Menopausal status dependence of the timing of breast cancer recurrence after surgical removal of the primary tumour View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2004-10-11

AUTHORS

Romano Demicheli, Gianni Bonadonna, William JM Hrushesky, Michael W Retsky, Pinuccia Valagussa

ABSTRACT

INTRODUCTION: Information on the metastasis process in breast cancer patients undergoing primary tumour removal may be extracted from an analysis of the timing of clinical recurrence. METHODS: The hazard rate for local-regional and/or distant recurrence as the first event during the first 4 years after surgery was studied in 1173 patients undergoing mastectomy alone as primary treatment for operable breast cancer. Subset analyses were performed according to tumour size, axillary nodal status and menopausal status. RESULTS: A sharp two-peaked hazard function was observed for node-positive pre-menopausal patients, whereas results from node-positive post-menopausal women always displayed a single broad peak. The first narrow peak among pre-menopausal women showed a very steep rise to a maximum about 8-10 months after mastectomy. The second peak was considerably broader, reaching its maximum at 28-30 months. Post-menopausal patients displayed a wide, nearly symmetrical peak with maximum risk at about 18-20 months. Peaks displayed increasing height with increasing axillary lymph node involvement. No multi-peaked pattern was evident for either pre-menopausal or post-menopausal node-negative patients; however, this finding should be considered cautiously because of the limited number of events. Tumour size influenced recurrence risk but not its timing. Findings resulting from the different subsets of patients were remarkably coherent and each observed peak maintained the same position on the time axis in all analysed subsets. CONCLUSIONS: The risk of early recurrence for node positive patients is dependent on menopausal status. The amount of axillary nodal involvement and the tumour size modulate the risk value at any given time. For pre-menopausal node-positive patients, the abrupt increase of the first narrow peak of the recurrence risk suggests a triggering event that synchronises early risk. We suggest that this event is the surgical removal of the primary tumour. The later, broader, more symmetrical risk peaks indicate that some features of the corresponding metastatic development may present stochastic traits. A metastasis development model incorporating tumour dormancy in specific micro-metastatic phases, stochastic transitions between them and sudden acceleration of the metastatic process by surgery can explain these risk dynamics. More... »

