TY - JOUR
T1 - Effect Estimates in Randomized Trials and Observational Studies
T2 - Comparing Apples with Apples
AU - Lodi, Sara
AU - Phillips, Andrew
AU - Lundgren, Jens
AU - Logan, Roger
AU - Sharma, Shweta
AU - Cole, Stephen R.
AU - Babiker, Abdel
AU - Law, Matthew
AU - Chu, Haitao
AU - Byrne, Dana
AU - Horban, Andrzej
AU - Sterne, Jonathan A.C.
AU - Porter, Kholoud
AU - Sabin, Caroline
AU - Costagliola, Dominique
AU - Abgrall, Sophie
AU - Gill, John
AU - Touloumi, Giota
AU - Pacheco, Antonio G.
AU - Van Sighem, Ard
AU - Reiss, Peter
AU - Bucher, Heiner C.
AU - Montoliu Giménez, Alexandra
AU - Jarrin, Inmaculada
AU - Wittkop, Linda
AU - Meyer, Laurence
AU - Perez-Hoyos, Santiago
AU - Justice, Amy
AU - Neaton, James D.
AU - Hernán, Miguel A.
N1 - Publisher Copyright:
© 2019 The Author(s). Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - 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.
AB - 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.
KW - antiretroviral initiation
KW - causal inference
KW - per-protocol effect
KW - target trial
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U2 - 10.1093/aje/kwz100
DO - 10.1093/aje/kwz100
M3 - Article
C2 - 31063192
AN - SCOPUS:85072687046
SN - 0002-9262
VL - 188
SP - 1569
EP - 1577
JO - American journal of epidemiology
JF - American journal of epidemiology
IS - 8
ER -
