Linked Life Data

15587975

Source:http://linkedlifedata.com/resource/pubmed/id/15587975

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2004-12-13
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1054-3406
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
969-83
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
An evaluation of a bayesian method of dose escalation based on bivariate binary responses.
pubmed:affiliation
The University of Reading, UK. j.r.whitehead@reading.ac.uk
pubmed:publicationType
Journal Article