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Effect estimates in randomized trials and observational studies: comparing apples with apples

Research output: Contribution to journalJournal articleResearchpeer-review

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  • Sara Lodi
  • Andrew Phillips
  • Jens Lundgren
  • Roger Logan
  • Shweta Sharma
  • Stephen R Cole
  • Abdel Babiker
  • Matthew Law
  • Haitao Chu
  • Dana Byrne
  • Andrzej Horban
  • Jonathan A C Sterne
  • Kholoud Porter
  • Caroline Sabin
  • Dominique Costagliola
  • Sophie Abgrall
  • John Gill
  • Giota Touloumi
  • Antonio G Pacheco
  • Ard van Sighem
  • Peter Reiss
  • Heiner C Bucher
  • Alexandra Montoliu Giménez
  • Inmaculada Jarrin
  • Linda Wittkop
  • Laurence Meyer
  • Santiago Perez-Hoyos
  • Amy Justice
  • James D Neaton
  • Miguel A Hernán
  • INSIGHT START Study Group and the HIV-CAUSAL Collaboration
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Effect estimates from randomized trials and observational studies might not be directly comparable because of differences in study design, other than randomization, and in data analysis. We propose a 3-step procedure to facilitate meaningful comparisons of effect estimates from randomized trials and observational studies: 1) harmonization of the study protocols (eligibility criteria, treatment strategies, outcome, start and end of follow-up, causal contrast) so that the studies target the same causal effect, 2) harmonization of the data analysis to estimate the causal effect, and 3) sensitivity analyses to investigate the impact of discrepancies that could not be accounted for in the harmonization process. To illustrate our approach, we compared estimates of the effect of immediate with deferred initiation of antiretroviral therapy in individuals positive for the human immunodeficiency virus from the Strategic Timing of Antiretroviral Therapy (START) randomized trial and the observational HIV-CAUSAL Collaboration.

Original languageEnglish
JournalAmerican Journal of Epidemiology
Volume188
Issue number8
Pages (from-to)1569-1577
Number of pages9
ISSN0002-9262
DOIs
Publication statusPublished - 2019

ID: 57115856