PROSPERO International prospective register of systematic reviews
Defining the optimal biological monotherapy in rheumatoid arthritis: network meta-analysis of randomized trials
Robin Christensen, Simon Tarp, Tove Lorenzen, Daniel Furst, Michael Hansen, Jasvinder Singh, Ernest Choy, Maarten Boers, Maria Suarez-Almazor, Bo Ejbjerg, Mikkel Østergaard, Henning Bliddal
Robin Christensen, Simon Tarp, Tove Lorenzen, Daniel Furst, Michael Hansen, Jasvinder Singh, Ernest Choy, Maarten Boers, Maria Suarez-Almazor, Bo Ejbjerg, Mikkel Østergaard, Henning Bliddal. Defining the optimal biological monotherapy in rheumatoid arthritis: network meta-analysis of randomized trials.
Available from http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42012002800
To review the evidence for efficacy and safety of biologic monotherapy in RA. The overall goal is to define the optimal biological monotherapy in RA patients who cannot tolerate MTX or where use of MTX is inappropriate, combining both direct and indirect evidence in a network meta-analysis of randomized trials.
A thorough and comprehensive literature search for RCTs, all looking at the biologic agents for RA, will be carried out with last search 1st September 2012. The following bibliographic databases will apply: MEDLINE via PubMed from 1950, EMBASE via OVID from 1980, CINAHL via EBSCO from 1981, Chemical Abstracts via Scifinder from 1907, and Web of Science from 1900, as well as The Cochrane Central Register of Controlled Trials (CENTRAL), to identify all trials relating Biologics to RA. Further searches will be undertaken for the American College of Rheumatology (ACR) and the ‘European League Against Rheumatism’ (EULAR) conferences in 2011 and 2012.
As the area of evidence-synthesis in “Biologics for RA” is not a novel research area, we will also manually apply a search strategy for cited articles from previous meta-analyses available from PubMed:
rheumatoid[title] AND (meta analysis[pt] OR (meta analyse[ti] OR meta analysed[ti] OR meta analyses[ti] OR meta analysesresearch[ti] OR meta analysing[ti] OR meta analysis[ti] OR meta analysisof[ti] OR meta analyst[ti] OR meta analysticians[ti] OR meta analysts[ti]) OR (metaanalyses[ti] OR metaanalysis[ti]) OR (meta regressed[tiab] OR meta regression[tiab] OR meta regression'by[tiab] OR meta regressional[tiab] OR meta regressions[tiab] OR meta regressive[tiab]) OR (metaregress[tiab] OR metaregression[tiab] OR metaregressions[tiab] OR metaregressive[tiab]) OR (multiple[All Fields] AND compar[All Fields]) OR (indirect[All Fields] AND compar[All Fields])) AND (("adalimumab"[Supplementary Concept] OR "adalimumab"[All Fields]) OR ("certolizumab pegol"[Supplementary Concept] OR "certolizumab pegol"[All Fields] OR "certolizumab"[All Fields]) OR ("TNFR-Fc fusion protein"[Supplementary Concept] OR "TNFR-Fc fusion protein"[All Fields] OR "etanercept"[All Fields] OR “etanercept"[Supplementary Concept]) OR ("golimumab"[Supplementary Concept] OR "golimumab"[All Fields]) OR ("infliximab"[Supplementary Concept] OR "infliximab"[All Fields]) OR ("interleukin 1 receptor antagonist protein"[MeSH Terms] OR "interleukin 1 receptor antagonist protein"[All Fields] OR "anakinra"[All Fields]) OR ("abatacept"[Supplementary Concept] OR "abatacept"[All Fields]) OR ("rituximab"[Supplementary Concept] OR "rituximab"[All Fields]) OR ("tocilizumab"[Supplementary Concept] OR "tocilizumab"[All Fields]))
This search will also be supported by the MEDLINE search strategy for systematic reviews as proposed by Montori et al; empirical search terms for high sensitivity (.98%) in retrieval of systematic reviews.
Types of study to be included
We will include randomized, controlled trials of patients with RA that include any of the nine biologics administered as monotherapy. Two reviewers (RC, ST) will independently evaluate reports for eligibility. Disagreements will be resolved by discussion (LEK & HB). No language restrictions apply.
