Linked Life Data

17530444

Source:http://linkedlifedata.com/resource/pubmed/id/17530444

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2007-8-31
pubmed:abstractText
To make optimal use of data from randomized trials in clinical decision-making, clinicians require knowledge of the magnitude of treatment effects. Reports of trials including quality of life data often fail to report results that provide interpretable estimates of magnitude of effect. Strategies that investigators could use to remedy this problem include reporting mean differences between groups in relation to the minimal important difference and reporting the proportion of patients who benefit from treatment and the associated number needed to treat. Techniques are available that allow investigators to use the same strategies in reporting pooled estimates from meta-analyses, even when studies use different instruments to measure the same construct. These reporting approaches, as well as ensuring access to data from individual items, will also help those developing decision aids to use quality of life data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0962-9343
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1097-105
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
How can quality of life researchers make their work more useful to health workers and their patients?
pubmed:affiliation
CLARITY Research Group, Department of Clinical Epidemiology and Biostatistics, Health Sciences Centre, McMaster University, 1200 Main Street West, Rm. HSC 2C12, Hamilton, ON, Canada, L8N 3Z5. guyatt@mcmaster.ca
pubmed:publicationType
Journal Article, Review