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. 2019 Apr 15;2019(4):CD013311. doi: 10.1002/14651858.CD013311

Baricitinib for rheumatoid arthritis

Natalia V Zamora 1, Jean H Tayar 2, Maria Angeles Lopez‐Olivo 2, Robin Christensen 3, Maria E Suarez‐Almazor 2,✉
PMCID: PMC6464708

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the benefits and harms of baricitinib for rheumatoid arthritis.

Background

Description of the condition

Rheumatoid arthritis is a chronic systemic inflammatory disease of unknown etiology, characterized by polyarticular and symmetrical joint involvement (Kelley 1989). It causes pain and swelling which, if not treated properly, can lead to bone erosions and joint deformities (Kvien 2005). Rheumatoid arthritis affects up to 1% of the general population and is more common in women aged 40 to 60 years old (Alamanos 2006; Silman 1998). Within the last decade the treatment of rheumatoid arthritis has changed drastically and currently there is a wide variety of disease‐modifying antirheumatic drugs which are available either orally, intravenously, or by subcutaneous injection. The objective of early and timely treatment is to reduce joint and systemic inflammation in order to improve quality of life, functionality, and inhibit disease progression (Emery 1995; Kavanaugh 2007; Klarenbeek 2009).

Description of the intervention

Conventional disease‐modifying antirheumatic drugs (administrated as monotherapy or in combination), such as methotrexate, have been the mainstay treatment for rheumatoid arthritis for decades and remain the first choice (Lopez‐Olivo 2014). However, these therapies are ineffective for up to one‐third of patients (Goekoop‐Ruiterman 2005; Moreland 2012; Saag 2008); the newer biologic disease‐modifying antirheumatic drugs developed in recent years have led to further advances toward better clinical response (Lethaby 2013; Lopez‐Olivo 2015; Maxwell 2010; Navarro‐Sarabia 2006; Singh 2010a; Singh 2010b). The Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have approved nine parenteral biologic disease‐modifying antirheumatic drugs, including five tumor necrosis factor alpha inhibitors, a cytotoxic T‐lymphocyte‐associated protein 4 inhibitor abatacept, an interleukin‐1 inhibitor anakinra, an interleukin‐6 inhibitor tocilizumab, and anti‐CD20 rituximab. Of these drugs, tumor necrosis factor alpha inhibitors are the most commonly used. Failure to these biologic disease modifying antirheumatic drugs has been also reported in up to 50% of all patients with 20% to 45% discontinuing treatment within one year (Hyrich 2011; Jobanputra 2012; Kievit 2007; Manders 2015). More recently, the FDA has approved a Janus kinase (JAK) inhibitor, tofacitinib, as the first oral small‐molecule drug for the treatment of patients with moderate and severe rheumatoid arthritis who have failed to respond to other treatments. (Bonilla‐Hernán 2011). On the other hand, EMA has recently approved the use of baricitinib, a newer reversible inhibitor of JAK 1 and 2 kinases, also orally administrated, for treating patients with moderately to severely active rheumatoid arthritis (Eli Lilly and Company 2017). The JAK kinase family plays an important role in the inflammatory response induced by cytokines (Fridman 2010; Tanaka 2013; Yazici 2011), and its inhibition results in the reduction of the production of pro‐inflammatory mediators and cytokines.

How the intervention might work

Baricitinib inhibits different cytokines implicated in rheumatoid arthritis pathogeneses; these include granulocyte‐macrophage colony‐stimulating factor, interleukin‐6, interleukin‐12, interleukin‐23 and interferon γ (O'Shea 2013). In preclinical rodent models of arthritis, baricitinib has shown significant anti‐inflammatory effects as well as preservation of cartilage and bone (Fridman 2010). Furthermore, in phase II and III studies, baricitinib has demonstrated to be effective in improving signs and symptoms compared with placebo, and with a relatively flat dose–response curve with all doses (4, 7, 8, or 10 mg administered once daily) (Dougados 2015; Fleischmann 2015; Genovese 2015; Greenwald 2010; Keystone 2015;Tanaka 2014). The manufacturer of baricitinib has recently received the approval for the drug by the EMA as a once‐daily therapy for moderately to severely active rheumatoid arthritis, in doses of 2 mg and 4 mg. Its efficacy has been reported when compared to a placebo group with significant American College of Rheumatology (ACR) 20, 50 and 70 responses at 12 and 24 weeks (Keystone 2015). Currently, the most frequently reported side effects associated with baricitinib are upper respiratory tract infections and dose‐dependent decreases in hemoglobin levels (Dougados 2015; Fleischmann 2015; Genovese 2015; Keystone 2015; Tanaka 2014).

