Linked Life Data

15201960

Source:http://linkedlifedata.com/resource/pubmed/id/15201960

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2004-6-17
pubmed:abstractText
This study assessed the prediction of gastric cancer recurrence based on detection of occult neoplastic cells (ONCs) in lymph nodes, and by using criteria that were developed to identify patients with a high risk of recurrence/metastasis. The subjects were 60 patients of stage II or III gastric cancer with lymph node metastasis. Prediction of recurrence based on the detection of ONCs showed a sensitivity of 33.3% (2/6), specificity of 70.0% (7/10), and accuracy of 51.7% in stage II patients, while the sensitivity was 73.5% (25/34), specificity was 100.0% (10/10), and accuracy was 86.8% in stage III patients. Prediction of recurrence based on the presence of at least 2 high-risk criteria had a sensitivity of 33.3% (2/6), specificity of 100.0% (10/10), and accuracy of 66.7% in stage II patients, while the sensitivity was 82.4% (28/34), specificity was 80.0% (8/10), and accuracy was 81.2% in stage III patients. These results suggest that prediction of recurrence/metastasis soon after surgery using ONCs plus the high-risk criteria can increase the specificity in stage II cancer, and can achieve a sensitivity of 80% or more with a high specificity and accuracy in stage III cancer.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1021-335X
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
63-6
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Accuracy of criteria for predicting recurrence and metastasis in stage II and III gastric cancer patients with lymph node metastasis.
pubmed:affiliation
Department of Surgery, Tokai University Oiso Hospital, Oiso, Kanagawa 259-0198, Japan. onc-res@oiso.u-tokai.ac.jp
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't