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How Much More Efficient Are Adaptive Platform Trials Than Multiple Stand-Alone Trials? A Comprehensive Simulation Study for Streamlining Drug Development During a Pandemic

Masanao Sasaki

Masanao Sasaki

Department of Clinical Biostatistics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan

These authors equally contributed to this work.

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Hiroyuki Sato

Hiroyuki Sato

Department of Clinical Biostatistics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan

These authors equally contributed to this work.

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Yukari Uemura

Yukari Uemura

Biostatistics Section, Department of Data Science, Center of Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan

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Ayako Mikami

Ayako Mikami

Center for Clinical Research, National Center for Child Health and Development, Tokyo, Japan

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Nao Ichihara

Nao Ichihara

Department of Healthcare Quality Assessment, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

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Shigeki Fujitani

Shigeki Fujitani

Department of Emergency and Critical Care Medicine, St. Marianna University School of Medicine, Kanagawa, Japan

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Masashi Kondo

Masashi Kondo

Center for Clinical Trial and Research Support, Fujita Health University School of Medicine, Aichi, Japan

Department of Respiratory Medicine, Fujita Health University School of Medicine, Aichi, Japan

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Yohei Doi

Yohei Doi

Departments of Microbiology and Infectious Diseases, Fujita Health University School of Medicine, Aichi, Japan

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Eriko Morino

Eriko Morino

Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan

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Daisuke Tokita

Daisuke Tokita

Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan

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Norio Ohmagari

Norio Ohmagari

Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan

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Wataru Sugiura

Wataru Sugiura

Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan

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Akihiro Hirakawa

Corresponding Author

Akihiro Hirakawa

Department of Clinical Biostatistics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan

Correspondence: Akihiro Hirakawa ([email protected])

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First published: 05 March 2024

Abstract

With the coronavirus disease 2019 (COVID-19) pandemic, there is growing interest in utilizing adaptive platform clinical trials (APTs), in which multiple drugs are compared with a single common control group, such as a placebo or standard-of-care group. APTs evaluate several drugs for one disease and accept additions or exclusions of drugs as the trials progress; however, little is known about the efficiency of APTs over multiple stand-alone trials. In this study, we simulated the total development period, total sample size, and statistical operating characteristics of APTs and multiple stand-alone trials in drug development settings for hospitalized patients with COVID-19. Simulation studies using selected scenarios reconfirmed several findings regarding the efficiency of APTs. The APTs without staggered addition of drugs showed a shorter total development period than stand-alone trials, but the difference rapidly diminished if patient's enrollment was accelerated during the trials owing to the spread of infection. APTs with staggered addition of drugs still have the possibility of reducing the total development period compared with multiple stand-alone trials in some cases. Our study demonstrated that APTs could improve efficiency relative to multiple stand-alone trials regarding the total development period and total sample size without undermining statistical validity; however, this improvement varies depending on the speed of patient enrollment, sample size, presence/absence of family-wise error rate adjustment, allocation ratio between drug and placebo groups, and interval of staggered addition of drugs. Given the complexity of planning and implementing APT, the decision to implement APT during a pandemic must be made carefully.

CONFLICT OF INTEREST

The authors declared no competing interests for this work.