| Literature DB >> 31063192 |
Sara Lodi1, Andrew Phillips2, Jens Lundgren3, Roger Logan4, Shweta Sharma5, Stephen R Cole, Abdel Babiker6, Matthew Law7, Haitao Chu5, Dana Byrne8, Andrzej Horban9, Jonathan A C Sterne10,11, Kholoud Porter2, Caroline Sabin2, Dominique Costagliola12, Sophie Abgrall12,13, John Gill14,15, Giota Touloumi16, Antonio G Pacheco17, Ard van Sighem18, Peter Reiss18,19,20, Heiner C Bucher21, Alexandra Montoliu Giménez22, Inmaculada Jarrin23, Linda Wittkop24, Laurence Meyer25,26, Santiago Perez-Hoyos27, Amy Justice28, James D Neaton5, Miguel A Hernán4,29,30.
Abstract
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.Entities:
Keywords: antiretroviral initiation; causal inference; per-protocol effect; target trial
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Year: 2019 PMID： 31063192 PMCID： PMC6670045 DOI： 10.1093/aje/kwz100
Source DB: PubMed Journal: Am J Epidemiol ISSN： 0002-9262 Impact factor: 5.363