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

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:33

Enthalten in:

Statistical methods in medical research - 33(2024), 2 vom: 21. Feb., Seite 203-226

Sprache:

Englisch

Beteiligte Personen:

Barnett, Helen [VerfasserIn]
George, Matthew [VerfasserIn]
Skanji, Donia [VerfasserIn]
Saint-Hilary, Gaelle [VerfasserIn]
Jaki, Thomas [VerfasserIn]
Mozgunov, Pavel [VerfasserIn]

Links:

Volltext

Themen:

Combination therapies
Dose-finding
Journal Article
Model-free designs
Phase I trials

Anmerkungen:

Date Completed 13.03.2024

Date Revised 22.03.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1177/09622802231220497

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM367543214