When, why and how are estimated effects transported between populations? A scoping review of studies applying transportability methods

Transportability methods can improve the external validity of estimated effects by accounting for effect heterogeneity due to differently distributed covariates between populations. This scoping review aims to provide an overview of when, why and how transportability methods have been applied. We systematically searched MEDLINE (Ovid), Embase, Web of Science, EconLit and Google Scholar for studies published between 2010 and December 18, 2024. Studies using transportability methods in a numerical application for at least partly non-overlapping source and target populations were included. We identified 3432 unique studies and included 64 studies applying transportability methods. Over two thirds of the included studies (44/64) introduced new methods. Less than one third of the included studies (20/64) were pure applications of transportability methods. Most applied studies (17/20) transported effect estimates from randomized controlled trials. Effects were transported to target populations with either complete (9/20) or no (9/20) treatment and outcome data or both (2/20). The most frequent aims of applied studies were to transport estimated effects to new populations (10/20) and to assess effect heterogeneity explainable by measured covariates (8/20). How transportability methods were applied varied widely between studies, for instance in the covariate selection approach and sensitivity analysis. Methodological studies with a transportability application presented new transportability estimators for randomized data (5/44), specific transportability applications (e.g., meta-analysis, mediation analysis; 21/44) and other methodological aspects (e.g., covariate selection, missing data handling; 18/44). Transportability methods are a useful tool for knowledge transfer between populations. More applications of transportability methods and guidance for their use are desirable.