ArticleBiometrics2019
Double robust estimation for multiple unordered treatments and clustered observations: Evaluating drug-eluting coronary artery stents.
Article in Biometrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
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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.
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Who cites it
8 citing papers in PubMed.
- A comparison of causal inference methods for evaluating multiple treatment groups.Journal of nonparametric statistics · 2025Article
- Targeted learning in observational studies with multi-valued treatments: An evaluation of antipsychotic drug treatment safety.Statistics in medicine · 2024Article
- Article
- CIMTx: An R Package for Causal Inference with Multiple Treatments using Observational Data.The R journal · 2022Article
- Matching on poset-based average rank for multiple treatments to compare many unbalanced groups.Statistics in medicine · 2021Article
- Revisiting performance metrics for prediction with rare outcomes.Statistical methods in medical research · 2021Article
- Intersections of machine learning and epidemiological methods for health services research.International journal of epidemiology · 2021Article
- Estimation of causal effects of multiple treatments in observational studies with a binary outcome.Statistical methods in medical research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Postmarket comparative effectiveness and safety analyses of therapeutic treatments typically involve large observational cohorts. We propose double robust machine learning estimation techniques for implantable medical device evaluations where there are more than two unordered treatments and patients are clustered in hospitals. This flexible approach also accommodates high-dimensional covariates drawn from clinical databases. The Massachusetts Data Analysis Center percutaneous coronary intervention cohort is used to assess the composite outcome of 10 drug-eluting stents among adults implanted with at least one drug-eluting stent in Massachusetts. We find remarkable discrimination between stents. A simulation study designed to mimic this coronary intervention cohort is also presented and produced similar results.
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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.