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Benefits, challenges and obstacles of adaptive clinical trial designs

In recent years, the use of adaptive design methods in pharmaceutical/clinical research and development has become popular due to its flexibility and efficiency for identifying potential signals of clinical benefit of the test treatment under investigation. The flexibility and efficiency, however, i...

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Detalles Bibliográficos
Autores principales: Chow, Shein-Chung, Corey, Ralph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3248853/
https://www.ncbi.nlm.nih.gov/pubmed/22129361
http://dx.doi.org/10.1186/1750-1172-6-79
Descripción
Sumario:In recent years, the use of adaptive design methods in pharmaceutical/clinical research and development has become popular due to its flexibility and efficiency for identifying potential signals of clinical benefit of the test treatment under investigation. The flexibility and efficiency, however, increase the risk of operational biases with resulting decrease in the accuracy and reliability for assessing the treatment effect of the test treatment under investigation. In its recent draft guidance, the United States Food and Drug Administration (FDA) expresses regulatory concern of controlling the overall type I error rate at a pre-specified level of significance for a clinical trial utilizing adaptive design. The FDA classifies adaptive designs into categories of well-understood and less well-understood designs. For those less well-understood adaptive designs such as adaptive dose finding designs and two-stage phase I/II (or phase II/III) seamless adaptive designs, statistical methods are not well established and hence should be used with caution. In practice, misuse of adaptive design methods in clinical trials is a concern to both clinical scientists and regulatory agencies. It is suggested that the escalating momentum for the use of adaptive design methods in clinical trials be slowed in order to allow time for development of appropriate statistical methodologies.