CIESAL researcher gave a seminar on heterogeneity in systematic reviews at the USACH



Nicolás Meza, a researcher at CIESAL, presented, on Wednesday, August 16, the seminar entitled “Heterogeneity in the context of systematic reviews” at the School of Medicine of the USACH. The invitation to this event was extended by Dr Vivienne Bachelet, full professor at the USACH School of Medicine and editor-in-chief of Medwave.

The seminar attracted a diverse audience composed of professors, residents, assistants and students of the career. During the session, Nicolás Meza, in addition to referring to the statistical assumptions underlying the analysis of heterogeneity, joined the discussion on the progress of the research (in which he is also a co-author) entitled “A methodological overview of systematic reviews and meta-analyses on the diagnostic accuracy of SARS-CoV-2 rapid antigen tests”; whose preliminary results were presented by assistants and professors of this school of studies, who are also part of the group of authors. This project focuses on developing a protocol to evaluate the diagnostic accuracy of rapid antigen tests for SARS-CoV-2.

The seminar provided a space for discussion and debate, in which participants could explore the complexities —and scope— of the topic addressed.

Within the context of systematic reviews of clinical trials and observational studies, both intervention and diagnostic accuracy, heterogeneity plays a central role. Heterogeneity refers to the variability in the observed results among the studies included in a systematic review. This variability may arise due to differences in study design, populations studied, interventions or measurement techniques used.

In systematic reviews of clinical trials, heterogeneity may manifest itself when the results of individual studies differ significantly in terms of the effects of an intervention. This may be due to variations in patient population, intervention dosing, duration of follow-up, and other factors that influence treatment response.

For systematic reviews of observational studies, such as those evaluating the diagnostic accuracy of medical tests, heterogeneity can arise due to the diversity of methods used to administer the tests, patient population characteristics, and underlying clinical conditions. Variability in sensitivity, specificity, and other diagnostic accuracy parameters between studies can complicate the synthesis of results and the formulation of robust conclusions.

Proper management of heterogeneity in systematic reviews is essential to ensure validity and accurate interpretation of results. Statistical methods, such as subgroup analysis and meta-regression, can be used to explore and quantify heterogeneity. Identifying sources of variability and understanding how they may influence outcomes is critical to making informed decisions and providing sound, evidence-based clinical recommendations.