Bayesian Design in Clinical Trials

• Andere auteurs: Berchialla, Paola (Redacteur), Baldi, Ileana (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Onderwerpen: 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 toegang: DOAB: download the publication; DOAB: description of the publication

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...