An IPD (Individual Participant Data) meta-analysis requires collecting original individual patient data and calculating an estimated effect based on these data. The use of individual patient data has various advantages: the original data and the results of published analyses are verified, comparability between studies in terms of definitions, coding and analyses is increased, the number of options for performing sub-group analyses becomes greater, and it becomes possible to conduct more complex statistical analyses, such as the pooling of time-dependent data and multivariate regression analyses. In an IPD meta-analysis, additional information can be used which was not mentioned in the original article, for example, data from long-term follow-up. Improvements to this methodology are still possible; for example, to find the right balance between sufficient power to detect clinically relevant subgroup effects and minimizing the risk of false-positive findings. Readers can evaluate an IPD meta-analysis on various factors, including the reason for the choice for an IPD meta-analysis, the method used to identify and select the studies, and the number of approached authors that made their data available.