OBJECTIVES: Real-world evidence (RWE) can mitigate challenges surrounding clinical evidence generation, and is therefore growing popular in health technology assessments (HTAs). Building upon this is the novel process of meta-analysis (MA) of RWE. This study aims to characterize the current role of RWE and MA of RWE in decision-making by HTA and regulatory bodies.

METHODS: A targeted literature review of PubMed and Google Scholar explored methodologies used to generate and apply RWE and MA of RWE to HTA submissions between 2022-2023. Guidance documents from the Food & Drug Administration (FDA) and National Institute for Health and Care Excellence (NICE) websites were reviewed and summarized.

RESULTS: Screened search results included 25 studies of (MA of) RWE in HTA submissions and 6 guidance documents. Methodologies used in RWE studies included external comparators (ECs) for single-arm clinical trials (SATs), pragmatic trials, target trial emulations, inferential models, and machine learning. In a study of 433 HTA submissions with SATs between 2011-2019, 52% employed ECs. Submissions with RWD ECs had a higher approval rate (59%) compared to those with no EC data (43%). MA of RWE studies integrated evidence from multiple sources through confidence profile methods, naive data synthesis, cross design synthesis, and three-level hierarchical models. Guidance on RWE use varied, with FDA guidance focusing on the fit of RWE and the quality of evidence, and NICE focusing on the three tenets of planning, conduct, and reporting. However, neither provided guidance on the use of MA of RWE in HTA submissions.

CONCLUSIONS: HTA bodies provide little guidance regarding the use of MA of RWE. To facilitate the use of these evidence sources, HTA bodies must establish reporting/quality standards and standard frameworks for analyses. Future studies should evaluate the impact of the use of RWE and MA of RWE studies on recent regulatory submissions.