Why it is important to do this review

To date, there are no comprehensive reviews comparing the evidence reported in the randomized controlled trials evaluating baricitinib. Therefore, we will undertake a systematic review of the evidence to evaluate benefits and harms associated with use of this novel drug for the management of rheumatoid arthritis. This review will be conducted according to the guidelines recommended by the Cochrane Musculoskeletal Group Editorial Board (Ghogomu 2014).

Objectives

To assess the benefits and harms of baricitinib for rheumatoid arthritis.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized controlled trials and controlled clinical trials comparing baricitinib alone, or in combination with any disease‐modifying antirheumatic drugs, versus placebo or other conventional or biologic disease‐modifying antirheumatic drugs. We will consider data from published and unpublished studies for inclusion. There will be no language restrictions.

Types of participants

We will include adults with a diagnosis of rheumatoid arthritis meeting the ACR 1987 criteria (Arnett 1988) or the ACR/European League Against Rheumatism (EULAR) 2010 criteria (Aletaha 2010), or both, for rheumatoid arthritis and active disease (as described by study authors).

Types of interventions

We will include trials comparing baricitinib at any dose, either alone or in combination with any disease‐modifying antirheumatic drugs, versus placebo or other conventional or biologic disease‐modifying antirheumatic drugs. For the purpose of defining a primary analysis, we will prioritize reporting baricitinib 4 mg (in clinical trials, the dosage of 2 mg demonstrated lower efficacy than 4 mg at 12 and 24 weeks, in terms of ACR categories for improvement [20, 50 and 70], low disease activity, and remission. When 4 mg was compared with 8 mg, the higher dose was associated with more adverse events and no additional efficacy (Keystone 2015)). Secondary analyses will include all other doses.

Types of outcome measures

Major outcomes

  1. Criteria for improvement in symptoms: measured using ACR response criteria for 50% improvement in symptoms (Felson 1995), which is defined as an improvement in response rates of 50% in tender and swollen joints, in addition to a 50% improvement observed in three out of five core measures such as patient and physical global assessments, pain, functional status and an acute phase reactant.

  2. Disease activity: measured by the Disease Activity Score in 28 joints (DAS28). In addition, we will consider remission rates as a useful measure of the disease activity, measured as a DAS less than 2.6 (Prevoo 1995) or ACR/EULAR 2011 definition of remission, either Boolean (total joint count (TJC) 1, swollen joint count (SJC) 1, C‐reactive protein (CRP) 1 mg/dL, patient global assessment 1), or index‐based (Simplified Disease Activity Index score of 3.3 or less) (Felson 2011).

  3. Radiographic progression: measured by radiographic scores to detect a change in the score from baseline, which include: i) modified total Sharp score (TSS) with score range 0 to 448; ii) erosion scores (ES); and iii) joint space narrowing score (JSNS). Scores for ES and JSNS are summed to yield the TSS (van der Heijde 1999).

  4. Function: measured by the Health Assessment Questionnaire (HAQ) (Fries 1980), Arthritis Impact Measurement Scale (AIMS) (Meenan 1980), or other scales reported by study authors.

  5. Health‐related quality of life (HRQOL): measured by the Medical Outcomes Study Short‐Form Health Survey (SF‐36), or any other scales reported by authors (Fries 1980).

  6. Withdrawals due to adverse events.

  7. Serious adverse events (as defined by the authors).

Minor outcomes

  1. ACR20, which is defined as an improvement in response rates of 20% in tender and swollen joints, in addition to a 20% improvement observed in three out of five in core measures like patient and physical global assessments, pain, functional status and an acute phase reactant.

  2. ACR70, which is defined as an improvement in response rates of 70% in tender and swollen joints, in addition to a 70% improvement observed in three out of five in core measures like patient and physical global assessments, pain, functional status and an acute phase reactant.

