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Use of Sensitivity Analyses to Assess Uncontrolled Confounding from Unmeasured Variables in Observational, Active Comparator Pharmacoepidemiologic Studies: A Systematic Review.

Chase D LatourMegan DelgadoI-Hsuan SuCatherine WienerClement O AcheampongCharles PooleJessie K EdwardsKenneth QuintoTil StürmerJennifer L LundJie LiNahleen LopezJohn ConcatoMichele Jonsson Funk
Published in: American journal of epidemiology (2024)
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.
Keyphrases
  • healthcare
  • randomized controlled trial
  • meta analyses
  • risk assessment