Ontology type: schema:ScholarlyArticle
2019-04
AUTHORS ABSTRACTPURPOSE: To assess the impact of postmastectomy radiotherapy (PMRT) on overall survival and relapse-free survival among breast cancer patients with T1-T2 N1 disease who received standard adjuvant systemic therapy. METHODS: This is an individual patient data pooled analysis of 1053 breast cancer patients referred for adjuvant therapy in three clinical trials (BIG 02/98, BCIRG001, and BCIRG005). Overall survival was assessed according to whether or not patients received adjuvant radiotherapy through Kaplan-Meier analysis. Univariate and multivariate analyses of predictors of overall and relapse-free survival were conducted through Cox regression analysis. RESULTS: Locoregional relapse rates (after a median follow up of 116 months) were 5.6% among patients who received adjuvant radiotherapy vs. 6.6% among patients who did not receive adjuvant radiotherapy. Actuarial 5‑ and 10-year locoregional relapse-free survival rates were 94 and 93%, respectively, among patients who did not receive adjuvant radiotherapy versus 95 and 92% among patients who received adjuvant radiotherapy. The following factors were associated with worse overall survival in multivariate Cox regression analysis: age < 40 years (P < 0.0001), T2 stage (P = 0.004), higher lymph node ratio (P < 0.0001), and negative hormone receptor status (P < 0.0001). Likewise, the following factors were predictive of shorter locoregional relapse-free survival: age ≤ 40 (P < 0.0001), no PMRT (P = 0.034), fluorouracil/adriamycin/cyclophosphamide (FAC) chemotherapy (P = 0.001), and higher T stage (P = 0.002). CONCLUSION: The current analysis does not show a beneficial impact of PMRT on overall or relapse-free survival among patients with T1-T2 N1 disease who received standard adjuvant systemic therapy. There is, however, evidence of improvement in locoregional relapse-free survival with PMRT. These findings need to be prospectively validated. More... »
PAGES297-305
http://scigraph.springernature.com/pub.10.1007/s00066-018-1343-x
DOIhttp://dx.doi.org/10.1007/s00066-018-1343-x
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1105948626
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30069737
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1112",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Oncology and Carcinogenesis",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Calgary",
"id": "https://www.grid.ac/institutes/grid.22072.35",
"name": [
"Clinical Oncology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt",
"Department of Oncology, Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada"
],
"type": "Organization"
},
"familyName": "Abdel-Rahman",
"givenName": "Omar",
"id": "sg:person.0671451062.54",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0671451062.54"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s00066-014-0687-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002312946",
"https://doi.org/10.1007/s00066-014-0687-0"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrobp.2013.06.596",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002448627"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.radonc.2007.02.001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002615469"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1200/jco.2010.28.5437",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008541211"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/bcr3179",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012055898",
"https://doi.org/10.1186/bcr3179"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1468-0262.2006.00655.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019345933"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1468-0262.2006.00655.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019345933"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/annonc/mdv298",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022951845"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1056/nejm199710023371402",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032226289"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0140-6736(14)60488-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036942698"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2478/raon-2013-0085",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043325959"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1056/nejm199710023371401",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045884455"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrobp.2004.08.009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047875446"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0140-6736(98)09201-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048838308"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0360-3016(01)02724-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051149247"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1470-2045(12)70525-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053153526"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.6004/jnccn.2016.0181",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1079276038"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.6004/jnccn.2016.0181",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1079276038"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.6004/jnccn.2017.0072",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085470559"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.6004/jnccn.2017.0072",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085470559"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrobp.2018.01.105",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100829604"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrobp.2018.01.105",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100829604"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrobp.2018.01.105",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100829604"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12032-018-1129-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1103218946",
"https://doi.org/10.1007/s12032-018-1129-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12032-018-1129-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1103218946",
"https://doi.org/10.1007/s12032-018-1129-0"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-04",
"datePublishedReg": "2019-04-01",
"description": "PURPOSE: To assess the impact of postmastectomy radiotherapy (PMRT) on overall survival and relapse-free survival among breast cancer patients with T1-T2 N1 disease who received standard adjuvant systemic therapy.\nMETHODS: This is an individual patient data pooled analysis of 1053 breast cancer patients referred for adjuvant therapy in three clinical trials (BIG\u00a002/98, BCIRG001, and BCIRG005). Overall survival was assessed according to whether or not patients received adjuvant radiotherapy through Kaplan-Meier analysis. Univariate and multivariate analyses of predictors of overall and relapse-free survival were conducted through Cox regression analysis.\nRESULTS: Locoregional relapse rates (after a\u00a0median follow up of 116\u00a0months) were 5.6% among patients who received adjuvant radiotherapy vs. 6.6% among patients who did not receive adjuvant radiotherapy. Actuarial 5\u2011 and 10-year locoregional relapse-free survival rates were 94 and 93%, respectively, among patients who did not receive adjuvant radiotherapy versus 95 and 92% among patients who received adjuvant radiotherapy. The following factors were associated with worse overall survival in multivariate Cox regression analysis: age\u202f<\u200940\u00a0years (P\u202f<\u20090.0001), T2 stage (P\u202f=\u20090.004), higher lymph node ratio (P\u202f<\u20090.0001), and negative hormone receptor status (P\u202f<\u20090.0001). Likewise, the following factors were predictive of shorter locoregional relapse-free survival: age\u202f\u2264\u200940 (P\u202f<\u20090.0001), no PMRT (P\u202f=\u20090.034), fluorouracil/adriamycin/cyclophosphamide (FAC) chemotherapy (P\u202f=\u20090.001), and higher T\u00a0stage (P\u202f=\u20090.002).\nCONCLUSION: The current analysis does not show a\u00a0beneficial impact of PMRT on overall or relapse-free survival among patients with T1-T2 N1 disease who received standard adjuvant systemic therapy. There is, however, evidence of improvement in locoregional relapse-free survival with PMRT. These findings need to be prospectively validated.",
"genre": "research_article",
"id": "sg:pub.10.1007/s00066-018-1343-x",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1054450",
"issn": [
"0179-7158",
"1439-099X"
],
"name": "Strahlentherapie und Onkologie",
"type": "Periodical"
},
{
"issueNumber": "4",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "195"
}
],
"name": "Impact of postmastectomy radiotherapy on the outcomes of breast cancer patients with T1\u20132 N1 disease",
"pagination": "297-305",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"947736e6a8ce98b2df9b458813953ec3bc08f7cd0065ab6f6838f74cc6d7a866"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30069737"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"8603469"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00066-018-1343-x"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1105948626"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00066-018-1343-x",
"https://app.dimensions.ai/details/publication/pub.1105948626"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T13:18",
"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/v90/0000000368_0000000368/records_78947_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs00066-018-1343-x"
}
]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/s00066-018-1343-x'
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/s00066-018-1343-x'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00066-018-1343-x'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00066-018-1343-x'
This table displays all metadata directly associated to this object as RDF triples.
130 TRIPLES
21 PREDICATES
48 URIs
21 LITERALS
9 BLANK NODES