PAGES

r689-r696

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/bcr937

DOI

http://dx.doi.org/10.1186/bcr937

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1035017267

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/15535851


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged, 80 and over", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Breast Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computer Simulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Disease-Free Survival", 
        "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": "Lymph Nodes", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lymphatic Metastasis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neoplasm Recurrence, Local", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Postmenopause", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Premenopause", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Proportional Hazards Models", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Istituto Nazionale Tumori, Milano, Italy", 
          "id": "http://www.grid.ac/institutes/grid.417893.0", 
          "name": [
            "Istituto Nazionale Tumori, Milano, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Demicheli", 
        "givenName": "Romano", 
        "id": "sg:person.01276602137.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01276602137.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Istituto Nazionale Tumori, Milano, Italy", 
          "id": "http://www.grid.ac/institutes/grid.417893.0", 
          "name": [
            "Istituto Nazionale Tumori, Milano, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bonadonna", 
        "givenName": "Gianni", 
        "id": "sg:person.01241043477.74", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01241043477.74"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Dorn VA Medical Center, Columbia, South Carolina, USA", 
          "id": "http://www.grid.ac/institutes/grid.417149.e", 
          "name": [
            "Dorn VA Medical Center, Columbia, South Carolina, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hrushesky", 
        "givenName": "William JM", 
        "id": "sg:person.01052725753.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01052725753.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA", 
          "id": "http://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Surgery, Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Retsky", 
        "givenName": "Michael W", 
        "id": "sg:person.01136261745.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136261745.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Istituto Nazionale Tumori, Milano, Italy", 
          "id": "http://www.grid.ac/institutes/grid.417893.0", 
          "name": [
            "Istituto Nazionale Tumori, Milano, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Valagussa", 
        "givenName": "Pinuccia", 
        "id": "sg:person.0715002305.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715002305.49"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nm0295-149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025343841", 
          "https://doi.org/10.1038/nm0295-149"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1019659925311", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051474111", 
          "https://doi.org/10.1023/a:1019659925311"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1006134702484", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014296348", 
          "https://doi.org/10.1023/a:1006134702484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1005849301420", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009909028", 
          "https://doi.org/10.1023/a:1005849301420"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01807163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004222897", 
          "https://doi.org/10.1007/bf01807163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1005887422022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041434159", 
          "https://doi.org/10.1023/a:1005887422022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/bcr804", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004879621", 
          "https://doi.org/10.1186/bcr804"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1010626302152", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035651053", 
          "https://doi.org/10.1023/a:1010626302152"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1054/bjoc.2001.1969", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037578852", 
          "https://doi.org/10.1054/bjoc.2001.1969"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2004-10-11", 
    "datePublishedReg": "2004-10-11", 
    "description": "INTRODUCTION: Information on the metastasis process in breast cancer patients undergoing primary tumour removal may be extracted from an analysis of the timing of clinical recurrence.\nMETHODS: The hazard rate for local-regional and/or distant recurrence as the first event during the first 4 years after surgery was studied in 1173 patients undergoing mastectomy alone as primary treatment for operable breast cancer. Subset analyses were performed according to tumour size, axillary nodal status and menopausal status.