Meta-Analysis in Surgical Research: Methodology and Statistical Application

Abstract

In evidence-based medicine, systematic review continues to carry the highest weight in terms of quality and reliability, synthesizing robust information from previously published cohort studies to provide a comprehensive overview of a topic. Meta-analysis provides further depth by allowing for comparative analysis between the studied intervention and the control group, providing the most up-to-date evidence on their characteristics and efficacy. We discuss the principles and methodology of meta-analysis, and its applicability to the field of surgical research. The clinical question is defined using PICO framework (Problem, Intervention, Comparison, Outcome). Then a systematic article search is performed across multiple medical databases using relevant search terms, which are then filtered out based on appropriate screening tools. Pertinent data from the selected articles are collected and undergo critical appraisal by at least two independent reviewers. Additional statistical tests may be performed to identify the presence of any significant bias. The data are then synthesized to perform comparative analysis between the intervention and comparison groups. In this article, we discuss specifically the usage of R software (R Foundation for Statistical Computing, Vienna, Austria) for data analysis and visualization. Meta-analysis results of the pooled data are presented using forest plots. Concerns for potential bias may be addressed through the creation of funnel plots. Meta-analysis is a powerful tool to provide highly reliable medical evidence. It may be readily performed by independent researchers with minimal need for funding or institutional approval. The ability to conduct such studies is an asset to budding medical scholars.