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Article

Estimating Similarity of Dose–Response Relationships in Phase I Clinical Trials—Case Study in Bridging Data Package

1
INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, USPC, Université de Paris, F-75006 Paris, France
2
Department of Biomedical Statistics and Bioinformatics, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
3
F-CRIN PARTNERS Platform, Assistance Publique-Hôpitaux de Paris, Université de Paris, F-75010 Paris, France
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2021, 18(4), 1639; https://doi.org/10.3390/ijerph18041639
Received: 14 December 2020 / Revised: 3 February 2021 / Accepted: 5 February 2021 / Published: 9 February 2021
(This article belongs to the Special Issue Bayesian Design in Clinical Trials)
Bridging studies are designed to fill the gap between two populations in terms of clinical trial data, such as toxicity, efficacy, comorbidities and doses. According to ICH-E5 guidelines, clinical data can be extrapolated from one region to another if dose–reponse curves are similar between two populations. For instance, in Japan, Phase I clinical trials are often repeated due to this physiological/metabolic paradigm: the maximum tolerated dose (MTD) for Japanese patients is assumed to be lower than that for Caucasian patients, but not necessarily for all molecules. Therefore, proposing a statistical tool evaluating the similarity between two populations dose–response curves is of most interest. The aim of our work is to propose several indicators to evaluate the distance and the similarity of dose–toxicity curves and MTD distributions at the end of some of the Phase I trials, conducted on two populations or regions. For this purpose, we extended and adapted the commensurability criterion, initially proposed by Ollier et al. (2019), in the setting of completed phase I clinical trials. We evaluated their performance using three synthetic sets, built as examples, and six case studies found in the literature. Visualization plots and guidelines on the way to interpret the results are proposed. View Full-Text
Keywords: bridging studies; distribution distance; oncology; phase I; dose-finding; dose–response; bayesian inference bridging studies; distribution distance; oncology; phase I; dose-finding; dose–response; bayesian inference
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MDPI and ACS Style

Ollier, A.; Zohar, S.; Morita, S.; Ursino, M. Estimating Similarity of Dose–Response Relationships in Phase I Clinical Trials—Case Study in Bridging Data Package. Int. J. Environ. Res. Public Health 2021, 18, 1639. https://doi.org/10.3390/ijerph18041639

AMA Style

Ollier A, Zohar S, Morita S, Ursino M. Estimating Similarity of Dose–Response Relationships in Phase I Clinical Trials—Case Study in Bridging Data Package. International Journal of Environmental Research and Public Health. 2021; 18(4):1639. https://doi.org/10.3390/ijerph18041639

Chicago/Turabian Style

Ollier, Adrien, Sarah Zohar, Satoshi Morita, and Moreno Ursino. 2021. "Estimating Similarity of Dose–Response Relationships in Phase I Clinical Trials—Case Study in Bridging Data Package" International Journal of Environmental Research and Public Health 18, no. 4: 1639. https://doi.org/10.3390/ijerph18041639

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