Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs). We will include studies reported as full-text, those published as abstract only, and unpublished data as long as we can assess the risk of bias of the study. There will be no language restriction.
Types of participants
We will include adults of age >=50 with giant cell arteritis satisfying either the American College of Rheumatology 1990 criteria for the classification of giant cell arteritis (Hunder 1990) or the definition proposed in the 2012 revised International Chapel Hill Consensus Conference nomenclature (Jennette 2013). The limit for age of at least 50 is based on the knowledge that GCA is diagnosed almost exclusively in patients older than 50 (Gonzalez-Gay 2009), and this fact is reflected in the current criteria for GCA (Hunder 1990; Jennette 2013)
Types of interventions
We will include trials comparing methotrexate (with or without folic acid) with placebo or any active comparator for a minimum duration of 12 weeks. Adjuvant treatments are allowed as long as they are present in both arms. Since methotrexate may have steroid-sparing effect, difference in corticosteroid dose between treatment arms will be allowed. Intra-articular corticosteroids will be allowed and will not be considered adjuvant treatments nor will be counted towards the cumulative corticosteroid dose when possible. Intravenous or Intramuscular corticosteroids will be counted towards cumulative corticosteroid dose in terms of prednisone equivalent of the administered formulation.
Types of outcome measures
The OMERACT Vasculitis Working group is currently working on developing the core set of outcome measures for giant cell arteritis (Aydin 2015). We will follow their recommendations when their work is completed, but for the time being we have identified the following set of outcomes based on our experience in clinical practice and outcomes-related research.
All major outcomes will be assessed at week 52 (1 year) or closest reported time point.
1. Proportion of patients who experience at least one relapse. Relapse will be defined as increase of the dose of corticosteroids or methotrexate (for patients on methotrexate), reintroduction of corticosteroids (if they have been discontinued), or addition of another immunosuppressive agent (other than methotrexate) to suppress either inflammatory markers (biochemical relapse) or any GCA-related clinical symptoms (clinical relapse).
2. Time to sustained discontinuation of corticosteroids defined as discontinuation for at least 12 weeks. If time-to-event data is not reported, proportions of participants who have achieved sustained discontinuation of corticosteroids will be reported.
3. Cumulative dose of glucocorticoids
4. Proportion of patients with cranial ischemic complications including vision loss and cerebrovascular events caused by active GCA
5. Health-related quality of life
6. Short term serious adverse effects, defined as events requiring hospitalization or resulting in death
7. Withdrawals due to adverse events
1. All major outcomes will be measured at the following additional time points (or the closest reported timepoints): week 12, 26 (6 months), 78 (18 months), and 104 (24 months)
2. Time to disease remission defined as normalization of inflammatory markers and absence of signs and symptoms of GCA. If time-to-event data is not reported for remission, proportions of participants who are in remission at each of the pre-specified time points will be reported
3. Proportion of patients who experience more than one relapse
4. Time to 1st relapse and time to 2nd relapse
6. Development of glucocorticoid complications e.g. osteoporosis, fragility fractures, hypertension, hyperglycaemia
Search methods for identification of studies
We will search the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and EMBASE.
We will also conduct a search of ClinicalTrials.gov (www.ClinicalTrials.gov) and the WHO trials portal (www.who.int/ictrp/en/).
We will search all databases from their inception to the present, and we will impose no restriction on language of publication.
See Appendix 1 for the MEDLINE search strategy.
Searching other resources
We will check reference lists of all primary studies and review articles for additional references. We will search relevant manufacturers' websites for trial information.
We will search for errata or retractions from included studies published in full-text on PubMed (www.ncbi.nlm.nih.gov/pubmed) and report the date this was done within the review.
Data collection and analysis
Selection of studies
Two review authors will independently screen titles and abstracts for inclusion of all the potential studies we identify as a result of the search and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. We will retrieve the full-text study reports/publication and two review authors will independently screen the full-text and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third person. We will identify and exclude duplicates and collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table.
Data extraction and management
We will use a data collection form for study characteristics and outcome data which has been piloted on at least one study in the review. Two review authors will extract study characteristics from included studies. We will extract the following study characteristics:
Methods: study design, total duration of study, details of any 'run in' period, number of study centres and location, study setting, withdrawals, and date of study.
Participants: N, mean age, age range, sex, disease duration, severity of condition, diagnostic criteria, important [condition-specific] baseline data; inclusion criteria, and exclusion criteria.
Interventions: intervention, comparison, concomitant medications, and excluded medications.
Outcomes: primary and secondary outcomes specified and collected, and time points reported.
Characteristics of the design of the trial as outlined below in the 'Assessment of risk of bias in included trials' section.
Notes: funding for trial, and notable declarations of interest of trial authors.
Two review authors will independently extract outcome data from included studies. The number of events and number of participants per treatment group for dichotomous outcomes, and means and standard deviations and number of participants per treatment group for continuous outcomes will be extracted. We will note in the 'Characteristics of included studies' table if outcome data was not reported in a usable way and when data was transformed or estimated from a graph. We will resolve disagreements by consensus or by involving a third person. One review author will transfer data into the Review Manager (RevMan 2012) file. We will double-check that data is entered correctly by comparing the data presented in the systematic review with the study reports.
