Linked Life Data

20544271

Source:http://linkedlifedata.com/resource/pubmed/id/20544271

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-12-14
pubmed:abstractText
Epidemiological studies have evaluated the association between ATM C.1066-6T > G (IVS10-6T > G) mutation and breast cancer risk. However, the results remain conflicting rather than conclusive. In order to derive a more precise estimation of the relationship, we performed this meta-analysis. Systematic searches of PubMed and Medline databases were performed. A total of 11 studies including 8,831 cases and 4,957 controls were identified. The carrier frequency of the ATM C.1066-6T > G mutation was 0.5% (45/8,831) in patients with breast cancer and 0.7% (38/4,957) in healthy controls. When all the 11 studies were pooled into the meta-analysis, there was no evidence for significant association between C.1066-6T > G mutation and breast cancer risk (OR 0.87, 95% CI 0.55-1.37). In the subgroup analyses by source of controls and family history with BRCA1/2 status, no significant association were found in any subgroup of population. When sensitivity analyses were performed, all the results were not materially altered. In summary, the meta-analysis strongly suggests that ATM C.1066-6T > G mutation is not associated with increased breast cancer risk.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1573-7217
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
125
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
473-7
pubmed:dateRevised
2011-11-2
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Lack of association between ATM C.1066-6T > G mutation and breast cancer risk: a meta-analysis of 8,831 cases and 4,957 controls.
pubmed:affiliation
Longgang Center for Disease Control and Prevention of Shenzhen, Shenzhen, China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Meta-Analysis