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An Optimal Two-Period Multiarm Platform Design with New Experimental Arms Added During the Trial
Haitao Pan   Xiaomeng Yuan 1   Jingjing Ye  

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https://doi.org/10.51387/22-NEJSDS15
Pub. online: 1 December 2022      Type: Cancer Research      Open accessOpen Access

1 The first two authors contributed equally.

Accepted
10 November 2022
Published
1 December 2022

Abstract

Platform trials are multiarm clinical studies that allow the addition of new experimental arms after the activation of the trial. Statistical issues concerning “adding new arms”, however, have not been thoroughly discussed. This work was motivated by a “two-period” pediatric osteosarcoma study, starting with two experimental arms and one control arm and later adding two more pre-planned experimental arms. The common control arm will be shared among experimental arms across the trial. In this paper, we provide a principled approach, including how to modify the critical boundaries to control the family-wise error rate as new arms are added, how to re-estimate the sample sizes and provide the optimal control-to-experimental arms allocation ratio, in terms of minimizing the total sample size to achieve a desirable marginal power level. We examined the influence of the timing of adding new arms on the design’s operating characteristics, which provides a practical guide for deciding the timing. Other various numerical evaluations have also been conducted. A method for controlling the pair-wise error rate (PWER) has also been developed. We have published an R package, PlatformDesign, on CRAN for practitioners to easily implement this platform trial approach. A detailed step-by-step tutorial is provided in Appendix A.2.

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© 2022 New England Statistical Society
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Keywords
Platform trial Adding new arms Family-wise error rate Multiarm trial

Funding
This research was supported by the NCI Comprehensive Cancer Center grant (P30 CA021765) and the American Lebanese Syrian Associated Charities (ALSAC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors have declared no conflict of interest. Data sharing is not applicable to this article, as no new data were created or analyzed in this study.

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