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Statistical considerations on implementing the MCP-Mod method for binary endpoints in clinical trials
The Multiple Comparison Procedure – Modelling (MCP-Mod) method was qaulified by regulatory agencies (e.g., EMA in 2014 and FDA in 2016) as an efficient statistical method for Phase 2 dose-finding studies when there is uncertainty about dose-response relationship. As this is a relatively new approach...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7451792/ https://www.ncbi.nlm.nih.gov/pubmed/32875139 http://dx.doi.org/10.1016/j.conctc.2020.100641 |
Sumario: | The Multiple Comparison Procedure – Modelling (MCP-Mod) method was qaulified by regulatory agencies (e.g., EMA in 2014 and FDA in 2016) as an efficient statistical method for Phase 2 dose-finding studies when there is uncertainty about dose-response relationship. As this is a relatively new approach, there is limited literature providing practical guidance on its application. In this paper, we evaluated the performance of the MCP-Mod method for clinical trials with a binary primary endpoint, focusing on (1) the impact of sample size, data variability and treatment effect size on the performance of the MCP-Mod, (2) the impact of candidate model mis-specification, and (3) optimal sample allocation under a fixed sample size. The evaluation was performed via simulations under different scenarios. |
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