Condition or domain being studied
Rheumatoid arthritis (RA) is a systemic disease that affects the synovial joints. RA is characterized by pain, swelling, and destruction of joints, with resultant disability. The inflammation in RA patients should be suppressed as early as possible; only disease-modifying antirheumatic drugs (DMARDs) can interfere with the disease process. Pharmacological therapy in RA patients includes both conventional DMARDs and new biological DMARDs. DMARDs are effective for both symptoms and signs of RA, although biological agents apparently offer greater suppression of progression of structural damage. Conventional DMARDs includes hydroxychloroquine, leflunomide, methotrexate (MTX), and sulfasalazine; these DMARDs are also used in various combinations. DMARD combination therapy includes 2 drugs, most of which are MTX based with only a few exceptions; these are given either with or without concomitant glucocorticoid therapy.
Eligible patients will have confirmed RA presumably according to the 1987 ACR-criteria.
A systematic review will be performed to identify randomized controlled trials (RCTs), which investigated the efficacy of a biologic agent administered as monotherapy in RA. The biologic agents of interest for this particular network meta-analysis include nine that are all approved for RA: adalimumab, certolizumab pegol, etanercept, golimumab, infliximab, anakinra, abatacept, rituximab, and tocilizumab.
A systematic review will be performed to identify randomized controlled trials (RCTs), which investigated the efficacy of a biologic agent administered as monotherapy in RA. Eligible patients will have confirmed RA presumably according to the 1987 ACR-criteria. The biologic agents of interest for this particular network meta-analysis include nine that are all approved for RA: adalimumab, certolizumab pegol, etanercept, golimumab, infliximab, anakinra, abatacept, rituximab, and tocilizumab.
The core-outcome data in each study consist of the sample size of the groups, the number of patients in each group who ‘had an event’. Two major outcomes will be considered our co-primary outcomes: Benefit (defined as a 50% improvement in the American College of Rheumatology symptomatic criteria [ACR50]) and Harm (determined by the number of withdrawals because of adverse events). ACR50 is a validated clinically meaningful binary measure of benefit. It is defined as a 50% improvement in swollen and tender joint counts plus a 50% improvement in 3 out of 5 clinically important criteria. For safety, we chose to include withdrawals that occurred because of adverse events, which is a measure of patients’ tolerance of adverse events and is reported consistently.
A priori it was decided to use the outcome assessment after on average 6 months varying according to the original protocols (i.e., 24-26 weeks) in each trial.
The secondary benefit outcomes will include the number of patients achieving an ACR20, and ACR70 response, respectively; whereas, the secondary outcomes for harm will be the number of patients who withdraw from the study, and the number of patients who have a serious adverse event (SAE). We anticipate these, together with the co-primary outcomes, will enable a simplistic version of the ‘Outcome Measures in Rheumatology [OMERACT] 3x3 table’ that comprises three ranks for both benefit and harm outcomes.
Outcome assessment after, on average, 6 months varying according to the original protocols (i.e., 24-26 weeks) in each trial.
Data extraction, (selection and coding)
Data collection process
The data extraction will be performed by one researcher (RC) and reviewed by another (ST); meaning, effectively, that the second reviewer will trace back every value/number/comment to the original full text report and validate the extracted data. A standard data-extraction form will be developed for data collection. The following information will be systematically extracted as characteristics of the studies for each of the k randomized trials, and handled in a customized Microsoft Excel spread-sheet: Demographic baseline variables, study duration, dosage, attrition, and report of the size of the original intention-to-treat population.
Participants and setting. The following study level characteristics will be collected from all the eligible trials: Rheumatoid Factor status (%), Number of females (%), Mean age (years), Median (or mean) number of years since RA diagnosis, Number of patients on glucocorticoids (%), the mean ‘Tender-’ and ‘Swollen-’ Joint Count (TJC and SJC, respectively), the mean patient global assessment (mm VAS).
Risk of bias (quality) assessment
Risk of bias in individual studies:
Empirical studies show that inadequate quality of trials may distort the results from meta-analyses. Therefore, influence of quality of included studies should be included in meta-analyses at least for the purpose of sensitivity analysis. Two of the reviewers (RC & ST) will independently assess: (i) randomization followed by concealment of treatment allocation, (ii) blinding, and (iii) adequacy of statistical analyses (i.e., proper intention-to-treat [ITT] analysis):
Randomization and concealment of allocation will be considered adequate if the investigators responsible for patient selection are unable, prior to allocation, to suspect which treatment was next.
Blinding will be considered adequate if participants and key study personnel ensured complete lack of knowledge of treatment allocation, and that it was unlikely that the blinding had been broken.
Statistical analyses will be considered adequate if all randomized patients were analyzed in the group to which they were randomly allocated, regardless of the treatment received (ITT principle). Modified ITT population/analysis will most likely be categorized as unclear.
The assessment of each entry will involve answering a question, with answer ‘A’ indicating low risk of bias (adequate reporting), ‘B’ indicating unclear (either lack of information or uncertainty concerning the potential for bias), and ‘C’ referring to an inadequate handling of the item (i.e., high risk of bias per se). Disagreements will be resolved by consensus (incl. LEK & HB).
