ArticleAmerican journal of epidemiology2023
Transporting a Prediction Model for Use in a New Target Population.
Article in American journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 31 citations in OpenAlex.
- Scoping review of methodology for aiding generalisability and transportability of clinical prediction models.Diagnostic and prognostic research · 2026Review
- External validation of a US claims-based frailty indicator and development of a population-specific model for the German healthcare system.GeroScience · 2026Article
- Improving accuracy in the estimation of probable dementia in racially and ethnically diverse groups with penalized regression and transfer learning.American journal of epidemiology · 2026Article
- Counterfactual prediction from machine learning models: transportability and joint analysis for model development and evaluation using multi-source data.Diagnostic and prognostic research · 2025Article
- Estimating and Evaluating Counterfactual Prediction Models.Statistics in medicine · 2025Article
- Correcting for case-mix shift when developing clinical prediction models.BMC medical research methodology · 2025Article
- Efficient risk-based collection of biospecimens in cohort studies: designing a prospective study of diagnostic performance for multicancer detection tests.American journal of epidemiology · 2025Article
- Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Structured Data Analysis.Health data science · 2025Review
- Robust Estimation of Loss-Based Measures of Model Performance under Covariate Shift.The Canadian journal of statistics = Revue canadienne de statistique · 2024Article
- Sensitivity analysis for studies transporting prediction models.Biometrics · 2024Article
- Learning about treatment effects in a new target population under transportability assumptions for relative effect measures.European journal of epidemiology · 2024Article
- Invited Commentary: Combining Information to Answer Epidemiologic Questions About a Target Population.American journal of epidemiology · 2024Article
- Semisupervised transfer learning for evaluation of model classification performance.Biometrics · 2024Article
- Estimating the area under the ROC curve when transporting a prediction model to a target population.Biometrics · 2023Article
- Assessing the transportability of clinical prediction models for cognitive impairment using causal models.BMC medical research methodology · 2023Article
- Role of calibration in uncertainty-based referral for deep learning.Statistical methods in medical research · 2023Review
- Transfer learning of individualized treatment rules from experimental to real-world data.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2023Article
- Uncertainty in lung cancer stage for survival estimation via set-valued classification.Statistics in medicine · 2022Article
- Predicting counterfactual risks under hypothetical treatment strategies: an application to HIV.European journal of epidemiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
We considered methods for transporting a prediction model for use in a new target population, both when outcome and covariate data for model development are available from a source population that has a different covariate distribution compared with the target population and when covariate data (but not outcome data) are available from the target population. We discuss how to tailor the prediction model to account for differences in the data distribution between the source population and the target population. We also discuss how to assess the model's performance (e.g., by estimating the mean squared prediction error) in the target population. We provide identifiability results for measures of model performance in the target population for a potentially misspecified prediction model under a sampling design where the source and the target population samples are obtained separately. We introduce the concept of prediction error modifiers that can be used to reason about tailoring measures of model performance to the target population. We illustrate the methods in simulated data and apply them to transport a prediction model for lung cancer diagnosis from the National Lung Screening Trial to the nationally representative target population of trial-eligible individuals in the National Health and Nutrition Examination Survey.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.