LODI, S.; PHILLIPS, A.; LUNDGREN, J.; LOGAN, R.; SHARMA, S.; COLE, S. R.; BABIKER, A.; LAW, M.; CHU, H.; BYRNE, D.; HORBAN, A.; STERNE, J. A. C.; PORTER, K.; SABIN, C.; COSTAGLIOLA, D.; ABGRALL, S.; GILL, J.; TOULOUMI, G.; PACHECO, A. G.; VAN SIGHEM, A.; REISS, P.; BUCHER, H. C.; MONTOLIU GIMENEZ, A.; JARRIN, I.; WITTKOP, Linda; MEYER, L.; PEREZ-HOYOS, S.; JUSTICE, A.; NEATON, J. D.; HERNAN, M. A.

doi:10.1093/aje/kwz100

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American journal of epidemiology. 2019-08-01, vol. 188, n° 8, p. 1569-1577

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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 in individuals positive to the human immunodeficiency virus from the START randomized trial and the observational HIV-CAUSAL Collaboration.< Leer menos

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MORPH3Eus

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

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