frequency of about 9% (Lallana 2011; Huskisson 1984; Weinshilboum 1980). Long‐term adverse events may include the risk of malignancy (lymphoma, skin cancer), although data on patients with MS are inconsistent (Amato 1993; Lhermitte 1984). Evidence from transplant recipients treated with AZA suggests that cancer risk may be dose‐related, although such possibility is still debated (Na 2016; Pasternak 2013).
How the intervention might work
The pathophysiology of MS supports the use immunosuppressive medications (Compston 2002; Massacesi 2002). T‐cell‐mediated immune response has a central role in the pathogenesis of MS. Indeed, an increased number of T‐lymphocytes, specific for myelin and other CNS antigens, has been observed in people with MS; these, together with B‐cells, are thought to initiate and perpetuate the immune component of the disease, as suggested by the presence of oligoclonal bands of immunoglobulin G in the cerebrospinal fluid of people with MS.
In the pathophysiological process of tissue damage in MS, T‐cell death through apoptosis (namely, activation‐induced T‐cell death) is involved. Evidence suggests that the elimination of autoreactive lymphocytes through apoptosis is reduced in people with MS, thereby maintaining a chronic cycle of inflammation (Ruggieri 2005). Therefore, drugs acting as modulators of apoptosis may be of therapeutic value (Zipp 2000).
In vitro studies show that AZA‐induced apoptosis can be observed particularly on CD45RO, a specific subset of memory T‐cells considered to be key effectors in autoimmune diseases such as inflammatory bowel disease (Tiede 2003; Zipp 2000). Such a mechanism, which is shared by other agents effective in MS (e.g. glatiramer acetate), could explain the immunosuppressive effects of AZA and its therapeutic action in MS through the elimination of pathogenic memory T‐cells, and the subsequent reduction of tissue damage and therefore less severe disease (Ruggieri 2005; Zipp 2000). AZA shows an immunosuppressive activity due to the interference with nucleic acid synthesis during the cellular multiplication that follows B‐ and T‐cell activation. Moreover, the purine antagonist effect inhibits the synthesis of RNA and DNA during replication of nucleic acid and the T‐cell‐dependent antibody‐mediated response (Invernizzi 2008).
Apoptosis of peripheral T‐cells is additionally induced by AZA and its metabolites through suppression of the activation of the RAC1 gene, coding for the RAC1 protein, and interfering with CD28 co‐stimulation of alloreactive T‐lymphocytes, mediated by the Rac1 GTPase (Tiede 2003). These observations are confirmed by studies on people with Crohn’s disease and RAC1 has also recently been exploited as a therapeutic target of cancer treatments (Cannon 2020; Tiede 2003).
Why it is important to do this review
Azathioprine is not approved by the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA) for the treatment of MS, although in some European countries it is used and reimbursed (AIFA 2020; Hommes 2004; Kieseier 2010). In clinical practice, AZA has been used to treat MS for over 40 years. Newer DMTs offer a broad spectrum of treatment options, although the most effective drugs are not always well tolerated and their cost may represent a substantial barrier to their use in settings with budget constrains (Zeineddine 2020). Recently published guidelines include off‐label use of AZA for people who do not have access to approved DMTs among therapeutic options (Rae‐Grant 2018; Yamout 2019).
A previously published Cochrane Review (Casetta 2007) on the efficacy and safety of AZA versus placebo in people with MS concluded that AZA may be an alternative to interferon beta, with a favourable benefit‐to‐risk ratio; however, this conclusion was not supported by direct evidence, since the review included only placebo‐controlled RCTs. The authors suggested that a goal for future research would have been direct comparisons of AZA with interferon beta. Moreover, a potentially increased risk of malignancy associated with high cumulative doses of AZA could not be excluded.
Ensuring timely access to safe and effective treatments for people with MS is warranted. Since AZA has been long used off‐label in people with MS, an updated systematic review of the available evidence on its efficacy and safety would be valuable to inform shared healthcare decisions by practitioners, policy makers, people with MS and their families.
