PRIME-IPD SERIES Part 1. The PRIME-IPD tool promoted verification and standardization of study datasets retrieved for IPD meta-analysis

Objectives: We describe a systematic approach to preparing data in the conduct of Individual Participant Data (IPD) analysis. Study design and setting: A guidance paper proposing methods for preparing individual participant data for meta-analysis from multiple study sources, developed by consultation of relevant guidance and experts in IPD. We present an example of how these steps were applied in checking data for our own IPD meta analysis (IPD-MA). Results: We propose five steps of Processing, Replication, Imputation, Merging, and Evaluation to prepare individual participant data for meta-analysis (PRIME-IPD). Using our own IPD-MA as an exemplar, we found that this approach identified missing variables and potential inconsistencies in the data, facilitated the standardization of indicators across studies, confirmed that the correct data were received from investigators, and resulted in a single, verified dataset for IPD-MA. Conclusion: The PRIME-IPD approach can assist researchers to systematically prepare, manage and conduct important quality checks on IPD from multiple studies for meta-analyses. Further testing of this framework in IPD-MA would be useful to refine these steps.