Linked Life Data

18999217

Source:http://linkedlifedata.com/resource/pubmed/id/18999217

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-11-12
pubmed:abstractText
The role of post-operative radiotherapy (PORT) is still controversial for some cancer sites. In the absence of large randomized controlled trials, survival prediction models can help estimate the predicted benefit of PORT for specific settings. The purpose of this study was to compare the performance of two types of prediction models for estimating the benefit of PORT for 2 cancer sites. Using data from the Surveillance, Epidemiology, and End Results database, we constructed prediction models for gallbladder (GB) cancer and non-small cell lung cancer (NSMLC), using Cox proportional hazards and Random Survival Forests. We compared validation measures for discrimination and found that both the CPH and RSF models had comparable C-indices. For GB cancer, PORT was associated with improved survival for node positive patients, and for NSCLC, PORT was associated with a survival benefit for patients with N2 disease.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1942-597X
pubmed:author
pubmed:issnType
Electronic
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
348-52
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Survival prediction models for estimating the benefit of post-operative radiation therapy for gallbladder cancer and lung cancer.
pubmed:affiliation
Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, OR, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural