title: An evaluation of a bayesian method of dose escalation based on bivariate binary responses.
abstract: Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.
authors.affiliation: The University of Reading, UK. j.r.whitehead@reading.ac.uk
authors.forename: John
authors.initials: J
authors.lastname: Whitehead
authors.forename: Yinghui
authors.initials: Y
authors.lastname: Zhou
authors.forename: John
authors.initials: J
authors.lastname: Stevens
authors.forename: Graham
authors.initials: G
authors.lastname: Blakey
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions; D005069:Evaluation Studies as Topic; D006801:Humans; D004364:Pharmaceutical Preparations / Q000008:administration & dosage*; D011014:Pneumonia / Q000188:drug therapy; D015203:Reproducibility of Results; D012107:Research Design / Q000706:statistics & numerical data; D018401:Sample Size; D016896:Treatment Outcome
chemical_list: D004364:Pharmaceutical Preparations