  3. Number of tender joints per patient.

  4. Number of swollen joints per patient.

  5. Pain (Visual Analogue Scale (VAS)).

  6. Physician global assessment (VAS).

  7. Patient global assessment (VAS).

  8. Acute phase reactants: including erythrocyte sedimentation rate (ESR) (this is a measurement of how fast red blood cells (erthrocytes) fall to the bottom of a test tube filled with whole blood; those with rheumatoid arthritis have high levels of sedimentation).

  9. Fatigue: including Functional Assessment of Chronic Illness Therapy‐Fatigue (FACIT‐F) questionnaire, or others.

  10. Total withdrawals and due to lack of efficacy.

  11. Total adverse events.

  12. Common adverse events (allergic reactions, headache, nausea).

  13. Expected adverse events (alterations in the cholesterol levels, decrease in hemoglobin, increase in creatinine, elevations of transaminase levels, decrease in neutrophils).

  14. Infections (including herpes zoster (shingles)).

  15. Deaths.

We will follow Cochrane guidelines to develop a 'Summary of findings' table (Schünemann 2017). We will include the seven major outcomes for presentation in the final table. We have selected the most relevant outcomes for patients and physicians, in accordance with those recommended by Cochrane Musculoskeletal and the current recommendations from Outcome Measures in Rheumatology (OMERACT).

The list of major outcomes has been selected following the updated guideline for Cochrane Musculoskeletal (Ghogomu 2014).

Search methods for identification of studies

Electronic searches

We will search for published data in the following electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and Web of Science (Dickersin 1994). The specific search strategy will be constructed according to Cochrane Musculoskeletal methods used in reviews. We will also conduct a search of ClinicalTrials.gov (clinicaltrials.gov/) and the WHO trials portal (who.int/ictrp/en/). We will search all databases from their inception to the present, and we will impose no restrictions 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 attempt to contact the authors of included studies and the baricitinib manufacturers (Eli Lilly and Incyte) for any additional information that has not been published, or when trial data are unclear, or further details are needed.

We will search for errata or retractions from included studies published in full‐text on PubMed (ncbi.nlm.nih.gov/pubmed) and report the date this was done within the review. We will also handsearch the list of references of potentially relevant citations which were not published or otherwise found.

Data collection and analysis

Selection of studies

Two review authors will screen all of the unique citations obtained by the electronic search strategy and other sources (NZ, JT). We will resolve any disagreement through discussion and consensus. If no consensus is reached, a third party will act as an adjudicator (MES‐A). 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. Covidence (covidence.org) will be used to manage the records retrieved from searches of electronic databases.

Data extraction and management

The data will be extracted independently by two authors (NZ, JT) and will be cross‐checked for any errors; any discrepancies will be resolved by discussion (MAL‐O/RC). Data from each included trial will be extracted in Covidence, to capture the following information (when available).

  1. 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.

  2. Participants: number (N), mean age, age range, sex, disease duration, severity of condition, diagnostic criteria, important (condition‐specific) baseline data; inclusion criteria, and exclusion criteria. (When appropriate, we will extract equity factors such as socio‐economic status or place of residence, when reported. See equity.cochrane.org/equity‐extension‐prisma.)

  3. Interventions: intervention, comparison, concomitant medications, and excluded medications.

  4. Outcomes: primary and secondary outcomes specified and collected, and time points reported.

  5. Characteristics of the design of the trial, as outlined below in Assessment of risk of bias in included studies.

  6. Notes: funding for trial, and notable declarations of interest of trial authors.

We will extract 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.

We will note in the 'Characteristics of included studies' table if outcome data were not reported in a usable way, and when data were transformed or estimated from a graph. One review author (NZ) will transfer data into the Review Manager 5 file (RevMan 2014). We will double‐check that data are entered correctly by comparing the data presented in the systematic review with the study reports.

We will identify any a priori decision rules to select which data to extract in the event of multiple outcome reporting, including:

  1. if both final values and change‐from‐baseline values are reported for the same outcome, final values will be reported;

  2. if multiple time points are reported, we will extract data reported at 12 weeks, 24 weeks and 52 weeks.

