Linked Life Data

19859804

Source:http://linkedlifedata.com/resource/pubmed/id/19859804

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2010-7-14
pubmed:abstractText
Many studies correlating gene expression data to clinical parameters assume a linear increase or decrease of the clinical parameter under investigation with the expression of a gene. We have studied genes encoding important breast cancer-related proteins using a model for survival-type data that is based on natural splines and the Cox proportional hazard model, thereby removing the linearity assumption. Expression data of 16 genes were studied in relation to metastasis-free probability in a cohort of 295 consecutive breast cancer patients treated at The Netherlands Cancer Institute. The independent predictive power for disease outcome of the 16 individual genes was tested in a multivariable model with known clinical and pathological risk factors. There is a linear relationship between increasing expression and a higher or lower hazard for distant metastasis for ESR1, ERBB4, VEGF, CCNE2, EZH2, and UPA; for ERBB2, ERBB3, CCND1, CCNE1, EED, CXCR4, CCR7, SDF1, and PAI1 there is no clear increase or decrease; and for EGFR there seems to be a non-linear relation. Multivariable analysis showed that the 70-gene prognosis profile outperforms all the other variables in the model (hazard-rate 5.4, 95% CI 2.5-11.7; P = 0.000018). EGFR-expression seems to have a non-linear relation with disease outcome, indicating that lower but also higher expression of EGFR are associated with worse outcome compared to intermediate expression levels; the other genes show no or a linear relation.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1573-7217
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
122
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
711-20
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Analysis of breast cancer related gene expression using natural splines and the Cox proportional hazard model to identify prognostic associations.
pubmed:affiliation
Division of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, The Netherlands.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't