Similarly to what has been noted about rituximab (Greenflield 2018), given that patent protection of AZA has expired, it is unlikely that a registered clinical trial to broaden the indication of AZA to MS will ever be undertaken, and it is therefore unlikely that new evidence on benefits and harms of AZA for MS will be provided by RCTs.
The above considerations have prompted us to perform an updated systematic review including both RCTs and non‐randomized studies of intervention (NRSI) to assess new available evidence on the efficacy and safety of AZA in people with MS. This new protocol outlines the methods we will undertake for a new version of the review.
Objectives
The objectives of the review are to estimate the benefits and harms of:
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azathioprine (AZA) compared with placebo or other disease ‐modifying treatments (DMTs) as first‐choice treatment for relapsing forms of multiple sclerosis (MS);
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AZA compared with placebo or other DMTs for relapsing forms of MS when switching from another DMT;
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AZA compared with placebo or other DMTs as first‐choice treatment for progressive forms of MS; and
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AZA compared with placebo or other DMTs for progressive forms of MS when switching from another DMT.
Methods
Criteria for considering studies for this review
Types of studies
We will include parallel RCTs and controlled NRSIs of between‐group design, open‐label extension studies, cohort and case‐control studies. NRSIs may be useful to assess safety related to long‐term and rare adverse effects, thereby informing clinical decisions if evidence from RCTs is lacking. We will not include cluster‐randomized and cross‐over trials to evaluate treatment with AZA in people with MS. We will exclude case reports and studies of within‐group design, e.g. before‐after (pre‐post) studies with no control group, or interrupted time series.
Given the natural course of MS and the time scale of the expected effects of AZA on efficacy outcomes (e.g. disability progression, frequency of relapse), we will consider only studies with a follow‐up of 12 months or longer. We will include full‐text publications, results published in non‐commercial trial registries (e.g. ClinicalTrials.gov) and abstracts, whenever sufficient information is available on study design, characteristics of participants, interventions and outcomes.
Types of participants
We will include adult participants (aged 18 years or older) of either sex, who are treatment‐naive or non‐responsive to treatment with DMTs. We will accept any definition of non‐response reported in the included studies. We will include studies adopting any diagnostic criteria for MS. We will include all types of MS, i.e. RRMS, SPMS and PPMS, regardless of disease duration and degree of disability.
Types of interventions
Experimental intervention
We will consider treatment with AZA as monotherapy or in combination with other treatments, regardless of dose, disease duration, and frequency of administration. We will consider AZA in combination with other treatments, provided that such treatments are used in all comparison groups. We will include studies assessing AZA in treatment‐naive people with MS, as well as those investigating switching from a previous different DMT, regardless of the reason for switching, method, or timing of the switching.
Comparison intervention
The comparator interventions will be placebo or any other DMT.
Types of outcome measures
An initial list of the outcomes of this review was identified by the authors and subsequently refined with the input of the members of a multi‐stakeholder guideline development group (including consumers, advisory groups, clinicians and other healthcare professionals with experience in the field of MS), aimed at producing evidence‐based recommendations on the use of AZA in MS. We will include short‐term and long‐term adverse outcomes reported in the included studies. Adverse effects will be assessed according to an exploratory approach (Peryer 2020).
Primary outcomes
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Disability: number of participants with sustained disability worsening based on clinical follow‐up visits at 24 months or more after randomization. Worsening is defined as at least one increased point on the Expanded Disability Status Scale (EDSS) (Kurtzke 1983), or a 0.5‐point increase if the baseline EDSS was greater than 5.5, confirmed during two consecutive clinical examinations separated by an interval of at least six months free from relapse and carried out by the same physician. EDSS is an ordinal scale where 0 is normal, 3 indicates mild disability, 6 indicates care requirement, 7 indicates wheelchair use, and 10 indicates death from MS. An advantage of the EDSS over other disability measures is its international acceptance, e.g. by the EMA (EMA 2015), as a primary end point in clinical trials. It is also widely used in trials, enabling cross‐study comparisons (Meyer‐Moock 2014).