Strategy for data synthesis
Synthesis of results
When 2 drugs are compared with a common standard, the difference in effect between these 2 drugs with respect to the common standard forms the basis of indirect comparisons. In rheumatology, most biologics will be used in conjunction with other baseline DMARDs and compared with MTX and the same (i.e., equally distributed concomitant) baseline therapy. Indirect treatment comparisons in meta-analysis can be analyzed by various methods according to the different networks applied, including the star, ladder, closed and partially closed-loop designs. We use the star design and include at least 1 mono-biologic group from each available trial.
We perform mixed-effects logistic regression using an arm-based, random-effects model within an empirical Bayes framework. The generalized linear mixed model (GLMM) incorporates a vector of random effects and a design matrix for the random effects. Allowance is made for differences in heterogeneity of effects between different drugs by specifying that the linear predictor varies at the level of study and the drug across study. The primary model will also include the following covariates (attempting to) adjust for important confounders: average age, percentage of females, and the median (or mean) disease duration.
We will present approximated inconsistency indices (I-squared) for each of the drugs compared with DMARD (ranging from 0% to 100%, higher values indicate more heterogeneity). Formally, however, we will evaluate heterogeneity for the direct and indirect network of comparisons using estimated covariance parameters (Tau-squared estimated from GLMM in SAS v. 9.2), which examines heterogeneity because of ‘Study’ and ‘Study?Drug’ interaction (smaller values indicate a better model fit per se).
Analysis of subgroups or subsets
The overall goal of this evidence synthesis project is to determine which of the biologic therapies are most likely to result in a significant disease reduction (>50%) from the patients’ and physicians’ perspective (ACR50), without causing harm that will make the patient want to discontinue therapy. We pre-specify that the following stratified analyses would add value to clinical decision making, thus, these will also be added to the statistical model:
• MTX-naive (or equivalent) RA patients vs. Active RA despite MTX therapy (Bio-Naïve) vs. Active RA previously received one or more biological therapies
•MTX-naïve & Active RA despite MTX therapy vs. Previous use of Biologic
•Anti-TNF Biologic vs. Non-TNF Biologic
Risk of bias across studies:
In order to empirically assess the Risk of Bias in our estimates, we will perform analyses stratified by the different Risk of Bias trial characteristics: concealment of allocation, blinding (i.e., double-dummy technique), adequacy of analyses in accordance with the intention-to-treat principal.
In RA patients with active disease, who are intolerant to MTX and need biological monotherapy, it is important that we provide the RA patients with the most optimal treatment strategy; optimal treatment strategy includes explicit considerations on benefit and harm in both relative and absolute terms. It is prudent that this informed decision making is based on empirical evidence rather than a “clinical gut feeling”, even if this subgroup of RA patients only represent a “minority” (i.e., 10-30% probably do not tolerate MTX).
Contact details for further information
The Parker Institute
Copenhagen University Hospital
Nordre Fasanvej 57
DK-2000 Copenhagen F
Organisational affiliation of the review
The Parker Institute, Dept. Rheumatology, Copenhagen University Hospital, Frederiksberg.
Dr Robin Christensen, Mr Simon Tarp, Dr Tove Lorenzen, Professor Daniel Furst, Dr Michael Hansen, Dr Jasvinder Singh, Professor Ernest Choy, Professor Maarten Boers, Professor Maria Suarez-Almazor, Dr Bo Ejbjerg, Professor Mikkel Østergaard, Professor Henning Bliddal,
Anticipated or actual start date
15 August 2012
Anticipated completion date
03 December 2012
This particular study, including both the protocol and subsequent manuscript, has been supported by a grant from Roche; the grant was provided as an unrestricted grant to Musculoskeletal Statistics Unit, The Parker Institute.
Conflicts of interest
Musculoskeletal Statistics Unit, The Parker Institute, has/are received/receiving consulting fees, honoraria, research or institutional support, educational grants, equipment, services or expenses from: Abbott, Amgen, Astellas Pharma, Axellus, Bristol-Myers Squibb, Cambridge Nutritional Foods, Centocor, Dansk Droge, DSM Nutritional Products, Expanscience, Genentech, Hyben Vital, Hypo-Safe, IPSEN, MSD, MundiPharma, NorPharma, NutriCare, Pharmavie, Pfizer, Roche, Sanofi-Aventis, UCB, Wyeth.
Scotland, Denmark, Netherlands, Sweden, United States of America
Formal screening of search results against eligibility criteria
Risk of bias (quality) assessment
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