Use of Sensitivity Analyses to Assess Uncontrolled Confounding from Unmeasured Variables in Observational, Active Comparator Pharmacoepidemiologic Studies: A Systematic Review.
Journal
American journal of epidemiology
ISSN: 1476-6256
Titre abrégé: Am J Epidemiol
Pays: United States
ID NLM: 7910653
Informations de publication
Date de publication:
03 Aug 2024
03 Aug 2024
Historique:
received:
08
09
2023
revised:
14
05
2024
medline:
5
8
2024
pubmed:
5
8
2024
entrez:
4
8
2024
Statut:
aheadofprint
Résumé
Understanding the potential for, direction, and magnitude of uncontrolled confounding is critical for generating informative real-world evidence. Many sensitivity analyses are available to assess robustness of study results to residual confounding, but it is unclear how researchers are using these methods. We conducted a systematic review of published active comparator cohort studies of drugs or biologics to summarize use of sensitivity analyses aimed at assessing uncontrolled confounding from an unmeasured variable. We reviewed articles in five medical and seven epidemiologic journals published between January 1, 2017, and June 30, 2022. We identified 158 active comparator cohort studies, 76 from medical and 82 from epidemiologic journals. Residual, unmeasured, or uncontrolled confounding was noted as a potential concern in 93% of studies, but only 84 (53%) implemented one or more sensitivity analysis to assess uncontrolled confounding from an unmeasured variable. The most common analyses were E-values among medical journal articles (21%) and restriction on measured variables among epidemiologic journal articles (22%). Researchers must rigorously consider the role of residual confounding in their analyses and the best sensitivity analyses for assessing this potential bias.
Identifiants
pubmed: 39098826
pii: 7726838
doi: 10.1093/aje/kwae234
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.