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Relapse: number of participants with clinical relapse based on clinical follow‐up visits at 12 months or more after randomization. Relapse is defined as the appearance of one or more new symptoms due to MS, or the deterioration of pre‐existing symptoms, persisting more than 24 hours in the absence of fever and preceded by a period of stability of at least one month (McDonald 2001).
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Serious adverse events (SAEs): number of participants with SAEs, defined according to the authors of the study. If an insufficient number of studies report the total number of SAEs and person‐years, we plan to use the number of participants with at least one SAE as defined in the study. If there is sufficient information available, we will specify individual SAEs.
Secondary outcomes
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Annualized relapse rate (ARR): mean number of new relapses per patient, adjusted for the duration of follow‐up to annualize it.
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Cognitive decline: number of participants with cognitive worsening assessed according to validated neurocognitive batteries for MS, e.g. the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) (Benedict 2020; Langdon 2012).
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Quality‐of‐life impairment: number of participants reporting quality‐of‐life impairment, assessed according to validated measures, among which the Multiple Sclerosis Quality of Life‐54 (MSQOL‐54) is a multidimensional health‐related quality‐of‐life measure (Vickrey 1995). MSQOL‐54 includes the generic 36‐Item Short Form Survey instrument, supplemented with 18 MS‐specific items that were based on expert opinion and literature review. There is no single overall score for MSQOL‐54. Two summary scores — physical health and mental health — can be derived from a weighted combination of scale scores (scale scores range from 0 to 100 and an increase of the score indicates improved quality of life).
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New or enlarging T2‐weighted MRI lesions: number of participants with new or enlarging T2‐weighted MRI lesions at 12 months or longer after randomization.
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New gadolinium‐enhancing positive T1‐weighted MRI lesions: number of participants with new gadolinium‐enhancing T1‐weighted MRI lesions at 12 months or longer after randomization.
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Adverse events: number of participants with any adverse event, regardless of severity. We will include clinical as well as instrumental adverse events, as defined in the study.
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Short‐term adverse effects: number of participants with drug‐specific short‐term adverse effects. “Short‐term adverse effect” is defined as a problem caused by a treatment that usually goes away after treatment ends (NCI 2021). These will include: gastrointestinal disorders, immune system disorders, skin and subcutaneous tissue disorders.
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Long‐term adverse effects: number of participants with drug‐specific long‐term adverse effects, as reported in the included studies. "Long‐term adverse effects" are defined as problems caused by a treatment that may continue for months or years (NCI 2021). Such AEs may be associated with dose accumulation of AZA and will include: infections and infestations (viral, bacterial, or fungal); neoplasms; blood and lymphatic system disorders; gastrointestinal disorders; hepatobiliary disorders; immune system disorders; skin and subcutaneous tissue disorders; CNS disorders.
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Treatment discontinuation due to adverse events: number of patients who discontinued treatment due to adverse events, regardless of their severity.
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Mortality: overall number of deaths.
Search methods for identification of studies
Electronic searches
We will identify eligible study references through systematic searches of the following bibliographic databases (see Appendix 1):
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Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library) (latest issue);
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MEDLINE (PubMed) (1966 to date); and
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Embase (Embase.com) (1974 to date).
Searching other resources
We will search for ongoing studies on the following databases (see Appendix 1):
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World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP); and
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US National Institutes of Health clinical trial register (ClinicalTrials.gov).
We will check reference lists of all included studies and any relevant systematic reviews identified for additional references to studies. We will examine any relevant retraction statements and errata for included studies. We will search for NRSIs according to the methods described in the Section 24.3 of the Cochrane Handbook for Systematic Reviews of Interventions (Reeves 2020 ).