\nRESULTS: A sharp two-peaked hazard function was observed for node-positive pre-menopausal patients, whereas results from node-positive post-menopausal women always displayed a single broad peak. The first narrow peak among pre-menopausal women showed a very steep rise to a maximum about 8-10 months after mastectomy. The second peak was considerably broader, reaching its maximum at 28-30 months. Post-menopausal patients displayed a wide, nearly symmetrical peak with maximum risk at about 18-20 months. Peaks displayed increasing height with increasing axillary lymph node involvement. No multi-peaked pattern was evident for either pre-menopausal or post-menopausal node-negative patients; however, this finding should be considered cautiously because of the limited number of events. Tumour size influenced recurrence risk but not its timing. Findings resulting from the different subsets of patients were remarkably coherent and each observed peak maintained the same position on the time axis in all analysed subsets.\nCONCLUSIONS: The risk of early recurrence for node positive patients is dependent on menopausal status. The amount of axillary nodal involvement and the tumour size modulate the risk value at any given time. For pre-menopausal node-positive patients, the abrupt increase of the first narrow peak of the recurrence risk suggests a triggering event that synchronises early risk. We suggest that this event is the surgical removal of the primary tumour. The later, broader, more symmetrical risk peaks indicate that some features of the corresponding metastatic development may present stochastic traits. A metastasis development model incorporating tumour dormancy in specific micro-metastatic phases, stochastic transitions between them and sudden acceleration of the metastatic process by surgery can explain these risk dynamics.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/bcr937", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7138316", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1022375", 
        "issn": [
          "1465-5411", 
          "1465-542X"
        ], 
        "name": "Breast Cancer Research", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "6"
      }
    ], 
    "keywords": [
      "menopausal status", 
      "tumor size", 
      "surgical removal", 
      "primary tumor", 
      "recurrence risk", 
      "pre-menopausal patients", 
      "node-positive patients", 
      "node-negative patients", 
      "axillary lymph node involvement", 
      "pre-menopausal women", 
      "post-menopausal patients", 
      "post-menopausal women", 
      "operable breast cancer", 
      "axillary nodal involvement", 
      "axillary nodal status", 
      "node positive patients", 
      "lymph node involvement", 
      "breast cancer patients", 
      "breast cancer recurrence", 
      "primary tumor removal", 
      "multi-peaked pattern", 
      "clinical recurrence", 
      "distant recurrence", 
      "node involvement", 
      "positive patients", 
      "nodal status", 
      "early recurrence", 
      "nodal involvement", 
      "cancer patients", 
      "tumor removal", 
      "cancer recurrence", 
      "primary treatment", 
      "subset analysis", 
      "breast cancer", 
      "early risk", 
      "patients", 
      "metastatic development", 
      "recurrence", 
      "tumor dormancy", 
      "metastatic process", 
      "metastasis process", 
      "first narrow peak", 
      "months", 
      "mastectomy", 
      "risk", 
      "surgery", 
      "tumors", 
      "risk peaks", 
      "women", 
      "maximum risk", 
      "status", 
      "first event", 
      "involvement", 
      "different subsets", 
      "findings", 
      "cancer", 
      "subset", 
      "events", 
      "second peak", 
      "treatment", 
      "risk values", 
      "timing", 
      "limited number", 
      "steep rise", 
      "hazard rate", 
      "years", 
      "removal", 
      "time", 
      "increase", 
      "rate", 
      "sudden acceleration", 
      "abrupt increase", 
      "hazard function", 
      "analysis", 
      "same position", 
      "patterns", 
      "function", 
      "size", 
      "development", 
      "number", 
      "peak", 
      "rise", 
      "features", 
      "results", 
      "risk dynamics", 
      "information", 
      "height", 
      "values", 
      "amount", 
      "stochastic traits", 
      "maximum", 
      "model", 
      "symmetrical peak", 
      "process", 
      "phase", 
      "position", 
      "single broad peak", 
      "acceleration", 
      "traits", 
      "dormancy", 
      "transition", 
      "dependence", 
      "broad peak", 
      "narrow peak", 
      "dynamics", 
      "observed peaks", 
      "development model", 
      "stochastic transitions", 
      "two-peaked hazard function", 
      "node-positive pre-menopausal patients", 
      "node-positive post-menopausal women", 
      "post-menopausal node-negative patients", 
      "pre-menopausal node-positive patients", 
      "symmetrical risk peaks", 
      "corresponding metastatic development", 
      "metastasis development model", 
      "specific micro-metastatic phases", 
      "micro-metastatic phases", 
      "Menopausal status dependence", 
      "status dependence"
    ], 
    "name": "Menopausal status dependence of the timing of breast cancer recurrence after surgical removal of the primary tumour", 
    "pagination": "r689-r696", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1035017267"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/bcr937"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "15535851"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/bcr937", 
      "https://app.dimensions.ai/details/publication/pub.1035017267"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-12-01T19:16", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/article/article_393.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/bcr937"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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.10.1186/bcr937'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/bcr937'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/bcr937'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/bcr937'