Assessment of risk of bias in included studies

Two review authors (NZ, JT) will independently assess the risk of bias using Covidence, and will follow Cochrane's recommendations for assessment (Higgins 2011(b)). Disagreements among the authors will be discussed and resolved through consensus. If disagreement persists, a final decision will be facilitated by a third review author (MAL‐O). We will summarize the 'Risk of bias' assessment for every outcome included in the 'Summary of findings' table within a study. Studies will be appraised for selection bias, performance bias, detection bias, attrition bias, reporting bias, and other biases (i.e. baseline imbalance ). We will explore these biases by considering the following criteria.

  1. Random or quasi‐random sequence generation

  2. Allocation concealment

  3. Blinding of participants. 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).

  4. Blinding of personnel and outcome assessors

  5. Incomplete outcome data. 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.

  6. Selective reporting

  7. Other biases (Higgins 2011(b))

We will grade each potential source of bias as low, unclear, or high, and will provide a quote from the study report and justification for each judgement in the 'Risk of bias' table.

We will summarize the 'Risk of bias' judgements across different studies for each of the domains listed (except for blinding of participants and incomplete outcome data, as specified above). When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome. The final ratings for all included studies will be presented in a ‘Risk of bias’ summary figure.

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

For efficacy outcomes, we will analyze data as reported in the studies (either modified intention‐to‐treat (ITT), per protocol, or treatment received analysis). If data are analysed based on an ITT sample and another sample (e.g. per‐protocol, as‐treated), the ITT will be extracted (for both outcomes representing benefits and harms).

For dichotomous variables, we will determine the risk ratio (RR), and for rare events the Peto odds ratio (Peto OR) will be applied (events less than 10%). Continuous data will be measured by using mean difference or standardized mean difference (SMD) (if the same construct is measured on different scales). We will estimate 95% confidence intervals (CIs) for all measures of treatment effect. 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), according to Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2011b).

For safety outcomes, an ITT model will be used to analyze the data. We will report the RR and its 95% CI for the number of patients with adverse events and number of discontinuations.

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

For dichotomous outcomes (e.g. number of withdrawals due to adverse events), the withdrawal rate will be calculated using the number of participants randomised in the group as the denominator. For continuous data, we will use the mean and standard deviation (SD) when available. Missing SDs will be calculated from other statistics such as standard errors, confidence intervals or P value, according to the methods recommended in theCochrane Handbook for Systematic Reviews of Interventions (Higgins 2011(a)). If the SD is not provided for any follow‐up visit, we will use the baseline SD. If SDs cannot be calculated, they will be imputed (e.g. from other studies in the meta‐analysis).

In cases where only the median and interquartile ranges (or minimum and maximum values) are reported, the median will be used as the mean, and one half of the difference between the first and third quartile range will be used as the SD (Higgins 2011(a)).

We will use Engauge Digitizer software to extract data from graphs or figures (Mitchell 2019). These data will also be extracted in duplicate. Data provided in graphs only will also be extracted.

Assessment of heterogeneity

We will assess clinical and methodological diversity (in terms of participants, interventions, outcomes and study characteristics) for the included studies to determine whether a meta‐analysis is appropriate. We will assess statistical heterogeneity by visual inspection of the forest plots to assess for obvious differences in results between the studies, and we will use the inconsistency index (I2 statistic) to describe the percentage of the variability in effect estimates that is due to heterogeneity rather than chance. We will consider values ranging from 0% to 40% as not important; 30% to 60% as representing moderate heterogeneity; 50% to 90% as representing substantial heterogeneity; and 75% to 100% as considerable heterogeneity (Deeks 2011). As noted in the Cochrane 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. If substantial heterogeneity is present, we will conduct a number of stratified analyses, in which we stratify the available studies according to trial characteristics and continuous variables at study level (see below).

Assessment of reporting biases

We will explore publication bias using inverted funnel plots. In the absence of bias, the plot will resemble a symmetrical, inverted funnel; if there is bias, it will lead to an asymmetrical appearance of the funnel plot. The more pronounced the asymmetry, the more likely it is that the amount of bias will be substantial. When interpreting funnel plots, we will examine the different possible reasons for funnel plot asymmetry, as outlined in section 10.4 of the Cochrane 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). Even if insufficient trials are identified to interpret a funnel plot appropriately, we will appraise studies individually for reporting bias (i.e. publication, time‐lag, multiple publication, location, citation, language and selective reporting). To assess outcome reporting bias, we will check trial protocols against published reports. For studies published after 1 July 2005, we will screen ClinicalTrials.gov for the a priori trial protocol. We will evaluate whether selective reporting of outcomes is present.

