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Interim monitoring in sequential multiple assignment randomized trials.
Wu, Liwen; Wang, Junyao; Wahed, Abdus S.
Afiliación
  • Wu L; Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Wang J; Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Wahed AS; Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Biometrics ; 79(1): 368-380, 2023 03.
Article en En | MEDLINE | ID: mdl-34571583
A sequential multiple assignment randomized trial (SMART) facilitates the comparison of multiple adaptive treatment strategies (ATSs) simultaneously. Previous studies have established a framework to test the homogeneity of multiple ATSs by a global Wald test through inverse probability weighting. SMARTs are generally lengthier than classical clinical trials due to the sequential nature of treatment randomization in multiple stages. Thus, it would be beneficial to add interim analyses allowing for an early stop if overwhelming efficacy is observed. We introduce group sequential methods to SMARTs to facilitate interim monitoring based on the multivariate chi-square distribution. Simulation studies demonstrate that the proposed interim monitoring in SMART (IM-SMART) maintains the desired type I error and power with reduced expected sample size compared to the classical SMART. Finally, we illustrate our method by reanalyzing a SMART assessing the effects of cognitive behavioral and physical therapies in patients with knee osteoarthritis and comorbid subsyndromal depressive symptoms.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proyectos de Investigación Tipo de estudio: Clinical_trials Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proyectos de Investigación Tipo de estudio: Clinical_trials Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article