 Systematic reviews and meta-analyses are considered the most reliable form of research due to their ability to combine multiple studies into one large dataset. However, these analyses can produce false positive results if there are not enough studies included, leading to a phenomenon known as small study syndrome. Trial sequential analysis, TSA, is a statistical method used to determine whether a meta-analysis is likely to be accurate or not. It does so by calculating the probability of a given result being correct, taking into account the number of studies and participants involved. By using TSA, clinicians can monitor the progress of a meta-analysis and make decisions about whether further research is necessary or not. Understanding the principles and assumptions behind TSA will help clinicians interpret the results correctly and make informed decisions. This article was authored by Hyun-Kwon