Linked Life Data

15027501

Source:http://linkedlifedata.com/resource/pubmed/id/15027501

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2004-3-18
pubmed:abstractText
Quality of life (QOL) end points in pharmaceutical clinical trials are at a crossroads. On the one hand, much has been learned in recent years of how to efficiently and effectively measure patient QOL. On the other hand, investigators and regulatory agencies still struggle with exactly how to assess the results of QOL end points and other patient-reported outcomes. Statisticians are often left in the position of having to bridge the gap between investigators who want to assess patient QOL and regulatory bodies who want a sound scientific rationale and analysis plan for doing so. Unfortunately, little has been written specifically for the statistical audience to assist in this translation. The purpose of this paper is to attempt to bridge this gap. We will describe the language and methods that have been successful in translating the psychometric and statistical challenges into understandable findings for investigators and regulatory agencies. One of the most important advances is the development of a general guideline for assessing clinical significance, namely the "half standard deviation" method based on the empirical rule effect size (ERES) approach. We populate the paper with concrete examples of how QOL data need not be treated any different, in terms of statistical analysis, than tumor response or other clinical end points.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1054-3406
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
73-96
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Issues for statisticians in conducting analyses and translating results for quality of life end points in clinical trials.
pubmed:affiliation
Department of Health Sciences Research, Mayo Clinic Cancer Center, Rochester, Minnesota 55905, USA. jsloan@mayo.edu
pubmed:publicationType
Journal Article