Trial sequential analysis involving same-year studies requires careful temporal ordering

Xing Xing; Yipeng Wang; Lifeng Lin

doi:10.1016/j.jclinepi.2024.111645

Trial sequential analysis involving same-year studies requires careful temporal ordering

J Clin Epidemiol. 2024 Dec 18:111645. doi: 10.1016/j.jclinepi.2024.111645. Online ahead of print.

Authors

Xing Xing¹, Yipeng Wang², Lifeng Lin³

Affiliations

¹ Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
² Department of Biostatistics, University of Florida, Gainesville, FL, USA.
³ Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA. Electronic address: lifenglin@arizona.edu.

PMID: 39706537
DOI: 10.1016/j.jclinepi.2024.111645

Abstract

Trial sequential analysis (TSA) is an increasingly used tool in systematic reviews to monitor synthesized evidence. However, the current practice of TSAs often overlooks the order of same-year studies, which are typically ordered alphabetically based on the last names of the studies' authors by default in the widely used TSA software application. This practice is inappropriate and contrary to the TSA's definition. This issue is particularly concerning in systematic reviews on time-sensitive topics, such as COVID-19, where reviews include many studies within a short period. In this article, we use a case study to illustrate the impact of the order of same-year studies on TSA conclusions. It shows dramatically different patterns of evidence accumulation when same-year studies are ordered alphabetically vs. in their actual temporal order. This article offers suggestions for authors to pay attention to study ordering in future TSAs.

Keywords: COVID-19; cumulative meta-analysis; evidence-based medicine; meta-analysis; trial sequential analysis.