An introduction to inverse probability of treatment weighting in observational research

Nicholas C. Chesnaye, Vianda S. Stel, Giovanni Tripepi, Friedo W. Dekker, Edouard L. Fu, Carmine Zoccali, Kitty J. Jager

Research output: Contribution to journalReview articleAcademicpeer-review

184 Citations (Scopus)

Abstract

In this article we introduce the concept of inverse probability of treatment weighting (IPTW) and describe how this method can be applied to adjust for measured confounding in observational research, illustrated by a clinical example from nephrology. IPTW involves two main steps. First, the probability - or propensity - of being exposed to the risk factor or intervention of interest is calculated, given an individual's characteristics (i.e. propensity score). Second, weights are calculated as the inverse of the propensity score. The application of these weights to the study population creates a pseudopopulation in which confounders are equally distributed across exposed and unexposed groups. We also elaborate on how weighting can be applied in longitudinal studies to deal with informative censoring and time-dependent confounding in the setting of treatment-confounder feedback.
Original languageEnglish
Pages (from-to)14-20
Number of pages7
JournalClinical Kidney Journal
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • Chronic renal insufficiency
  • Dialysis
  • Epidemiology
  • Guidelines
  • Systematic review

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