Brand versus generic: addressing non-adherence, secular trends and non-overlap

Lamar Hunt, Irene B. Murimi, Jodi B. Segal, Marissa J. Seamans, Daniel O. Scharfstein, Ravi Varadhan

Research output: Contribution to journalArticlepeer-review

Abstract

Whereas generic drugs offer a cost-effective alternative to brand name drugs, regulators need a method to assess therapeutic equivalence in a post-market setting. We develop such a method in the context of assessing the therapeutic equivalence of immediate release venlafaxine, based on a large insurance claims data set provided by OptumLabs\circledR. To address this question properly, our methodology must deal with issues of non-adherence, secular trends in health outcomes and lack of treatment overlap due to sharp uptake of the generic drug once it becomes available. We define, identify (under assumptions) and estimate (using G-computation) a causal effect for a time-to-event outcome by extending regression discontinuity to survival curves. We do not find evidence for a lack of therapeutic equivalence of brand and generic immediate release venlafaxine.

Original languageEnglish (US)
Pages (from-to)1461-1478
Number of pages18
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume183
Issue number4
DOIs
StatePublished - Oct 1 2020

Keywords

  • G-computation
  • Generic drugs
  • Regression discontinuity
  • Temporal confounding
  • Therapeutic equivalence
  • Time-varying confounding
  • Venlafaxine

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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