 

This table displays all metadata directly associated to this object as RDF triples.

322 TRIPLES      22 PREDICATES      172 URIs      155 LITERALS      24 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/bcr937 schema:about N15c2b94bda094094aa385e3d279e39ca
2 N171f770fbb57452aa48fdb348fd84116
3 N20932ac395df41ba90c8d5ae9599bc7a
4 N243ed18d166345a08fd85e85ff16d2ea
5 N35d0ad6cae9f433eb6f65ab62e287cb4
6 N553f3548d14a405698bb7b5378d0c622
7 N6059271b016646419212f470d88d02a3
8 N7a66ed11b15e44fca0b0996da907c535
9 N8830197940b64d2b9012475017631449
10 N8b9fbc6c331b4ce6912829a0c7b31dcc
11 N8e733f1f902f41daa9701786054fc9a8
12 Nb47b4a46b453420c9bf51cc014f23bac
13 Nbe289064edc44a6eb00d324ebc71a48f
14 Nbf109620494b43c784d753a2ca00bc0d
15 Nc83542765e7e4ef7a1eeadd1afdb79f3
16 Ne68158049c084effb1eac1e5dd2a7747
17 Nf213ce0aadeb49269bf94bca1121040b
18 anzsrc-for:11
19 anzsrc-for:1112
20 schema:author N6c6143527967477595aca059a0651e2d
21 schema:citation sg:pub.10.1007/bf01807163
22 sg:pub.10.1023/a:1005849301420
23 sg:pub.10.1023/a:1005887422022
24 sg:pub.10.1023/a:1006134702484
25 sg:pub.10.1023/a:1010626302152
26 sg:pub.10.1023/a:1019659925311
27 sg:pub.10.1038/nm0295-149
28 sg:pub.10.1054/bjoc.2001.1969
29 sg:pub.10.1186/bcr804
30 schema:datePublished 2004-10-11
31 schema:datePublishedReg 2004-10-11
32 schema:description INTRODUCTION: Information on the metastasis process in breast cancer patients undergoing primary tumour removal may be extracted from an analysis of the timing of clinical recurrence. METHODS: The hazard rate for local-regional and/or distant recurrence as the first event during the first 4 years after surgery was studied in 1173 patients undergoing mastectomy alone as primary treatment for operable breast cancer. Subset analyses were performed according to tumour size, axillary nodal status and menopausal status. RESULTS: A sharp two-peaked hazard function was observed for node-positive pre-menopausal patients, whereas results from node-positive post-menopausal women always displayed a single broad peak. The first narrow peak among pre-menopausal women showed a very steep rise to a maximum about 8-10 months after mastectomy. The second peak was considerably broader, reaching its maximum at 28-30 months. Post-menopausal patients displayed a wide, nearly symmetrical peak with maximum risk at about 18-20 months. Peaks displayed increasing height with increasing axillary lymph node involvement. No multi-peaked pattern was evident for either pre-menopausal or post-menopausal node-negative patients; however, this finding should be considered cautiously because of the limited number of events. Tumour size influenced recurrence risk but not its timing. Findings resulting from the different subsets of patients were remarkably coherent and each observed peak maintained the same position on the time axis in all analysed subsets. CONCLUSIONS: The risk of early recurrence for node positive patients is dependent on menopausal status. The amount of axillary nodal involvement and the tumour size modulate the risk value at any given time. For pre-menopausal node-positive patients, the abrupt increase of the first narrow peak of the recurrence risk suggests a triggering event that synchronises early risk. We suggest that this event is the surgical removal of the primary tumour. The later, broader, more symmetrical risk peaks indicate that some features of the corresponding metastatic development may present stochastic traits. A metastasis development model incorporating tumour dormancy in specific micro-metastatic phases, stochastic transitions between them and sudden acceleration of the metastatic process by surgery can explain these risk dynamics.
33 schema:genre article
34 schema:inLanguage en
35 schema:isAccessibleForFree true
36 schema:isPartOf N143e106a583c450bbff49b44f05fdc6c
37 N3a785cf4bf5c451abf256ad1adce1362
38 sg:journal.1022375
39 schema:keywords Menopausal status dependence
40 abrupt increase
41 acceleration
42 amount
43 analysis
44 axillary lymph node involvement
45 axillary nodal involvement
46 axillary nodal status
47 breast cancer
48 breast cancer patients
49 breast cancer recurrence
50 broad peak
51 cancer
52 cancer patients
53 cancer recurrence
54 clinical recurrence
55 corresponding metastatic development
56 dependence
57 development
58 development model
59 different subsets
60 distant recurrence
61 dormancy
62 dynamics
63 early recurrence
64 early risk
65 events
66 features
67 findings
68 first event
69 first narrow peak
70 function
71 hazard function
72 hazard rate
73 height
74 increase
75 information
76 involvement
77 limited number
78 lymph node involvement
79 mastectomy
80 maximum
81 maximum risk
82 menopausal status
83 metastasis development model
84 metastasis process
85 metastatic development
86 metastatic process
87 micro-metastatic phases
88 model
89 months
90 multi-peaked pattern
91 narrow peak
