Ontology type: schema:ScholarlyArticle
2017-04
AUTHORSDong Ho Lee, Jeong Min Lee, Nam-Joon Yi, Kwang-Woong Lee, Kyung-Suk Suh, Jeong-Hoon Lee, Kyung Bun Lee, Joon Koo Han
ABSTRACTPURPOSE: To evaluate prognostic value of hepatic stiffness (HS) measurement using MR elastography (MRE) in patients with hepatocellular carcinoma (HCC) treated by hepatic resection (HR). METHODS: We enrolled 144 patients with Barcelona Clinic Liver Cancer stage A HCCs initially treated by HR who underwent preoperative liver MRE between January 2010 and June 2013. HS values were measured using MRE. Receiver operating characteristics (ROC) and multivariate logistic regression analyses were used to determine significant predictive factors for posthepatecomy liver failure (PHLF). Overall survival (OS) was analyzed by evaluating prognostic factors using the Kaplan-Meier method and Cox proportional hazard regression model. RESULTS: After HR, 43 patients (29.9 %) experienced PHLF. HS values were significant predictive factors for PHLF. In ROC analysis, the area under the curve of HS was 0.740 (P = 0.001) for PHLF. Thirty-one patients had HS values ≥ 4.02 kPa; the estimated 1, 3, 5-year survival were 90.0 %, 74.7 % and 65.4 %, respectively, versus 98.1 %, 96.5 % and 96.5 % in 113 patients with HS values < 4.02 kPa (P = 0.015). An HS value ≥ 4.02 kPa was the only significant affecting factor for OS. CONCLUSION: HS values measured by MRE could predict PHLF development post-HR. Furthermore, an HS value ≥4.02 kPa was a significant predicting factor for poor OS post-HR. KEY POINTS: • Hepatic stiffness value was a predictive factor for developing posthepatectomy liver failure • Hepatic stiffness value was a significant affecting factor for OS • Hepatic stiffness value ≥ 4.02 kPa was a predictive factor for poor OS. More... »
PAGES1713-1721
http://scigraph.springernature.com/pub.10.1007/s00330-016-4499-8
DOIhttp://dx.doi.org/10.1007/s00330-016-4499-8
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1005076543
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/27456966
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"description": "PURPOSE: To evaluate prognostic value of hepatic stiffness (HS) measurement using MR elastography (MRE) in patients with hepatocellular carcinoma (HCC) treated by hepatic resection (HR).\nMETHODS: We enrolled 144 patients with Barcelona Clinic Liver Cancer stage A HCCs initially treated by HR who underwent preoperative liver MRE between January 2010 and June 2013. HS values were measured using MRE. Receiver operating characteristics (ROC) and multivariate logistic regression analyses were used to determine significant predictive factors for posthepatecomy liver failure (PHLF). Overall survival (OS) was analyzed by evaluating prognostic factors using the Kaplan-Meier method and Cox proportional hazard regression model.\nRESULTS: After HR, 43 patients (29.9\u00a0%) experienced PHLF. HS values were significant predictive factors for PHLF. In ROC analysis, the area under the curve of HS was 0.740 (P\u2009=\u20090.001) for PHLF. Thirty-one patients had HS values\u2009\u2265\u20094.02 kPa; the estimated 1, 3, 5-year survival were 90.0\u00a0%, 74.7\u00a0% and 65.4\u00a0%, respectively, versus 98.1\u00a0%, 96.5\u00a0% and 96.5\u00a0% in 113 patients with HS values\u2009<\u20094.02 kPa (P\u2009=\u20090.015). An HS value\u2009\u2265\u20094.02 kPa was the only significant affecting factor for OS.\nCONCLUSION: HS values measured by MRE could predict PHLF development post-HR. Furthermore, an HS value \u22654.02 kPa was a significant predicting factor for poor OS post-HR.\nKEY POINTS: \u2022 Hepatic stiffness value was a predictive factor for developing posthepatectomy liver failure \u2022 Hepatic stiffness value was a significant affecting factor for OS \u2022 Hepatic stiffness value\u2009\u2265\u20094.02 kPa was a predictive factor for poor OS.",
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]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"27456966"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"9114774"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00330-016-4499-8"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1005076543"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00330-016-4499-8",
"https://app.dimensions.ai/details/publication/pub.1005076543"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T12:27",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87119_00000000.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs00330-016-4499-8"
}
]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.10.1007/s00330-016-4499-8'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00330-016-4499-8'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-016-4499-8'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-016-4499-8'
This table displays all metadata directly associated to this object as RDF triples.
324 TRIPLES
21 PREDICATES
90 URIs
36 LITERALS
24 BLANK NODES