How to do do meta-analysis for clinical data?

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Ajit Singh

Since you are conducting a meta-analysis, it is important to ensure the systematic search and selection of clinical trials, and to assess the risk of bias of the included studies. Given that there are no control groups in the trials, you may consider using a single-group meta-analysis approach to estimate the response rate of daratumumab in relapsed and refractory multiple myeloma. Alternatively, you may conduct a network meta-analysis if there are studies comparing daratumumab with other treatments. As for the software, RevMan is a popular choice for conducting meta-analyses, particularly for Cochrane systematic reviews. However, it may not be suitable for single-group meta-analyses or network meta-analyses. Other free software that can be used for meta-analyses include Comprehensive Meta-Analysis, MetaEasy, and OpenMeta.

Ma'Mon Abu Hammad

Meta-analysis is a statistical method that combines results from multiple studies to generate a summary estimate of the effect size of a particular intervention or exposure. The steps to conducting a meta-analysis for clinical data include:

Define the research question and identify relevant studies: Determine the clinical question or problem that the meta-analysis will address, and identify studies that are relevant to the question. This can be done by conducting a comprehensive literature search using databases such as PubMed, Cochrane Library, and Embase.

Evaluate the quality of the studies: Assess the quality of the studies using established criteria, such as the Cochrane Risk of Bias Tool or the Newcastle-Ottawa Scale. This will help to determine which studies are of high enough quality to be included in the meta-analysis.

Extract data from the studies: Collect relevant data from each study, including information about the study design, sample size, intervention or exposure, outcome measures, and effect sizes.

Analyze the data: Use statistical software such as R or STATA to analyze the data. Depending on the type of data and research question, the analysis may involve calculating summary statistics, conducting regression analyses, or using other statistical methods.

Conduct a meta-analysis: Combine the results of the individual studies to generate an overall estimate of the effect size using statistical methods such as fixed-effect or random-effects models.

Interpret the results: Interpret the results of the meta-analysis and draw conclusions about the effectiveness of the intervention or exposure. Assess the level of heterogeneity between studies, and conduct sensitivity analyses to explore the robustness of the results.

Report the findings: Write up the results of the meta-analysis in a clear and concise manner, including details about the studies included, the methods used, and the results of the analysis. This should be done following established reporting guidelines such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

It's important to note that conducting a meta-analysis requires a solid understanding of statistical methods and research design, so it's recommended to seek the help of a statistician or experienced researcher to ensure the analysis is conducted appropriately.