This protocol specifies the conduct and reporting of a systematic review and meta-analysis in compliance with the guideline Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). The protocol has been registered in the PROSPERO database and assigned an identifier CRD42013005034.
Bibliographical databases for literature search include PubMed, Cochrane Library, Embase, Google Scholar, and ClinicalTrials (http://www.clinicaltrials.gov). Our search strategy will include main keywords ‘dapagliflozin’ and ‘diabetes’ (Appendix). Google search will be conducted to find other RCT information that is not available from bibliographical databases. Manual search will be conducted to track relevant RCTs that are not obviously indexed by normal keywords. Study selection will be documented and summarized in a PRISMA-compliant flowchart (Additional file 1: Figure S1).
The retrieved studies will be selected according to the checklist in Additional file 2 and the eligibility criteria listed below:
Only RCTs will be included. Observational, cohort, case–control, case series, and laboratory studies will be excluded.
Follow up periods
As long enough follow-up time is required for observing changes in HbA1c levels, this meta-analysis will include only the RCTs with follow-up periods >8 weeks.
This meta-analysis will include only the RCTs on adult T2D patients (aged ≥18 years).
This meta-analysis will include only the RCTs on the efficacy of dapagliflozin combined with conventional anti-diabetic drugs. The RCTs on dapagliflozin monotherapy will be excluded.
This meta-analysis will include the RCTs employing placebo combined with conventional anti-diabetic drugs as the controls. The RCTs employing only placebo as the control group will be excluded.
This meta-analysis will include the RCTs measuring HbA1c, FPG, and body weight as the outcomes. The RCTs without all these three outcomes will be excluded.
At least two reviewers will use the same eligibility evaluation form to evaluate the studies according to the eligibility criteria. Disagreement of their evaluation will be resolved by discussion.
Data from each included RCT will be extracted by one reviewer and verified by another. In addition to the outcome measures, the following characteristics of the verified RCTs will be extracted: (1) authors (and publication year), (2) interventions (doses of dapagliflozin and the drug used in combination), (3) characteristics of participants, (4) follow-up periods, and (5) conclusion. The extracted data will be tabulated (Additional file 3: Table S1) for further analysis.
We will assess the design, execution, and reporting of the included RCTs according to the Cochrane risk of bias tool (Additional file 4: Table S2) . The quality of each RCT will be assessed by one reviewer and verified by another. The quality of evidence will be determined with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system . The analysis will be conducted with GRADE profiler 3.2.
Data synthesis and analysis
All statistical analysis will be performed with R 3.0.1 software (http://www.r-project.org/). Meta-analysis based on the random-effects model will be conducted with ‘metaphor’ package . Continuous data such as the changes of HbA1c (%), FPG (mmol/L), and body weight (kg) will be presented as adjusted mean differences with 95% confidence intervals. A subgroup analysis will be conducted according to different drug combinations. The effects of follow-up periods and drug dosages will be assessed by meta-regression.
Publication bias will be evaluated with a funnel plot (that is, a plot of the effect sizes against their standard errors) and Egger’s regression test. Heterogeneity will be assessed with the I2 statistic, which is the proportion of total variance observed between the RCTs attributable to differences between RCTs rather than to sampling errors.
Sensitivity analysis will be performed to evaluate the robustness of the meta-analysis results. We will exclude the RCTs with some extreme features, for example, long follow-up periods (>24 weeks) or high risks of bias (if any), for sensitivity analyses. We would claim the meta-analysis to be robust or reliable if the sensitivity analysis does not significantly change the final results.