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Br J Clin Pharmacol ; 86(7): 1235-1239, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-31883123

RESUMO

There is a key problem in randomised clinical trials as outcomes can be distorted due to informative post-randomisation events. This is inadequately addressed by the use of traditional intention-to-treat or per protocol analysis sets and often either ignored or wrongly labelled as missing data. As a consequence, the treatment effects of interest in a clinical trial are not well defined and their estimates might be misinterpreted. The estimand framework should help all those planning, conducting and analysing clinical trials as well as those interpreting the results to better define, estimate and understand the treatment effects of interest. This framework is described in the addendum to ICH E9 and addresses precisely this problem. It is relevant for regulatory drug trials and academic-run trials, as well as for trials of nonpharmacological interventions.


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Projetos de Pesquisa , Interpretação Estatística de Dados , Humanos , Ensaios Clínicos Controlados Aleatórios como Assunto
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