Data collection and analysis
Selection of studies
Data management and extraction will be conducted in accordance with the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2020). Two review authors (FN and EB) will independently screen the titles and abstracts of the search results and discard studies that are clearly not relevant. They will independently assess all potentially relevant articles as full text.
Two review authors (FN and EB) will compare multiple reports of the same study and use the most comprehensive report. They will link together multiple publications as companion reports but exclude true duplicates. We will resolve any discrepancies by discussion and report excluded studies, together with reasons for exclusion, in the ‘Characteristics of excluded studies’ table.
Abstracts and full texts in all languages will be considered for inclusion. All potentially eligible non‐English‐language abstracts will progress to full‐text review, with methods translated for eligibility and the full text translated for data extraction.
We will report included studies in the ‘Characteristics of included studies’ table. We will create a PRISMA flow chart reporting the selection process (Liberati 2009).
Data extraction and management
Two pairs of review authors (BR and EB, IC and GI) will independently extract data from the studies included in the analysis using a predefined data extraction form in an Excel spreadsheet. We will pilot the data extraction form on at least one study in the review. We will resolve disagreements by discussion. If necessary, a third review author (GF) will be consulted. We will manage and synthesise the available data using RevMan Web (RevMan Web 2020). One review author (BR) will transfer data into RevMan Web, while two review authors (IC, GI) will double‐check the transferred data for accuracy by comparing the data presented in the systematic review with the data extraction form.
From each included study we will extract the following data.
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Study details: first author or acronym; year of publication; number of centres and location; study setting; study duration (total study duration, recruitment stage and follow‐up); type of publication (full‐text publication, abstract publication, unpublished data).
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Study design (RCT or NRSI); for NRSI, type of design; inclusion and exclusion criteria; number of participants in each arm; number of withdrawals; early termination of trial.
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Participants: age; sex; diagnostic criteria; type and duration of MS; important baseline data (EDSS score, proportion of participants with previous use of DMTs; MRI brain lesions).
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Interventions: whether participants are treatment‐naive or switching from a different treatment; comparison(s); concomitant medications.
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Data analysis: type of estimate(s) provided; subgroup analysis, if performed.
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Outcomes: primary and secondary outcomes specified and collected; method of outcome measurement; outcome time points reported; for NRSIs: confounding factors for which the study authors performed adjustment.
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Disclosure of interests of study authors; funding source of the study.
For continuous outcomes we will extract mean and standard deviation of the comparison groups, where possible. We will extract arm‐level data when possible. Should arm‐level data not be available we will extract effect sizes. We will extract data at the authors' defined time points.
Randomized controlled trials
Two review authors (EB, FN) will independently assess the risk of bias of each included study using the first version of the Cochrane 'Risk of bias' tool (Higgins 2017). The recommended two‐part tool to assess the risk of bias addresses specific domains of sequence generation and allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessors (detection bias), incomplete outcome data (attrition bias), and selective outcome reporting (reporting bias). In the first part of the tool the assessor describes what was reported to have occurred in the study, while in the second part a judgement (low, high, or unclear) is provided about the risk of bias for each domain (see Appendix 2).
Non‐randomized studies
Two review authors (EB, IC) will independently assess the risk of bias using the ROBINS‐I tool for NRSI (Sterne 2016). Based on the inclusion and exclusion criteria for this review, we define our generic target trial as comparing AZA versus placebo or versus other DMTs for the treatment of people with MS. We therefore will use the ROBINS‐I analogue of starting experimental intervention versus starting control intervention to evaluate risk of bias. The ROBINS‐I tool includes the following bias domains: confounding, selection of participants into the study, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes and selection of reported result. We will assign an overall 'Risk of bias' judgement to each study based on the worst assessment across all bias domains, using the recommended levels (low, moderate, serious or critical risk of bias or no information) (Sterne 2016). We will resolve any disagreements between the review authors by discussion.
