Ontology type: schema:ScholarlyArticle
2009-03
AUTHORSDaniel A. Anaya, Guy Lahat, Xuemei Wang, Lianchun Xiao, Daniel Tuvin, Peter W. Pisters, Dina C. Lev, Raphael E. Pollock
ABSTRACTBACKGROUND: Retroperitoneal sarcoma (RPS) American Joint Committee on Cancer (AJCC) staging applies to primary tumors only; due to specific RPS disease characteristics, staging is driven primarily by grade, stratifying patients into only two distinct prognostic subsets. The objective of this study was to help improve currently available staging for RPS by establishing a new, more robust histology-based prognostic system. METHODS: A RPS database of 1,118 patients seen at our institution (1996-2006) identified 343 patients treated for resectable primary or recurrent disease; a histologic subtype-based RPS prognostic system was designed and evaluated for prognostic accuracy in comparison with the current AJCC staging system. RESULTS: Histology stratified patients into three groups by prognosis (P<0.0002): atypical lipomatous tumor (ALT), non-ALT liposarcoma (LPS), and "other," an improvement compared with AJCC staging which could only identify two distinct prognostic groups. In contrast to AJCC staging, this prognostic stratification was reproducible for both primary and recurrent RPS (P<0.0001). After multivariate analysis, LPS (P=0.0004) and "other" histologies (P<0.0001) were found to be independent predictors of worse survival. The concordance ratio of this model was 0.74, equivalent to that of the model using the AJCC staging system. CONCLUSIONS: A histology-based RPS prognostic system has two advantages over AJCC staging: it can stratify into three versus two distinct prognostic groups, and it can be used for both primary and recurrent RPS. Distinct risk stratification is critical for specific assessment of prognosis as well as decisions regarding individualized adjuvant therapies, hence the advantage of a three-tiered histology-based system applicable in both primary and recurrent RPS. More... »
PAGES667-675
http://scigraph.springernature.com/pub.10.1245/s10434-008-0250-2
DOIhttp://dx.doi.org/10.1245/s10434-008-0250-2
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/19101765
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]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1245/s10434-008-0250-2'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1245/s10434-008-0250-2'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1245/s10434-008-0250-2'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1245/s10434-008-0250-2'
This table displays all metadata directly associated to this object as RDF triples.
302 TRIPLES
21 PREDICATES
83 URIs
39 LITERALS
27 BLANK NODES