A multi-arm multi-stage platform design that allows pre-planned addition of arms while still controlling the family-wise error

TL;DR

This paper introduces a multi-stage platform trial design that allows adding new treatment arms while controlling the family-wise error rate, optimizing sample size and power in adaptive clinical trials.

Contribution

It presents a novel multi-arm multi-stage design enabling pre-planned addition of arms with error control, including methods for sample size calculation and distribution analysis.

Findings

The proposed design controls family-wise error rate effectively.

It achieves smaller sample sizes compared to separate trials.

The method is demonstrated through a motivating clinical trial example.

Abstract

There is growing interest in platform trials that allow for adding of new treatment arms as the trial progresses as well as being able to stop treatments part way through the trial for either lack of benefit/futility or for superiority. In some situations, platform trials need to guarantee that error rates are controlled. This paper presents a multi-stage design that allows additional arms to be added in a platform trial in a pre-planned fashion, while still controlling the family wise error rate. A method is given to compute the sample size required to achieve a desired level of power and we show how the distribution of the sample size and the expected sample size can be found. A motivating trial is presented which focuses on two settings, with the first being a set number of stages per active treatment arm and the second being a set total number of stages, with treatments that are added later getting fewer stages. Through this example we show that the proposed method results in a smaller sample size while still controlling the errors compared to running multiple separate trials.