For each NRSI we will use the 'Risk‐Of‐Bias VISualization' (robvis) tool to create the 'Risk of bias' graphs (McGuinness 2021). We will assess if the authors of the study considered the following potential confounders, if they were controlled for, and which method (statistical adjustment) was used by the authors to reduce confounding.
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Confounding by indication (pre‐intervention confounder) when starting treatment in treatment‐naive people with MS. In this scenario, more severe cases (e.g. severity determined by number of relapses in the previous year) are likely to be assigned to more effective treatments (e.g. fingolimod, natalizumab) whereas participants with low pretreatment MS activity are likely to be treated with less powerful drugs (e.g. interferon beta). Baseline confounding by indication is likely the most frequent confounder in NRSIs. A cohort study directly comparing DMTs for MS should control for age, sex, MS duration, relapses, EDSS score and MRI activity measured before the start of DMT, because these are prognostic for the outcomes “relapse” and “disability worsening” and are also likely to influence treatment choice.
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Confounding by indication when shifting from a previous treatment to the treatment of interest (pre‐intervention confounder, see the considerations above).
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Duration of follow‐up from the start of the treatment of interest or the control treatment (confounder during the intervention). In some NRSIs, particularly those based on registries (i.e. routinely collected data), participants may be observed for different follow‐up periods due to differences in drug licensing and availability across different geographical and historical cohorts (Trojano 2017). Such difference in follow‐up duration may be a confounder, particularly on medium‐ and long‐term outcomes.
Adverse events
We will assess characteristics associated with the monitoring and reporting of adverse events considering specific factors that may have a large influence on adverse event data. We will evaluate methods of monitoring and detecting adverse events in each primary study in order to assess if the researchers:
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actively monitored for adverse events, or if they simply provided spontaneous reporting of adverse events; and
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defined adverse events according to an accepted international classification.
We will report such information in an additional table titled 'Assessment of adverse events monitoring'.
Measures of treatment effect
For dichotomous outcomes, we will report risk ratio (RR) and 95% confidence intervals (CIs). For continuous outcomes we will calculate mean difference (MD) or standardised mean difference (SMD) if the same continuous outcome was measured with different metrics. We will back‐calculate any results that we generate with a SMD based on scales that most closely reflect the outcome measure of interest to the review, as listed under important outcomes.
Unit of analysis issues
For multi‐armed trials, the intervention groups of interest will be those that can be included in a pairwise comparison of intervention groups which, if investigated alone, would have met the criteria for including studies in the review.
For example, if we will identify a study comparing AZA versus glatiramer acetate versus AZA plus glatiramer acetate, only one comparison (AZA versus glatiramer acetate) will be used since it addresses the review objective. However, if the study compares AZA versus glatiramer versus fingolimod, all pairwise comparisons of interventions are relevant to the review. In this scenario, we will treat multi‐armed studies as multiple independent two‐arm studies assessed in separate comparisons.
Dealing with missing data
We will use data that reflect the intention‐to‐treat analysis for each included outcome, with the exception of adverse events. In order to assess the effect of unreported missing outcome data, we will assume that missing participants in both the intervention and the control group had an unfavourable outcome.
Assessment of heterogeneity
To evaluate clinical heterogeneity within treatment comparisons, we will assess differences in types of MS, type of interventions across the trials, and study duration. We will assess the presence of statistical heterogeneity using the I2 statistic (Higgins 2003). An I2 value of greater than 30% will be considered to represent moderate heterogeneity, and a value greater than 75% will be considered to represent considerable heterogeneity (Deeks 2020). In the latter case, we will explore possible explanations through subgroup and sensitivity analysis.
Assessment of reporting biases
If we are able to pool more than 10 clinically and methodologically consistent studies, we will evaluate the possibility of reporting bias for the primary outcomes by means of contour‐enhanced funnel plots (Peters 2008). Contour‐enhanced funnel plots show areas of statistical significance and help distinguish reporting bias from other possible reasons for asymmetry in the plot (plot asymmetry indicates the presence of small‐study effects and not necessarily reporting bias). If visual assessment of funnel plots suggest asymmetry, we will use formal tests (Sterne 2011).
