Bayesian dose‐regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Biometrics Année : 2022

Bayesian dose‐regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics

Résumé

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose (MTD) of a drug under a specific schedule. Evaluating drug-schedules aims at improving treatment safety while maintaining eÿcacy. However, while we can reasonably assume that toxicity increases with the dose for cytotoxic drugs, the relationship between toxicity and multiple schedules remains elusive. We proposed a Bayesian dose-regimen assessment method (DRtox) using pharma-cokinetics/pharmacodynamics (PK/PD) information to estimate the maximum tolerated dose-regimen (MTD-regimen), at the end of the dose-escalation stage of a trial to be recommended for the next phase. We modeled the binary toxicity via a PD endpoint and estimated the dose-regimen toxicity relationship through the integration of a dose-regimen PD model and a PD toxicity model. For the dose-regimen PD model, we considered nonlinear mixed-e˙ects models, and for the PD toxicity model, we proposed the following two Bayesian approaches: a logistic model and a hierarchical model. We evaluated the operating characteristics of the DRtox through simulation studies under various scenarios. The results showed that our method outperforms traditional model-based designs demonstrating a higher percentage of correctly selecting the MTD-regimen. Moreover, the inclusion of PK/PD information in the DRtox helped provide more precise estimates for the entire dose-regimen toxicity curve; therefore the DRtox may recommend alternative untested regimens for expansion cohorts. The DRtox should be applied at the end of the dose-escalation stage of an ongoing trial for pa-tients with relapsed or refractory acute myeloid leukemia (NCT03594955) once all toxicity and PK/PD data are collected.
Fichier principal
Vignette du fichier
2011.11480 (773.93 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03141298 , version 1 (11-12-2023)

Identifiants

Citer

Emma Gerard, Sarah Zohar, Hoai‐thu Thai, Christelle Lorenzato, Marie‐karelle Riviere, et al.. Bayesian dose‐regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics. Biometrics, 2022, ⟨10.1111/biom.13433⟩. ⟨hal-03141298⟩
54 Consultations
7 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More