Confirmatory efficacy testing for individual dose-placebo comparisons using serial gatekeeping procedure in dose-finding trials with multiple comparison procedures-modeling

Pharm Stat. 2022 Nov;21(6):1309-1323. doi: 10.1002/pst.2246. Epub 2022 Jun 16.

Abstract

Dose-finding trials play a key role in the entire drug development process to determine optimal doses for regulatory approval. We address confirmatory efficacy testing for individual dose-placebo comparisons in the context of a dose-finding trial designed with multiple comparison procedures-modeling (MCP-Mod). An extension of the MCP-Mod, called closed MCP-Mod, has been proposed to carry out the MCP-Mod in conjunction with pairwise dose-placebo comparisons; however, an issue associated with the misspecification of candidate dose-response models remains. We consider another way to combine the MCP-Mod and the individual dose-placebo comparisons using serial gatekeeping procedures with fixed sequence, Holm, Hochberg, and step-down Dunnett procedure. The method controls the family-wise error rate in the strong sense and is simple enough to be implemented by existing software. Simulation studies suggested that the serial gatekeeping procedure was comparable with the closed MCP-Mod in terms of statistical power to detect the efficacy of at least one dose, and both methods were capable of pursuing the efficacy claim rather than just establishing the dose-response signal with less than a 20% increase in sample size when assuming monotonic dose-response shapes. The serial gatekeeping procedure would have advantages in the simplicity of implementation and ease of interpretation. The dose-finding trials aiming to declare the dose-response signal, as well as the efficacy of individual doses, would be worth considering as an option to accelerate the drug development program in certain situations.

Keywords: MCP-Mod; confirmatory efficacy testing; dose-finding trial; dose-response model; serial gatekeeping procedure.

MeSH terms

  • Computer Simulation
  • Dose-Response Relationship, Drug
  • Humans
  • Models, Statistical*
  • Research Design*
  • Sample Size