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Bayesian leveraging of historical control data for a clinical trial with time-to-event endpoint.
Roychoudhury, Satrajit; Neuenschwander, Beat.
Afiliación
  • Roychoudhury S; Pfizer Inc, New York, New York.
  • Neuenschwander B; Novartis Pharma AG, Basel, Switzerland.
Stat Med ; 39(7): 984-995, 2020 03 30.
Article en En | MEDLINE | ID: mdl-31985077
ABSTRACT
The recent 21st Century Cures Act propagates innovations to accelerate the discovery, development, and delivery of 21st century cures. It includes the broader application of Bayesian statistics and the use of evidence from clinical expertise. An example of the latter is the use of trial-external (or historical) data, which promises more efficient or ethical trial designs. We propose a Bayesian meta-analytic approach to leverage historical data for time-to-event endpoints, which are common in oncology and cardiovascular diseases. The approach is based on a robust hierarchical model for piecewise exponential data. It allows for various degrees of between trial-heterogeneity and for leveraging individual as well as aggregate data. An ovarian carcinoma trial and a non-small cell cancer trial illustrate methodological and practical aspects of leveraging historical data for the analysis and design of time-to-event trials.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Revista: Stat Med Año: 2020 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Revista: Stat Med Año: 2020 Tipo del documento: Article