The design and evaluation of hybrid controlled trials that leverage external data and randomization.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
02 10 2022
02 10 2022
Historique:
received:
31
08
2020
accepted:
07
09
2022
entrez:
2
10
2022
pubmed:
3
10
2022
medline:
5
10
2022
Statut:
epublish
Résumé
Patient-level data from completed clinical studies or electronic health records can be used in the design and analysis of clinical trials. However, these external data can bias the evaluation of the experimental treatment when the statistical design does not appropriately account for potential confounders. In this work, we introduce a hybrid clinical trial design that combines the use of external control datasets and randomization to experimental and control arms, with the aim of producing efficient inference on the experimental treatment effects. Our analysis of the hybrid trial design includes scenarios where the distributions of measured and unmeasured prognostic patient characteristics differ across studies. Using simulations and datasets from clinical studies in extensive-stage small cell lung cancer and glioblastoma, we illustrate the potential advantages of hybrid trial designs compared to externally controlled trials and randomized trial designs.
Identifiants
pubmed: 36184621
doi: 10.1038/s41467-022-33192-1
pii: 10.1038/s41467-022-33192-1
pmc: PMC9527257
doi:
Banques de données
ClinicalTrials.gov
['NCT00003299', 'NCT00119613', 'NCT00363415', 'NCT01439568', 'NCT00453154']
Types de publication
Journal Article
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
5783Subventions
Organisme : NLM NIH HHS
ID : R01 LM013352
Pays : United States
Informations de copyright
© 2022. The Author(s).
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