[5]. Research studies, especially the Randomized Controlled Trials (RCTs) for positive interventions and Cohort studies, where interventional studies are not possible, are the major study designs employed to collect information on the effect of interventions and exposures on health-related outcomes [6]. Yet, the effect estimates from multiple studies may vary in intensity, direction of the effect, sample sizes and methodological intricacies. Systematic reviews (SR) and meta-analysis (MA) were introduced to address these concerns, to review, collate, analyse, estimate the pooled effects, and interpret and critically analyse all the existing studies under specific topic of interest [7,8]. In the level of evidence, meta-analysis of well-conducted RCTs has been placed at Level IA, the highest level of evidence [5], for answering any clinical or public health questions. Meta-analysis can be done on observational analytical studies (case-control, cohort studies) as well as on cross-sectional prevalence studies. This review enumerates the applications of SR and MA, steps to be followed while undertaking SR and MA, and common methodological issues encountered during the meta-analysis, which will be helpful for beginners in the evidence synthesis. Also, the review elaborately discusses the concept of heterogeneity, its impact on the meta-analysis estimates, techniques to measure heterogeneity and the strategies to address heterogeneity.
Meta-analysis and its applications
Meta-analysis has been defined as "The statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings" [9]. Meta-analysis is the statistical extension of the systematic review [10]. By applying appropriate statistical methods, MA helps to estimate the pooled effect size from multiple studies answering the same research question. It improves the statistical power with increased precision of the effect estimates [11,12]. A single estimate will always be better in terms of decision-making in the clinical and public health domains. By pooling the data from multiple studies on the same research question, meta-analysis informs the researchers, clinicians and policymakers whether there was any significant effect of the exposure/interventions on the outcomes, and if so, what is the direction and strength of the effect [13]. Such pooling of the data can also be done while estimating the burden of the diseases in terms of prevalence, indicating the application of meta-analysis in descriptive studies. Thus, meta-analysis can assess the distribution and determinants of health states and diseases, which are the essential components of epidemiology. The outcomes of a meta-analysis may enhance the accuracy of impact estimates, address issues that were not addressed by the individual studies, resolve disputes resulting from seemingly incongruent studies, and provide new hypotheses [14]. Overall, meta-analysis, preceded by systematic review, is the most valuable tool under EBM and EBPH
Steps in meta-analysis
All SR and MAs should follow the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) or "Meta-analyses Of Observational Studies in Epidemiology" (MOOSE) guidelines for maintaining the objectivity and quality in the process [15,16]. The steps involved in conducting an SR and MA, including the tools to assist the process, are discussed in the subsequent section. [Figure 1]
Figure 1: Major steps in conducting the meta-analysis
Building a team:
Systematic review and meta-analysis require forming a group with a minimum of three researchers (reviewers), to enable independent data extraction and adjudication of the contradictions. The group should consist of expert(s) of the domain in which the research is being undertaken. For instance, SR and MA on the effect of a clinical intervention on neonatal mortality should include a neonatologist or a paediatrician. At-least one of the members should be well-versed with the stepwise process of the SR and MA and the statistical methods employed under various aspects of meta-analysis. These domain experts and methodological experts should have a consultative working through all SR and MA stages to achieve methodologically robust and policy-influencing outcomes.