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    Rights statement: This is the peer reviewed version of the following article: Cotterill A, Jaki T. Dose‐escalation strategies which use subgroup information. Pharmaceutical Statistics. 2018;17:414–436. https://doi.org/10.1002/pst.1860 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/pst.18606/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Dose-escalation strategies which utilise subgroup information

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>09/2018
<mark>Journal</mark>Pharmaceutical Statistics
Issue number5
Volume17
Number of pages13
Pages (from-to)414-436
Publication statusPublished
Early online date13/06/18
Original languageEnglish

Abstract

Dose‐escalation trials commonly assume a homogeneous trial population to identify a single recommended dose of the experimental treatment for use in future trials. Wrongly assuming a homogeneous population can lead to a diluted treatment effect. Equally, exclusion of a subgroup that could in fact benefit from the treatment can cause a beneficial treatment effect to be missed. Accounting for a potential subgroup effect (ie, difference in reaction to the treatment between subgroups) in dose‐escalation can increase the chance of finding the treatment to be efficacious in a larger patient population.

A standard Bayesian model‐based method of dose‐escalation is extended to account for a subgroup effect by including covariates for subgroup membership in the dose‐toxicity model. A stratified design performs well but uses available data inefficiently and makes no inferences concerning presence of a subgroup effect. A hypothesis test could potentially rectify this problem but the small sample sizes result in a low‐powered test. As an alternative, the use of spike and slab priors for variable selection is proposed. This method continually assesses the presence of a subgroup effect, enabling efficient use of the available trial data throughout escalation and in identifying the recommended dose(s). A simulation study, based on real trial data, was conducted and this design was found to be both promising and feasible.

Bibliographic note

This is the peer reviewed version of the following article: Cotterill A, Jaki T. Dose‐escalation strategies which use subgroup information. Pharmaceutical Statistics. 2018;17:414–436. https://doi.org/10.1002/pst.1860 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/pst.18606/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.