Transportability Analyses in Action: A Landscape Assessment of Application Studies Using Real Data

Author(s)

Vuong Q1, Metcalfe R2, Yan R1, Park J1
1Core Clinical Sciences, Vancouver, BC, Canada, 2Core Clinical Sciences, Calgary, AB, Canada

OBJECTIVES: Transportability analysis can facilitate health technology assessment (HTA) decision making by transporting the findings from randomized clinical trials (RCTs) or observational studies to a distinct target population. Recently there have been rapid developments in transportability analysis methods, but adoption of these methods is still in the early stages. We conducted a landscape review of applications of transportability analysis to gain an overview of how transportability analysis is being used in practice.

METHODS: We systematically searched PubMed for articles about transportability analysis. We then screened the abstracts and full texts of the returned articles to only include those that applied at least one transportability analysis method on real datasets collected from human populations. We extracted data from the screened articles on the clinical context, the characteristics of the source and target datasets, and the characteristics of the statistical analysis.

RESULTS: The PubMed search returned 1439 abstracts, from which we retained 90 for full text screening. We ultimately included 52 articles, three of which were identified through hand-searches. Among these articles, 81 separate transportability analyses were performed on 62 source/target dataset pairs. Among source datasets, 42 (67.7%) were from US populations, and 51 (82.3%) were from RCTs, with 8 (12.9%) from observational studies. Among target datasets, 40 (64.5%) were from US populations, and 41 (66.1%) were from observational studies, with 18 (29.0%) from RCTs. Most analyses were conducted using individual patient data (IPD) in both the study and target datasets. Weighting (43 analyses, 53.1%), g-computation (13 analyses, 16.0%), and augmented approaches (15 analyses, 18.5%) were most frequently used to conduct transportability analysis.

CONCLUSIONS: Applications of transportability analysis have not substantially expanded beyond US populations. More analyses which transport findings to non-US populations will be helpful in establishing the role of transportability analysis in global health.

Conference/Value in Health Info

2024-11, ISPOR Europe 2024, Barcelona, Spain

Value in Health, Volume 27, Issue 12, S2 (December 2024)

Acceptance Code

P34

Topic

Methodological & Statistical Research, Study Approaches

Topic Subcategory

Clinical Trials, Confounding, Selection Bias Correction, Causal Inference, Meta-Analysis & Indirect Comparisons, Prospective Observational Studies

Disease

no-additional-disease-conditions-specialized-treatment-areas

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