92 nodal involvement
93 nodal status
94 node involvement
95 node positive patients
96 node-negative patients
97 node-positive patients
98 node-positive post-menopausal women
99 node-positive pre-menopausal patients
100 number
101 observed peaks
102 operable breast cancer
103 patients
104 patterns
105 peak
106 phase
107 position
108 positive patients
109 post-menopausal node-negative patients
110 post-menopausal patients
111 post-menopausal women
112 pre-menopausal node-positive patients
113 pre-menopausal patients
114 pre-menopausal women
115 primary treatment
116 primary tumor
117 primary tumor removal
118 process
119 rate
120 recurrence
121 recurrence risk
122 removal
123 results
124 rise
125 risk
126 risk dynamics
127 risk peaks
128 risk values
129 same position
130 second peak
131 single broad peak
132 size
133 specific micro-metastatic phases
134 status
135 status dependence
136 steep rise
137 stochastic traits
138 stochastic transitions
139 subset
140 subset analysis
141 sudden acceleration
142 surgery
143 surgical removal
144 symmetrical peak
145 symmetrical risk peaks
146 time
147 timing
148 traits
149 transition
150 treatment
151 tumor dormancy
152 tumor removal
153 tumor size
154 tumors
155 two-peaked hazard function
156 values
157 women
158 years
159 schema:name Menopausal status dependence of the timing of breast cancer recurrence after surgical removal of the primary tumour
160 schema:pagination r689-r696
161 schema:productId N906ce508fad94b94b64ca254a9780e19
162 Na59f9af4aa004fbe97a60c2f28e112d9
163 Nf6db49587c3a4dfe8830b53350bd0955
164 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035017267
165 https://doi.org/10.1186/bcr937
166 schema:sdDatePublished 2021-12-01T19:16
167 schema:sdLicense https://scigraph.springernature.com/explorer/license/
168 schema:sdPublisher Na5d6a97ebafc4056822631379d646a3c
169 schema:url https://doi.org/10.1186/bcr937
170 sgo:license sg:explorer/license/
171 sgo:sdDataset articles
172 rdf:type schema:ScholarlyArticle
173 N143e106a583c450bbff49b44f05fdc6c schema:issueNumber 6
174 rdf:type schema:PublicationIssue
175 N15c2b94bda094094aa385e3d279e39ca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
176 schema:name Postmenopause
177 rdf:type schema:DefinedTerm
178 N171f770fbb57452aa48fdb348fd84116 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
179 schema:name Lymph Nodes
180 rdf:type schema:DefinedTerm
181 N20932ac395df41ba90c8d5ae9599bc7a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
182 schema:name Aged, 80 and over
183 rdf:type schema:DefinedTerm
184 N243ed18d166345a08fd85e85ff16d2ea schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
185 schema:name Lymphatic Metastasis
186 rdf:type schema:DefinedTerm
187 N35d0ad6cae9f433eb6f65ab62e287cb4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
188 schema:name Computer Simulation
189 rdf:type schema:DefinedTerm
190 N3a785cf4bf5c451abf256ad1adce1362 schema:volumeNumber 6
191 rdf:type schema:PublicationVolume
192 N553f3548d14a405698bb7b5378d0c622 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
193 schema:name Breast Neoplasms
194 rdf:type schema:DefinedTerm
195 N6059271b016646419212f470d88d02a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
196 schema:name Premenopause
197 rdf:type schema:DefinedTerm
198 N682537f95cf141b892864605114bebb8 rdf:first sg:person.01241043477.74
199 rdf:rest N7fb65345af73430a9503636b45471163
200 N6c6143527967477595aca059a0651e2d rdf:first sg:person.01276602137.37
201 rdf:rest N682537f95cf141b892864605114bebb8
202 N7a66ed11b15e44fca0b0996da907c535 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
203 schema:name Humans
204 rdf:type schema:DefinedTerm
205 N7fb65345af73430a9503636b45471163 rdf:first sg:person.01052725753.79
206 rdf:rest Nb9666a29d9bf490bbd34e0e2a6bedb53
207 N8830197940b64d2b9012475017631449 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
208 schema:name Risk Factors
209 rdf:type schema:DefinedTerm
210 N8b9fbc6c331b4ce6912829a0c7b31dcc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
211 schema:name Neoplasm Recurrence, Local
212 rdf:type schema:DefinedTerm
213 N8e733f1f902f41daa9701786054fc9a8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
214 schema:name Female
215 rdf:type schema:DefinedTerm
216 N906ce508fad94b94b64ca254a9780e19 schema:name pubmed_id
217 schema:value 15535851
218 rdf:type schema:PropertyValue
219 Na59f9af4aa004fbe97a60c2f28e112d9 schema:name doi
220 schema:value 10.1186/bcr937
221 rdf:type schema:PropertyValue
222 Na5d6a97ebafc4056822631379d646a3c schema:name Springer Nature - SN SciGraph project
223 rdf:type schema:Organization
224 Nb47b4a46b453420c9bf51cc014f23bac schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
225 schema:name Proportional Hazards Models
226 rdf:type schema:DefinedTerm
227 Nb9666a29d9bf490bbd34e0e2a6bedb53 rdf:first sg:person.01136261745.40
228 rdf:rest Nf6b24b04fb614329aa11117a72714101
