Ontology type: schema:ScholarlyArticle Open Access: True
2015-03
AUTHORSE Laas, P Mallon, M Delomenie, V Gardeux, J-Y Pierga, P Cottu, F Lerebours, D Stevens, R Rouzier, F Reyal
ABSTRACTBACKGROUND: Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level. METHODS: We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction. RESULTS: Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95% CI 0.71-0.77) for the Cancermath.net model and 0.72 (95% CI 0.69-0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90% with a median score dispersion at 0.08 (range 0.06-0.10). Dispersion, however, reached 30% for the subgroups with a predicted survival between 10 and 50%. CONCLUSION: This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups. More... »
PAGES912
http://scigraph.springernature.com/pub.10.1038/bjc.2014.641
DOIhttp://dx.doi.org/10.1038/bjc.2014.641
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1019044146
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/25590666
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"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Adult",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Breast Neoplasms",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Female",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Middle Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Models, Biological",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Receptor, ErbB-2",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Receptors, Estrogen",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "SEER Program",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Survival Analysis",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Web Browser",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"1] Department of Surgery, Institut Curie, Paris, France [2] Department of Gynecology, H\u00f4pital Tenon, Paris, France."
],
"type": "Organization"
},
"familyName": "Laas",
"givenName": "E",
"id": "sg:person.01347132026.83",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347132026.83"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"1] Department of Surgery, Institut Curie, Paris, France [2] Craigavon Area Hospital Breast Unit, Portadown BT63 5QQ, Northern Ireland."
],
"type": "Organization"
},
"familyName": "Mallon",
"givenName": "P",
"id": "sg:person.01221233570.94",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01221233570.94"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of Surgery, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Delomenie",
"givenName": "M",
"id": "sg:person.01352403660.89",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01352403660.89"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"1] Department of Informatics, EISTI Engineering School, Cergy, France [2] Department of Medicine, Bio5 Institute, University of Arizona, Tucson, AZ, USA."
],
"type": "Organization"
},
"familyName": "Gardeux",
"givenName": "V",
"id": "sg:person.01132534500.89",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132534500.89"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of medical oncology, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Pierga",
"givenName": "J-Y",
"id": "sg:person.0711334140.14",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0711334140.14"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of medical oncology, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Cottu",
"givenName": "P",
"id": "sg:person.0731533007.65",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0731533007.65"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of medical oncology, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Lerebours",
"givenName": "F",
"id": "sg:person.01075435727.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075435727.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of public health, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Stevens",
"givenName": "D",
"id": "sg:person.01226317002.01",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01226317002.01"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"Department of Surgery, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Rouzier",
"givenName": "R",
"id": "sg:person.01101754741.17",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01101754741.17"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute Curie",
"id": "https://www.grid.ac/institutes/grid.418596.7",
"name": [
"1] Department of Surgery, Institut Curie, Paris, France [2] Residual Tumor and Response to Treatment Team, Department of Translational Research, Institut Curie, Paris, France."
],
"type": "Organization"
},
"familyName": "Reyal",
"givenName": "F",
"id": "sg:person.01104374270.94",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01104374270.94"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1038/bjc.2012.166",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000550332",
"https://doi.org/10.1038/bjc.2012.166"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ejca.2012.01.034",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001374724"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1200/jco.2005.06.178",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001535254"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/cncr.24565",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005440551"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/cncr.24565",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005440551"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/bcr2464",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007180392",
"https://doi.org/10.1186/bcr2464"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrclinonc.2010.170",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010400980",
"https://doi.org/10.1038/nrclinonc.2010.170"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrclinonc.2010.170",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010400980",
"https://doi.org/10.1038/nrclinonc.2010.170"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/annonc/mdn590",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011470778"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0027446",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011897797"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature10983",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014607335",
"https://doi.org/10.1038/nature10983"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/sj.bjc.6605283",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021659705",
"https://doi.org/10.1038/sj.bjc.6605283"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/sj.bjc.6605283",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021659705",
"https://doi.org/10.1038/sj.bjc.6605283"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/bcr3038",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022312855",
"https://doi.org/10.1186/bcr3038"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1200/jco.2013.50.3417",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026821109"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10549-010-0794-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026878892",
"https://doi.org/10.1007/s10549-010-0794-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10549-010-0794-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026878892",
"https://doi.org/10.1007/s10549-010-0794-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/sim.1802",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027475560"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/sj.bjc.6605863",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035057816",
"https://doi.org/10.1038/sj.bjc.6605863"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/sj.bjc.6605863",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035057816",
"https://doi.org/10.1038/sj.bjc.6605863"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1470-2045(09)70254-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046690818"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1472-6947-12-108",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051355270",
"https://doi.org/10.1186/1472-6947-12-108"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1245/s10434-013-2956-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052562127",
"https://doi.org/10.1245/s10434-013-2956-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10549-011-1366-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053536280",
"https://doi.org/10.1007/s10549-011-1366-9"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1082880449",
"type": "CreativeWork"
}
],
"datePublished": "2015-03",
"datePublishedReg": "2015-03-01",
"description": "BACKGROUND: Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level.\nMETHODS: We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction.\nRESULTS: Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95% CI 0.71-0.77) for the Cancermath.net model and 0.72 (95% CI 0.69-0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90% with a median score dispersion at 0.08 (range 0.06-0.10). Dispersion, however, reached 30% for the subgroups with a predicted survival between 10 and 50%.\nCONCLUSION: This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups.",
"genre": "research_article",
"id": "sg:pub.10.1038/bjc.2014.641",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1017082",
"issn": [
"0007-0920",
"1532-1827"
],
"name": "British Journal of Cancer",
"type": "Periodical"
},
{
"issueNumber": "5",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "112"
}
],
"name": "Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models",
"pagination": "912",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"5abd25254b0d1b08ebef3963927ab9c52b7ae6b2989c20d97d7bc6b5ea5946b3"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"25590666"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"0370635"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1038/bjc.2014.641"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1019044146"
]
}
],
"sameAs": [
"https://doi.org/10.1038/bjc.2014.641",
"https://app.dimensions.ai/details/publication/pub.1019044146"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-10T23:13",
"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/v90/0000000001_0000000264/records_8693_00000434.jsonl",
"type": "ScholarlyArticle",
"url": "https://www.nature.com/articles/bjc2014641"
}
]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.10.1038/bjc.2014.641'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/bjc.2014.641'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/bjc.2014.641'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/bjc.2014.641'
This table displays all metadata directly associated to this object as RDF triples.
253 TRIPLES
21 PREDICATES
60 URIs
32 LITERALS
20 BLANK NODES