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Open AccessArticle

Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study

1
Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, UK
2
MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(1), 345; https://doi.org/10.3390/ijerph18010345
Received: 9 November 2020 / Revised: 14 December 2020 / Accepted: 31 December 2020 / Published: 5 January 2021
(This article belongs to the Special Issue Bayesian Design in Clinical Trials)
There is growing interest in Phase I dose-finding studies studying several doses of more than one agent simultaneously. A number of combination dose-finding designs were recently proposed to guide escalation/de-escalation decisions during the trials. The majority of these proposals are model-based: a parametric combination-toxicity relationship is fitted as data accumulates. Various parameter shapes were considered but the unifying theme for many of these is that typically between 4 and 6 parameters are to be estimated. While more parameters allow for more flexible modelling of the combination-toxicity relationship, this is a challenging estimation problem given the typically small sample size in Phase I trials of between 20 and 60 patients. These concerns gave raise to an ongoing debate whether including more parameters into combination-toxicity model leads to more accurate combination selection. In this work, we extensively study two variants of a 4-parameter logistic model with reduced number of parameters to investigate the effect of modelling assumptions. A framework to calibrate the prior distributions for a given parametric model is proposed to allow for fair comparisons. Via a comprehensive simulation study, we have found that the inclusion of the interaction parameter between two compounds does not provide any benefit in terms of the accuracy of selection, on average, but is found to result in fewer patients allocated to the target combination during the trial. View Full-Text
Keywords: dose-escalation; combination study; modelling assumption; interaction dose-escalation; combination study; modelling assumption; interaction
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MDPI and ACS Style

Mozgunov, P.; Knight, R.; Barnett, H.; Jaki, T. Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study. Int. J. Environ. Res. Public Health 2021, 18, 345. https://doi.org/10.3390/ijerph18010345

AMA Style

Mozgunov P, Knight R, Barnett H, Jaki T. Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study. International Journal of Environmental Research and Public Health. 2021; 18(1):345. https://doi.org/10.3390/ijerph18010345

Chicago/Turabian Style

Mozgunov, Pavel; Knight, Rochelle; Barnett, Helen; Jaki, Thomas. 2021. "Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study" Int. J. Environ. Res. Public Health 18, no. 1: 345. https://doi.org/10.3390/ijerph18010345

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