229 Nbe289064edc44a6eb00d324ebc71a48f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
230 schema:name Adult
231 rdf:type schema:DefinedTerm
232 Nbf109620494b43c784d753a2ca00bc0d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
233 schema:name Aged
234 rdf:type schema:DefinedTerm
235 Nc83542765e7e4ef7a1eeadd1afdb79f3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
236 schema:name Middle Aged
237 rdf:type schema:DefinedTerm
238 Ne68158049c084effb1eac1e5dd2a7747 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
239 schema:name Retrospective Studies
240 rdf:type schema:DefinedTerm
241 Nf213ce0aadeb49269bf94bca1121040b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
242 schema:name Disease-Free Survival
243 rdf:type schema:DefinedTerm
244 Nf6b24b04fb614329aa11117a72714101 rdf:first sg:person.0715002305.49
245 rdf:rest rdf:nil
246 Nf6db49587c3a4dfe8830b53350bd0955 schema:name dimensions_id
247 schema:value pub.1035017267
248 rdf:type schema:PropertyValue
249 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
250 schema:name Medical and Health Sciences
251 rdf:type schema:DefinedTerm
252 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
253 schema:name Oncology and Carcinogenesis
254 rdf:type schema:DefinedTerm
255 sg:grant.7138316 http://pending.schema.org/fundedItem sg:pub.10.1186/bcr937
256 rdf:type schema:MonetaryGrant
257 sg:journal.1022375 schema:issn 1465-5411
258 1465-542X
259 schema:name Breast Cancer Research
260 schema:publisher Springer Nature
261 rdf:type schema:Periodical
262 sg:person.01052725753.79 schema:affiliation grid-institutes:grid.417149.e
263 schema:familyName Hrushesky
264 schema:givenName William JM
265 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01052725753.79
266 rdf:type schema:Person
267 sg:person.01136261745.40 schema:affiliation grid-institutes:grid.38142.3c
268 schema:familyName Retsky
269 schema:givenName Michael W
270 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136261745.40
271 rdf:type schema:Person
272 sg:person.01241043477.74 schema:affiliation grid-institutes:grid.417893.0
273 schema:familyName Bonadonna
274 schema:givenName Gianni
275 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01241043477.74
276 rdf:type schema:Person
277 sg:person.01276602137.37 schema:affiliation grid-institutes:grid.417893.0
278 schema:familyName Demicheli
279 schema:givenName Romano
280 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01276602137.37
281 rdf:type schema:Person
282 sg:person.0715002305.49 schema:affiliation grid-institutes:grid.417893.0
283 schema:familyName Valagussa
284 schema:givenName Pinuccia
285 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715002305.49
286 rdf:type schema:Person
287 sg:pub.10.1007/bf01807163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004222897
288 https://doi.org/10.1007/bf01807163
289 rdf:type schema:CreativeWork
290 sg:pub.10.1023/a:1005849301420 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009909028
291 https://doi.org/10.1023/a:1005849301420
292 rdf:type schema:CreativeWork
293 sg:pub.10.1023/a:1005887422022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041434159
294 https://doi.org/10.1023/a:1005887422022
295 rdf:type schema:CreativeWork
296 sg:pub.10.1023/a:1006134702484 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014296348
297 https://doi.org/10.1023/a:1006134702484
298 rdf:type schema:CreativeWork
299 sg:pub.10.1023/a:1010626302152 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035651053
300 https://doi.org/10.1023/a:1010626302152
301 rdf:type schema:CreativeWork
302 sg:pub.10.1023/a:1019659925311 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051474111
303 https://doi.org/10.1023/a:1019659925311
304 rdf:type schema:CreativeWork
305 sg:pub.10.1038/nm0295-149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025343841
306 https://doi.org/10.1038/nm0295-149
307 rdf:type schema:CreativeWork
308 sg:pub.10.1054/bjoc.2001.1969 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037578852
309 https://doi.org/10.1054/bjoc.2001.1969
310 rdf:type schema:CreativeWork
311 sg:pub.10.1186/bcr804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004879621
312 https://doi.org/10.1186/bcr804
313 rdf:type schema:CreativeWork
314 grid-institutes:grid.38142.3c schema:alternateName Department of Surgery, Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
315 schema:name Department of Surgery, Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
316 rdf:type schema:Organization
317 grid-institutes:grid.417149.e schema:alternateName Dorn VA Medical Center, Columbia, South Carolina, USA
318 schema:name Dorn VA Medical Center, Columbia, South Carolina, USA
319 rdf:type schema:Organization
320 grid-institutes:grid.417893.0 schema:alternateName Istituto Nazionale Tumori, Milano, Italy
321 schema:name Istituto Nazionale Tumori, Milano, Italy
322 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...