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Analysis of randomised trials with long-term follow-up.
Herbert, Robert D; Kasza, Jessica; Bø, Kari.
Afiliación
  • Herbert RD; Neuroscience Research Australia (NeuRA), Sydney, Australia. r.herbert@neura.edu.au.
  • Kasza J; The University of New South Wales, Sydney, Australia. r.herbert@neura.edu.au.
  • Bø K; Monash University, Melbourne, Australia.
BMC Med Res Methodol ; 18(1): 48, 2018 05 29.
Article en En | MEDLINE | ID: mdl-29843614
Randomised trials with long-term follow-up can provide estimates of the long-term effects of health interventions. However, analysis of long-term outcomes in randomised trials may be complicated by problems with the administration of treatment such as non-adherence, treatment switching and co-intervention, and problems obtaining outcome measurements arising from loss to follow-up and death of participants. Methods for dealing with these issues that involve conditioning on post-randomisation variables are unsatisfactory because they may involve the comparison of non-exchangeable groups and generate estimates that do not have a valid causal interpretation. We describe approaches to analysis that potentially provide estimates of causal effects when such issues arise. Brief descriptions are provided of the use of instrumental variable and propensity score methods in trials with imperfect adherence, marginal structural models and g-estimation in trials with treatment switching, mixed longitudinal models and multiple imputation in trials with loss to follow-up, and a sensitivity analysis that can be used when trial follow-up is truncated by death or other events. Clinical trialists might consider these methods both at the design and analysis stages of randomised trials with long-term follow-up.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ensayos Clínicos Controlados Aleatorios como Asunto / Evaluación de Resultado en la Atención de Salud Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2018 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ensayos Clínicos Controlados Aleatorios como Asunto / Evaluación de Resultado en la Atención de Salud Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2018 Tipo del documento: Article País de afiliación: Australia