Year: 2022
Type: review
Abstract: Phase I early-phase clinical studies aim at investigating the safety and the underlying dose-toxicity relationship of a drug or combination. While little may still be known about the compound's properties, it is crucial to consider quantitative information available from any studies that may have been conducted previously on the same drug. A meta-analytic approach has the advantages of being able to properly account for between-study heterogeneity, and it may be readily extended to prediction or shrinkage applications. Here we propose a simple and robust two-stage approach for the estimation of maximum tolerated dose(s) utilizing penalized logistic regression and Bayesian random-effects meta-analysis methodology. Implementation is facilitated using standard R packages. The properties of the proposed methods are investigated in Monte Carlo simulations. The investigations are motivated and illustrated by two examples from oncology.
Source: Statistics in Medicine
DOI: 10.1002/sim.9484
Institutions: Universitätsmedizin Göttingen, Institut national de recherche en sciences et technologies du numérique, Inserm, Université Paris Cité, Sorbonne Université, Centre de Recherche des Cordeliers, Assistance Publique – Hôpitaux de Paris, Hôpital Robert-Debré, Centre d'Investigation Clinique Robert Debré, Heka : Méthodes basées sur les données et modèles en santé pour l'acquisition de connaissances
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,800
OpenAlex ID: W4281971612