Data synthesis

Treatment groups will be analyzed separately (for trials comparing more than two dosages of baricitinib). We will analyze outcomes reported at 12, 24 and 52 weeks; however, for the primary analyses of safety outcomes we will only use the longest follow‐up up until the blinding was broken. We will include the following comparison groups:

  1. baricitinib combined with methotrexate versus placebo combined with methotrexate (or methotrexate monotherapy);

  2. baricitinib monotherapy versus methotrexate monotherapy;

  3. baricitinib combined with methotrexate versus other biologics combined with methotrexate;

  4. baricitinib combined with methotrexate versus baricitinib monotherapy.

The results of the studies will be analyzed using Review Manager 5. We will summarize the data of clinically homogeneous studies in a meta‐analysis. We will use standard inverse variance or Mantel Haenszel random‐effects for meta‐analysis (DerSimonian 1986), whereas the fixed‐effect analysis will be applied for the purpose of sensitivity. 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.

Participants with different prior therapy history (i.e. those naive to disease‐modifying antirheumatic drugs; those with prior exposure to disease‐modifying antirheumatic drugs; and those with prior exposure to biologic disease‐modifying antirheumatic drugs) will be pooled for primary analysis, and differences in effects will be explored using subgroup analyses (see below).

We will only include trials with low risk of detection and selection bias in the primary analysis for self‐reported outcomes (e.g. outcomes such as pain, function, health‐related quality of life, participant global assessment of treatment success or well‐being). Thus, the results included in the 'Summary of findings' table, abstract, and plain language summary will be based on trials with low risk of detection and selection bias.

'Summary of findings' table

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

  1. Criteria for improvement in symptoms: measured using ACR response criteria for 50% improvement in symptoms (Felson 1995), which is defined as an improvement in response rates of 50% in tender and swollen joints, in addition to a 50% improvement observed in three out of five core measures such as patient and physical global assessments, pain, functional status and an acute phase reactant.

  2. Disease activity: measured by the Disease Activity Score in 28 joints (DAS28). In addition, we will consider remission rates as a useful measure of the disease activity, measured as a DAS less than 2.6 (Prevoo 1995).

  3. Function: measured by the Health Assessment Questionnaire (HAQ) (Fries 1980)

  4. Radiographic progression: measured by radiographic scores to detect a change in the score from baseline, which include: i) modified total Sharp score (TSS) with score range 0 to 448 (van der Heijde 1999).

  5. Health‐related quality of life (HRQOL): measured by the Medical Outcomes Study Short‐Form Health Survey (SF‐36) (Ware 1992).

  6. Withdrawals due to adverse events

  7. Serious adverse events (as defined by the authors).

The 'Summary of findings' table will be based on the comparison baricitinib 4 mg plus methotrexate versus placebo plus methotrexate. We will report results only before the rescue treatment was implemented in the control group.

Two people(NZ, JT) 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, Chapter 11 and Section 13.5 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011(a); Schünemann 2011a), and will use GRADEpro GDT software to create the table (GRADEpro GDT).

We will justify all decisions to downgrade or upgrade our assessments of the quality of studies using footnotes, and we will make comments to aid the reader's understanding of the review where necessary. In the 'Comments' column of the 'Summary of findings' table, we will provide the absolute per cent difference, the relative per cent change from baseline, the number needed to treat for an additional beneficial outcome (NNTB), and number needed to treat for an additional harmful outcome (NNTH) (the NNTB and NNTH will be provided only when the outcome shows a statistically significant difference).

For dichotomous outcomes, such as serious adverse events, the NNTB will be calculated from the control group event rate and the relative risk, using the Visual Rx NNT calculator (Cates 2008). The NNTB for continuous measures will be calculated using the Wells calculator (available from http://musculoskeletal.cochrane.org/). For dichotomous outcomes, the absolute risk difference will be calculated using the 'risk difference' statistic in Review Manager 5 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 per cent 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 subgroup analyses to determine the effects of:

  1. disease duration (less than two years versus two years or longer);

  2. previous disease‐modifying antirheumatic drugs treatment (those naive to disease‐modifying antirheumatic drugs versus those with prior exposure to disease‐modifying antirheumatic drugs versus those with prior exposure to biologic disease‐modifying antirheumatic drugs).

