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A comparison of model-free phase I dose escalation designs for dual-agent combination therapies.

Published version
Peer-reviewed

Repository DOI


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Authors

George, Matthew 
Skanji, Donia 
Saint-Hilary, Gaelle 

Abstract

It is increasingly common for therapies in oncology to be given in combination. In some cases, patients can benefit from the interaction between two drugs, although often at the risk of higher toxicity. A large number of designs to conduct phase I trials in this setting are available, where the objective is to select the maximum tolerated dose combination. Recently, a number of model-free (also called model-assisted) designs have provoked interest, providing several practical advantages over the more conventional approaches of rule-based or model-based designs. In this paper, we demonstrate a novel calibration procedure for model-free designs to determine their most desirable parameters. Under the calibration procedure, we compare the behaviour of model-free designs to model-based designs in a comprehensive simulation study, covering a number of clinically plausible scenarios. It is found that model-free designs are competitive with the model-based designs in terms of the proportion of correct selections of the maximum tolerated dose combination. However, there are a number of scenarios in which model-free designs offer a safer alternative. This is also illustrated in the application of the designs to a case study using data from a phase I oncology trial.

Description

Peer reviewed: True

Keywords

Dose-finding, combination therapies, model-free designs, phase I trials, Humans, Bayes Theorem, Computer Simulation, Dose-Response Relationship, Drug, Medical Oncology, Neoplasms, Research Design, Clinical Trials, Phase I as Topic

Journal Title

Stat Methods Med Res

Conference Name

Journal ISSN

0962-2802
1477-0334

Volume Title

33

Publisher

SAGE Publications
Sponsorship
NIHR Academy (SRF-2015-08-001)
Medical Research Council (MC_UU_00002/14)
National Institute for Health and Care Research (IS-BRC-1215-20014)