Effect estimates in randomized trials and observational studies

American Journal of Epidemiology 2019: , ISBN 0002-9262 (Journal)

Lodi Sara, Phillips Andrew, Lundgren Jens, Logan Roger, Sharma Shweta, Cole Stephen R., Babiker Abdel, Law Matthew, Chu Haitao, Byrne Dana, Horban Andrzej, Sterne Jonathan, Porter Kholoud, Sabin Caroline A., Costagliola Dominique, Abgrall Sophie, Gill Michael, Touloumi Giota, Pacheco Antonio Guilherme, van Sighem Ard, Reiss Peter, Bucher Heiner C., Giménez Alexandra, Jarrin Inmaculada, Wittkop Linda, Meyer Laurence, Pérez-Hoyos Santiago, Justice Amy, Neaton James D., Hernán Miguel A.

Effect estimates from randomized trials and observational studies may not be directly comparable because of differences in study design, other than randomization, and in data analysis. We propose a three-step procedure to facilitate meaningful comparisons of effect estimates from randomized trials and observational studies: 1) harmonization of the study protocol (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 (ART) in HIV-positive individuals from the START randomized trial and the observational HIV-CAUSAL Collaboration.

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