Data synthesis
We will conduct an initial qualitative comparison of all the individually included studies to examine whether pooling of results (meta‐analysis) will be reasonable. This will take into account differences in study populations, inclusion and exclusion criteria, interventions and outcome assessment. If we cannot perform meta‐analyses, we will present the results from all included studies in tables and comment on the results as a narrative. We will conduct separate meta‐analysis for RCTs and (if possible) for NRSIs. If a meta‐analysis will be feasible for NRSIs we plan to analyse the different types of NRSIs separately.
We will conduct separate meta‐analyses for relapsing and progressive forms of MS, and for populations who are either treatment naive or switching from other DMTs. For dichotomous outcomes, we will base the estimation of the between‐study variance using the Mantel‐Haenszel method. We will use a random‐effects model because a certain degree of heterogeneity is expected among studies. We assume that studies are not all estimating the same intervention effect and that such intervention effects follow a normal distribution across studies (DerSimonian 1986). For NRSIs, we plan to only analyse outcomes with adjusted effect estimates if these were adjusted for the same factors using the inverse‐variance method, as recommended in Chapter 24 of the Cochrane Handbook for Systematic Reviews of Interventions (Reeves 2020).
Synthesis without meta‐analysis
If we will identify substantial clinical, methodological, or statistical heterogeneity across studies that prevents pooling of data, we will use a narrative approach to data synthesis by presenting results in a structured tabulated format, ordering outcomes according to risk of bias (McKenzie 2020). Reporting of synthesis without meta‐analysis will be performed according to the Synthesis Without Meta‐analysis (SWiM) guideline (Campbell 2020).
Subgroup analysis and investigation of heterogeneity
If possible, we will perform subgroup analysis for the primary outcomes by using the characteristics of the population (active MS; non‐active MS) as effect modifiers and possible sources of heterogeneity.
Sensitivity analysis
We will assess the impact of studies that we judge to be at high risk of bias in any domain, by removing them from the analyses for primary and secondary outcomes. We will consider different assumptions relating to missing outcomes as the basis for sensitivity analyses.
Summary of findings and assessment of the certainty of the evidence
We will present the main results of the review in 'Summary of findings' tables, according to recommendations described in Chapter 14 of the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2020). Two review authors (EB, FN) will assess the certainty of evidence for each primary outcome, considering risk of bias, indirectness, inconsistency, imprecision of effect estimates, and risk of publication bias. Reasons for downgrading the certainty in the estimates of studies will be provided in footnotes. Certainty in the estimates will be appraised by means of the GRADEpro GDT software (GRADEproGDT), defining one of four levels of certainty of evidence: high, moderate, low, or very low.
In the 'Summary of findings' tables, we will prioritise long‐term outcomes, if available; otherwise, we will include short‐term outcomes. We plan to present four such tables, addressing the following comparisons in RMS or PMS:
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AZA as a first‐choice treatment compared with other DMTs for RMS;
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AZA when switching from a different DMT compared with other DMTs for RMS;
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AZA as a first‐choice treatment compared with other DMTs for PMS; and
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AZA when switching from a different DMT compared with other DMTs for PMS.
We will include the following additional comparisons in the "Additional tables" section:
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AZA as a first‐choice treatment compared with placebo for RMS;
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AZA when switching from a different DMT compared with placebo for RMS;
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AZA as a first‐choice treatment compared with placebo for PMS; and
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AZA when switching from a different DMT compared with placebo for PMS.
We will assess certainty of evidence for the following outcomes in the 'Summary of findings' tables:
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disability
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relapse
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serious adverse events (SAEs)
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quality‐of‐life impairment
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long‐term adverse events
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mortality