Data analysed based on an intention-to-treat sample will be preferentially used for the analysis.
The Short Form 36 health survey (SF-36) (McHorney 1992) will be preferentially used to measure health-related quality of life, if it is reported.
If both unadjusted and adjusted values for the same outcome are reported, the unadjusted values will be used to allow comparison/compatibility between studies.
Assessment of risk of bias in included studies
Two review authors will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreements by discussion or by involving another author. We will assess the risk of bias according to the following domains.
Random sequence generation.
Blinding of participants and personnel.
Blinding of outcome assessment.
Incomplete outcome data.
Selective outcome reporting.
Other bias: Imbalance on baseline values, source of funding.
We will grade each potential source of bias as high, low or unclear and provide a quote from the study report together with a justification for our judgment in the 'Risk of bias' table. We will summarise the risk of bias judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes where necessary (e.g. for unblinded outcome assessment, risk of bias for all-cause mortality may be different than for a patient reported pain scale). As well, we will consider the impact of missing data by key outcomes.
Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table.
When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome.
We will present the figures generated by the risk of bias tool to provide summary assessments of the risk of bias.
Assesment of bias in conducting the systematic review
We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.
Measures of treatment effect
We will analyse dichotomous data as risk ratios or Peto odds ratio when the outcome is a rare event (approximately less than 10%), and use 95% confidence intervals. Continuous data will be analyzed as mean difference or standardised mean difference, depending on whether the same scale is used to measure an outcome, and 95% confidence intervals. We will enter data presented as a scale with a consistent direction of effect across studies.
When different scales are used to measure the same conceptual outcome (e.g. disability), standardised mean differences (SMD) will be calculated instead, with corresponding 95% CI]. SMD will be back-translated to a typical scale (e.g. 0 to 10 for pain) by multiplying the SMD by a typical among-person standard deviation (e.g. the standard deviation of the control group at baseline from the most representative trial) (as per Chapter 12 of the Cochrane Handbook (Schünemann 2011b))
We will analyze time-to-event data as hazard ratios. Rate data will be analyzed using Poisson methods.
In the 'Effects of intervention' results section and the 'Comments' column of the Summary of findings table, we will provide the absolute percent difference, the relative percent change from baseline, and the number needed-to-treat (NNT) (the NNT will be provided only when the outcome shows a statistically significant difference).
For dichotomous outcomes, such as serious adverse events, the number needed to treat will be calculated from the control group event rate and the relative risk using the Visual Rx NNT calculator (Cates 2008). The NNT for continuous measures will be calculated using the Wells calculator (available at the CMSG Editorial office).
For dichotomous outcomes, the absolute risk difference will be calculated using the Risk Difference statistic in RevMan and the result expressed as a percentage. For continuous outcomes, the absolute benefit will be calculated as the improvement in the intervention group minus the improvement in the control group, in the original units.
The relative percent change for dichotomous data will be calculated as the Risk Ratio - 1 and expressed as a percentage. For continuous outcomes, the relative difference in the change from baseline will be calculated as the absolute benefit divided by the baseline mean of the control group.
Unit of analysis issues
Where multiple trial arms are reported in a single trial, we will include only the relevant arms. If two comparisons (e.g. drug A versus placebo and drug B versus placebo) are combined in the same meta-analysis, we will halve the control group to avoid double-counting.
Dealing with missing data
We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when a study is identified as abstract only or when data is not available for all participants). Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis. Any assumptions and imputations to handle missing data will be clearly described and the effect of imputation will be explored by sensitivity analyses.
For dichotomous outcomes (e.g. number of withdrawals due to adverse events), the withdrawal rate will be calculated using the number of patients randomised in the group as the denominator.
For continuous outcomes (e.g. cumulative glucocorticoid dose), we will calculate the MD or SMD based on the number of patients analysed at that time point. If the number of patients analysed is not presented for each time point, the number of randomised patients in each group at baseline will be used. If corticosteroid formulations other than prednisone are used, we will convert the cumulative dose to prednisone equivalent.
Where possible, missing standard deviations will be computed from other statistics such as standard errors, confidence intervals or P-values, according to the methods recommended in the Cochrane Handbook for Systematic Reviews of Interventions. If standard deviations cannot be calculated, they will be imputed (e.g. from other studies in the meta-analysis).
Assessment of heterogeneity
Clinical and methodological diversity will be assessed in terms of participants, interventions, outcomes and study characteristics for the included studies to determine whether a meta-analysis is appropriate. This will be conducted by observing this data from the data extraction tables. Statistical heterogeneity will be assessed by visual inspection of the forest plot to assess for obvious differences in result between the studies, and using the I² and chi² statistical tests.
As recommended in the Cochrane Handbook (Deeks 2011), the interpretation of an I² value of 0% to 40% might 'not be important'; 30% to 60% may represent 'moderate' heterogeneity; 50% to 90% may represent 'substantial' heterogeneity; and 75% to 100% represents 'considerable' heterogeneity. As noted in the Handbook, we will keep in mind that the importance of I2 depends on (i) magnitude and direction of effects and (ii) strength of evidence for heterogeneity.
