A recent study investigated whether and how statistical techniques, referred to as 'transportability methods,' have been applied in published studies that use data collected during routine healthcare, commonly called real-world evidence (RWE) studies. The use of transportability methods for RWE generation is an emerging and promising area of research that addresses evidence gaps in settings with limited data and infrastructure.
This article explores the growing use of transportability methods to generate real-world evidence (RWE), particularly in settings where data and infrastructure are limited. Transportability methods allow researchers to apply findings from one population, such as those in clinical trials or well-studied groups, to another population by adjusting for differences in demographics, clinical factors, or other relevant characteristics. Through a targeted literature review, the authors identified six studies published between 2021 and 2023 that applied transportability methods to estimate the effectiveness or safety of biomedical interventions. These studies used data from the U.S. and Canada, primarily employing statistical weighting techniques to adjust effect estimates for their target populations.
The findings suggest that while transportability methods are still emerging, they hold promise for filling evidence gaps where randomized controlled trials (RCTs) may not be feasible. The authors highlight the importance of clear and thorough reporting of the assumptions and methods used in transportability analyses to enhance the validity and acceptability of results. They emphasize that these methods can be particularly valuable in jurisdictions with limited data or small patient populations, enabling healthcare decision-makers to better assess the safety and effectiveness of treatments in real-world settings. The article calls for the development of good practices to facilitate the broader adoption of transportability methods in regulatory and health technology assessment contexts.