pubmed-article:18216292 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:18216292 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
pubmed-article:18216292 | lifeskim:mentions | umls-concept:C0040053 | lld:lifeskim |
pubmed-article:18216292 | lifeskim:mentions | umls-concept:C1527148 | lld:lifeskim |
pubmed-article:18216292 | lifeskim:mentions | umls-concept:C1519941 | lld:lifeskim |
pubmed-article:18216292 | lifeskim:mentions | umls-concept:C0681890 | lld:lifeskim |
pubmed-article:18216292 | pubmed:issue | 10 | lld:pubmed |
pubmed-article:18216292 | pubmed:dateCreated | 2008-5-9 | lld:pubmed |
pubmed-article:18216292 | pubmed:abstractText | Risk of venous thromboembolism (VTE) is elevated in cancer, but individual risk factors cannot identify a sufficiently high-risk group of outpatients for thromboprophylaxis. We developed a simple model for predicting chemotherapy-associated VTE using baseline clinical and laboratory variables. The association of VTE with multiple variables was characterized in a derivation cohort of 2701 cancer outpatients from a prospective observational study. A risk model was derived and validated in an independent cohort of 1365 patients from the same study. Five predictive variables were identified in a multivariate model: site of cancer (2 points for very high-risk site, 1 point for high-risk site), platelet count of 350 x 10(9)/L or more, hemoglobin less than 100 g/L (10 g/dL) and/or use of erythropoiesis-stimulating agents, leukocyte count more than 11 x 10(9)/L, and body mass index of 35 kg/m(2) or more (1 point each). Rates of VTE in the derivation and validation cohorts, respectively, were 0.8% and 0.3% in low-risk (score = 0), 1.8% and 2% in intermediate-risk (score = 1-2), and 7.1% and 6.7% in high-risk (score >/= 3) category over a median of 2.5 months (C-statistic = 0.7 for both cohorts). This model can identify patients with a nearly 7% short-term risk of symptomatic VTE and may be used to select cancer outpatients for studies of thromboprophylaxis. | lld:pubmed |
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pubmed-article:18216292 | pubmed:language | eng | lld:pubmed |
pubmed-article:18216292 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:18216292 | pubmed:citationSubset | AIM | lld:pubmed |
pubmed-article:18216292 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:18216292 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:18216292 | pubmed:month | May | lld:pubmed |
pubmed-article:18216292 | pubmed:issn | 1528-0020 | lld:pubmed |
pubmed-article:18216292 | pubmed:author | pubmed-author:LymanGary HGH | lld:pubmed |
pubmed-article:18216292 | pubmed:author | pubmed-author:KudererNicole... | lld:pubmed |
pubmed-article:18216292 | pubmed:author | pubmed-author:FrancisCharle... | lld:pubmed |
pubmed-article:18216292 | pubmed:author | pubmed-author:KhoranaAlok... | lld:pubmed |
pubmed-article:18216292 | pubmed:author | pubmed-author:CulakovaEvaE | lld:pubmed |
pubmed-article:18216292 | pubmed:issnType | Electronic | lld:pubmed |
pubmed-article:18216292 | pubmed:day | 15 | lld:pubmed |
pubmed-article:18216292 | pubmed:volume | 111 | lld:pubmed |
pubmed-article:18216292 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:18216292 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:18216292 | pubmed:pagination | 4902-7 | lld:pubmed |
pubmed-article:18216292 | pubmed:dateRevised | 2010-9-22 | lld:pubmed |
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