A straightforward meta-analysis approach for oncology phase I dose-finding studies.
Bayesian statistics
dose-escalation trial
random-effects meta-analysis
shrinkage estimation
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
10 09 2022
10 09 2022
Historique:
revised:
12
05
2022
received:
12
10
2021
accepted:
16
05
2022
pubmed:
7
6
2022
medline:
1
9
2022
entrez:
6
6
2022
Statut:
ppublish
Résumé
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.
Types de publication
Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3915-3940Informations de copyright
© 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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