The chi² test will be interpreted where a P-value ≤ 0.10 will indicate evidence of statistical heterogeneity.
If we identify substantial heterogeneity we will report it and investigate possible causes by following the recommendations in section 9.6 of the Handbook.
Assessment of reporting biases
We will create and examine a funnel plot to explore possible small study biases. In interpreting funnel plots, we will examine the different possible reasons for funnel plot asymmetry as outlined in section 10.4 of the Handbook and relate this to the results of the review. If we are able to pool more than 10 trials, we will undertake formal statistical tests to investigate funnel plot asymmetry, and will follow the recommendations in section 10.4 of the Handbook (Sterne 2011).
To assess outcome reporting bias, we will check trial protocols against published reports. For studies published after 1st July 2005, we will screen the Clinical Trial Register at the International Clinical Trials Registry Platform of the World Health Organisation (http://apps.who.int/trialssearch) for the a priori trial protocol. We will evaluate whether selective reporting of outcomes is present.
We will undertake meta-analyses only where this is meaningful i.e. if the treatments, participants and the underlying clinical question are similar enough for pooling to make sense.
We will use a fixed-effect model and perform a sensitivity analysis with the random model.
Summary of findings table
We will create a 'Summary of findings' table using the following outcomes: proportion of patients who experience at least one relapse, time to sustained discontinuation of corticosteroids, cumulative dose of glucocorticoids, proportion of patients with cranial ischemic complications, health-related quality of life, short term serious adverse effects, and withdrawals due to adverse events. The comparison in the first SoF table will be placebo. Other active comparators (if applicable) will be listed in the other SOF tables.
Two people will independently assess the quality of the evidence. We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies which contribute data to the meta-analyses for the prespecified outcomes. We will use methods and recommendations described in Section 8.5, 8.7 and Chapter 11 and chapter 13 section 13.5 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011; Schünemann 2011a) using GRADEpro software. We will justify all decisions to down- or up-grade the quality of studies using footnotes and we will make comments to aid reader's understanding of the review where necessary.
In the Comments column of the Summary of findings table, we will provide the absolute percent difference, the relative percent change from baseline, and the number needed-to-treat (NNT) (the NNT will be provided only when the outcome shows a statistically significant difference).
For dichotomous outcomes, such as serious adverse events, the number needed to treat will be calculated from the control group event rate and the relative risk using the Visual Rx NNT calculator (Cates 2008). The NNT for continuous measures will be calculated using the Wells calculator (available at the CMSG Editorial office, http://musculoskeletal.cochrane.org/).
For dichotomous outcomes, the absolute risk difference will be calculated using the Risk Difference statistic in RevMan and the result expressed as a percentage. For continuous outcomes, the absolute benefit will be calculated as the improvement in the intervention group minus the improvement in the control group (mean difference), in the original units, and expressed as a percentage.
The relative percent change for dichotomous data will be calculated as the Risk Ratio - 1 and expressed as a percentage. For continuous outcomes, the relative difference in the change from baseline will be calculated as the absolute benefit divided by the baseline mean of the control group, expressed as a percentage.
Subgroup analysis and investigation of heterogeneity
We plan to carry out the following subgroup analyses.
Age (<=65, > 65), based on the knowledge that age may have an effect on physiologic response to certain medications, including incidence and severity of adverse events (Pagnoux 2015).
Sex, due to the potential effect hormonal environment can have on one's response to and tolerance of medications for GCA, similar to its effect on the incidence of this condition (Ponte 2015).
Histologic versus clinical diagnosis of GCA, based on existing evidence that the clinical phenotypes of these two groups of GCA differ (Gonzalez-Gay 2001), which may in turn translate into differences in response to therapies.
Dose of MTX (<= 15mg versus = 15mg per week); while the standard dosing of low-dose methotrexate for rheumatoid arthritis and other inflammatory conditions is 20 to 25mg per week, all but one patients included in the individual-case metaanalysis performed by Marh et al (Mahr 2007) were on maximum dose of 15mg; comparing of groups with the cut-off of 15mg would allow demonstration of a dose effect, if such exists (Mahr 2007).
We will use the 7 main outcomes in subgroup analyses.
We will use the formal test for subgroup interactions in Review Manager (RevMan 2012) and will use caution in the interpretation of subgroup analyses as advised in section 9.6 of the Handbook. The magnitude of the effects will be compared between the subgroups by means of assessing the overlap of the confidence intervals of the summary estimated. Non-overlap of the confidence intervals indicates statistical significance.
We plan to carry out the following sensitivity analyses.
Risk of bias
Formulation of MTX
Use of intravenous and intramuscular corticosteroids
Interpreting results and reaching conclusions
We will follow the guidelines in the Cochrane Handbook, chapter 12 (Schünemann 2011b), for interpreting results and will be aware of distinguishing a lack of evidence of effect from a lack of effect. We will base our conclusions only on findings from the quantitative or narrative synthesis of included studies for this review. We will avoid making recommendations for practice and our implications for research will suggest priorities for future research and outline what the remaining uncertainties are in the area.