Subgroup analyses will be restricted to the ACR improvement criteria of 50%. We will use the formal test for subgroup interactions in Review Manager 5 (RevMan 2014) and will use caution in the interpretation of subgroup analyses, as advised in Section 9.6 of the Cochrane 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.

Sensitivity analysis

If sufficient trials are identified, we plan to carry out the following sensitivity analyses, comparing the results using all trials with high methodological quality.

  1. Studies classified as having a low risk of bias versus those identified as having a high risk of bias for the domains of allocation concealment and blinding, for the ACR improvement criteria of 50% (Higgins 2011(b)).

  2. Where missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results. Any assumptions and imputations to handle missing data will be clearly described and the effect of imputation will be explored.

Interpreting results and reaching conclusions

We will follow the guidelines in Chapter 12 of the Cochrane Handbook (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.

Acknowledgements

We would like to thank Gregory F Pratt, DDS, MS, at the Research Medical Library of The University of Texas MD Anderson Cancer Center, for providing comments on the 'Search methods for identification of studies' section. The Musculoskeletal Statistics Unit at the Parker Institute (RC) is supported by grants from the Oak Foundation.

Appendices

Appendix 1. MEDLINE search strategy

1. exp RHEUMATOID ARTHRITIS/

2. ((rheumatoid or reumatoid) and arthriti*).ti.

3. ((rheumatoid or reumatoid) adj5 arthriti*).mp.+

4. ra.ti.

5. (rheumatism* or rheumarthriti*).mp.

6. ((rheumatic or reumatic) and (arthriti* or polyarthriti*)).ti.

7. ((rheumatic or reumatic) adj5 (arthriti* or polyarthriti*)).mp.

8. (rheumatoid and nodul*).ti.

9. (rheumatoid adj5 nodul*).mp.

10. (rheumatoid and vasculit*).ti.

11. (rheumatoid adj5 vasculit*).mp.

12. ((Sjogren* or Sjoegren*) and (rheum* or reum*)).ti.

13. ((Sjogren* or Sjoegren*) adj10 (rheum* or reum*)).mp.

14. ((Caplan* or Felty* or Stills* or "Still's" or sicca) and (syndrome* or disease*)).ti.

15. ((Caplan* or Felty* or Stills* or "Still's" or sicca) adj5 (syndrome* or disease*)).mp.

16. or/1‐15

17. BARICITINIB/

18. (baricitinib* or LY3009104* or "LY 3009104*" or INCB028050* or "INCB 028050*" or "INCB 28050*").mp

19. or/17‐18

20. 16 and 19

Contributions of authors

Draft the protocol: NVZ, JT, MLO, MSA, RC

Develop a search strategy: GP

Search for trials (usually two people): NVZ, GP

Obtain copies of trials: GP, NVZ

Select which trials to include (two people, plus one arbiter): NVZ, JT, MLO, MSA

Extract data from trials (two people): NVZ, JT

Enter data into Review Manager 5: NVZ

Carry out the analysis: RC, NVZ

Interpret the analysis: NVZ, JT, RC, MLO, MSA

Draft the final review: NVZ, JT, MLO, MSA, RC

Update the review: NVZ, MLO, MSA

Sources of support

Internal sources

  • The University of Texas, MD Anderson Cancer Center, USA.

External sources

  • No sources of support supplied

Declarations of interest

Dr Suarez‐Almazor is the recipient of a K24 career award from the National Institute for Musculoskeletal and Skin Disorders, and a research grant from Pfizer Inc.

Dr Lopez‐Olivo is recipient of a career award from the Rheumatology Research Foundation and has received consulting fees from Complete HEOR Solutions outside the scope of the submitted work. Dr Lopez‐Olivo has no other relationships or activities that could appear to have influenced the submitted work.

Dr Christensen’s unit has received consulting fees, honoraria, research or institutional support, educational grants, equipment, services or expenses from the following companies: Abbott, Astellas Pharma, Axellus, Bristol‐Myers Squibb, Cambridge Nutritional Foods, Centocor, DSM Nutritional Products, HypoSafe, MSD, MundiPharma, NorPharma, Pharmavie, Pfizer, Roche, Sanofi‐Aventis, and Scandinavian Clinical Nutrition.

Dr Zamora and Dr. Tayar: none.

New

References

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