ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2021
Generalizability and Transportability of the National Lung Screening Trial Data: Extending Trial Results to Different Populations.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Estimating the impact of stimulant use on initiation of buprenorphine and extended-release naltrexone in two clinical trials and real-world populations.Addiction science & clinical practice · 2023Trial
- Association of Intensive Blood Pressure Control and Living Arrangement on Cardiovascular Outcomes by Race: Post Hoc Analysis of SPRINT Randomized Clinical Trial.JAMA network open · 2022Trial
- Uptake of HIV Self-testing Among Adolescents and Young Adults in Nigeria: A Secondary Observational Analysis of a Stepped-Wedge, Cluster-Randomized Trial.AIDS and behavior · 2026Article
- Predictive Modeling of Heterogeneous Treatment Effects in RCTs: A Scoping Review.JAMA network open · 2025Article
- When, why and how are estimated effects transported between populations? A scoping review of studies applying transportability methods.European journal of epidemiology · 2025Article
- Potential clinical impact of predictive modeling of heterogeneous treatment effects: scoping review of the impact of the PATH Statement.medRxiv : the preprint server for health sciences · 2025Article
- Use of transportability methods for real-world evidence generation: a review of current applications.Journal of comparative effectiveness research · 2024Review
- Linking clinical trial participants to their U.S. real-world data through tokenization: A practical guide.Contemporary clinical trials communications · 2024Article
- A General Primer for Data Harmonization.Scientific data · 2024Article
- Comparing Lung Cancer Screening Strategies in a Nationally Representative US Population Using Transportability Methods for the National Lung Cancer Screening Trial.JAMA network open · 2024Article
- Transportability Analysis-A Tool for Extending Trial Results to a Representative Target Population.JAMA network open · 2024Article
- Machine-learning-based high-benefit approach versus conventional high-risk approach in blood pressure management.International journal of epidemiology · 2023Article
- AdaDiag: Adversarial Domain Adaptation of Diagnostic Prediction with Clinical Event Sequences.Journal of biomedical informatics · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundRandomized controlled trials (RCT) play a central role in evidence-based healthcare. However, the clinical and policy implications of implementing RCTs in clinical practice are difficult to predict as the studied population is often different from the target population where results are being applied. This study illustrates the concepts of generalizability and transportability, demonstrating their utility in interpreting results from the National Lung Screening Trial (NLST).
methodsUsing inverse-odds weighting, we demonstrate how generalizability and transportability techniques can be used to extrapolate treatment effect from (i) a subset of NLST to the entire NLST population and from (ii) the entire NLST to different target populations.
resultsOur generalizability analysis revealed that lung cancer mortality reduction by LDCT screening across the entire NLST [16% (95% confidence interval [CI]: 4-24)] could have been estimated using a smaller subset of NLST participants. Using transportability analysis, we showed that populations with a higher prevalence of females and current smokers had a greater reduction in lung cancer mortality with LDCT screening [e.g., 27% (95% CI, 11-37) for the population with 80% females and 80% current smokers] than those with lower prevalence of females and current smokers.
conclusionsThis article illustrates how generalizability and transportability methods extend estimation of RCTs' utility beyond trial participants, to external populations of interest, including those that more closely mirror real-world populations. IMPACT: Generalizability and transportability approaches can be used to quantify treatment effects for populations of interest, which may be used to design future trials or adjust lung cancer screening eligibility criteria.
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