Bayesian Design in Clinical Trials

Bayesian Design in Clinical Trials

In the last decade, the number of clinical trials using Bayesian methods has grown dramatically. Nowadays, regulatory authorities appear to be more receptive to Bayesian methods than ever. The Bayesian methodology is well suited to address the issues arising in the planning, analysis, and conduct of...

Full description

Saved in:
Bibliographic Details
Other Authors: Berchialla, Paola (Editor), Baldi, Ileana (Editor)
Format: Book Chapter
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Humanities
Social interaction
dose-escalation
combination study
modelling assumption
interaction
adaptive designs
adaptive randomization
Bayesian designs
clinical trials
predictive power
target allocation
Bayesian inference
highest posterior density intervals
normal approximation
predictive analysis
sample size determination
bayesian meta-analysis
clustering
binary data
priors
frequentist validation
Bayesian
rare disease
prior distribution
meta-analysis
sample size
bridging studies
distribution distance
oncology
phase I
dose-finding
dose-response
bayesian inference
prior elicitation
latent dirichlet allocation
clinical trial
power-prior
poor accrual
Bayesian trial
cisplatin
doxorubicin
oxaliplatin
dose escalation
PIPAC
peritoneal carcinomatosis
randomized controlled trial
causal inference
doubly robust estimation
propensity score
Bayesian monitoring
futility rules
interim analysis
posterior and predictive probabilities
stopping boundaries
Bayesian trial design
early phase dose finding
treatment combinations
optimal dose combination
Online Access:Get Fullteks
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the last decade, the number of clinical trials using Bayesian methods has grown dramatically. Nowadays, regulatory authorities appear to be more receptive to Bayesian methods than ever. The Bayesian methodology is well suited to address the issues arising in the planning, analysis, and conduct of clinical trials. Due to their flexibility, Bayesian design methods based on the accrued data of ongoing trials have been recommended by both the US Food and Drug Administration and the European Medicines Agency for dose-response trials in early clinical development. A distinctive feature of the Bayesian approach is its ability to deal with external information, such as historical data, findings from previous studies and expert opinions, through prior elicitation. In fact, it provides a framework for embedding and handling the variability of auxiliary information within the planning and analysis of the study. A growing body of literature examines the use of historical data to augment newly collected data, especially in clinical trials where patients are difficult to recruit, which is the case for rare diseases, for example. Many works explore how this can be done properly, since using historical data has been recognized as less controversial than eliciting prior information from experts' opinions. In this book, applications of Bayesian design in the planning and analysis of clinical trials are introduced, along with methodological contributions to specific topics of Bayesian statistics. Finally, two reviews regarding the state-of-the-art of the Bayesian approach in clinical field trials are presented.
Physical Description:1 electronic resource (190 p.)
ISBN:books978-3-0365-3333-9
9783036533339
Access:Open Access

Similar Items