The Prognostic Significance of Sentinel Lymph Node Status for Patients with Thick Melanoma View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-08-15

AUTHORS

Danielle M. Bello, Gang Han, Laura Jackson, Kaleigh Bulloch, Stephan Ariyan, Deepak Narayan, Bonnie Gould Rothberg, Dale Han

ABSTRACT

BackgroundSentinel lymph node biopsy (SLNB) is recommended for patients with intermediate-thickness melanoma, but the use of SLNB for patients with thick melanoma is debated. This report presents a single-institution study investigating factors predictive of sentinel lymph node (SLN) metastasis and outcome for thick-melanoma patients .MethodsA retrospective review of a single-institution database from 1997 to 2012 identified 147 patients with thick primary cutaneous melanoma (≥4 mm) who had an SLNB. Clinicopathologic characteristics were correlated with nodal status and outcome.ResultsThe median age of the patients was 67 years, and 61.9 % of the patients were men. The median tumor thickness was 5.5 mm, and 54 patients (36.7 %) had a positive SLN. Multivariable analysis showed that only tumor thickness significantly predicted SLN metastasis (odds ratio 1.14; 95 % confidence interval (CI) 1.02–1.28; P = 0.02). The overall median follow-up period was 34.6 months. Overall survival (OS) and melanoma-specific survival (MSS) were significantly worse for the positive versus negative-SLN patients. Multivariable analysis showed that age [hazard ratio (HR) 1.04; 95 % CI 1.01–1.07; P = 0.02] and SLN status (HR 2.24; 95 % CI 1.03–4.88; P = 0.04) significantly predicted OS, whereas only SLN status (HR 3.85; 95 % CI 2.13–6.97; P < 0.01) significantly predicted MSS.ConclusionsTumor thickness predicts SLN status in thick melanomas. Furthermore, SLN status is prognostic for OS and MSS in thick-melanoma patients, with positive-SLN patients having significantly worse OS and MSS. These findings show that SLNB should be recommended for thick-melanoma patients, particularly because detection of SLN metastasis can identify patients for potential systemic therapy and treatment of nodal disease at a microscopic stage. More... »

PAGES

938-945

Identifiers

URI

http://scigraph.springernature.com/pub.10.1245/s10434-016-5502-y

DOI

http://dx.doi.org/10.1245/s10434-016-5502-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037963676

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27527717


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": "Age Factors", 
        "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": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Follow-Up Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lymph Node Excision", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Melanoma", 
        "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": "Prognosis", 
        "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": "Sentinel Lymph Node", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sentinel Lymph Node Biopsy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Skin Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Survival Rate", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tumor Burden", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bello", 
        "givenName": "Danielle M.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, USA", 
          "id": "http://www.grid.ac/institutes/grid.264756.4", 
          "name": [
            "Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Gang", 
        "id": "sg:person.0723254444.14", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0723254444.14"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jackson", 
        "givenName": "Laura", 
        "id": "sg:person.015414304135.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015414304135.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bulloch", 
        "givenName": "Kaleigh", 
        "id": "sg:person.013413612021.89", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013413612021.89"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ariyan", 
        "givenName": "Stephan", 
        "id": "sg:person.014265505777.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014265505777.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Narayan", 
        "givenName": "Deepak", 
        "id": "sg:person.01006374045.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006374045.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rothberg", 
        "givenName": "Bonnie Gould", 
        "id": "sg:person.0757247334.39", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757247334.39"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA", 
          "id": "http://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Dale", 
        "id": "sg:person.0607026044.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0607026044.65"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1245/s10434-015-4894-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022565055", 
          "https://doi.org/10.1245/s10434-015-4894-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1245/s10434-010-1203-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010303932", 
          "https://doi.org/10.1245/s10434-010-1203-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02574492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023933653", 
          "https://doi.org/10.1007/bf02574492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1245/s10434-012-2826-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041968267", 
          "https://doi.org/10.1245/s10434-012-2826-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1245/aso.2003.03.055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010115773", 
          "https://doi.org/10.1245/aso.2003.03.055"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02574479", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049525477", 
          "https://doi.org/10.1007/bf02574479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10434-000-0160-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035530171", 
          "https://doi.org/10.1007/s10434-000-0160-4"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-08-15", 
    "datePublishedReg": "2016-08-15", 
    "description": "BackgroundSentinel lymph node biopsy (SLNB) is recommended for patients with intermediate-thickness melanoma, but the use of SLNB for patients with thick melanoma is debated. This report presents a single-institution study investigating factors predictive of sentinel lymph node (SLN) metastasis and outcome for thick-melanoma patients .MethodsA retrospective review of a single-institution database from 1997 to 2012 identified 147 patients with thick primary cutaneous melanoma (\u22654\u00a0mm) who had an SLNB. Clinicopathologic characteristics were correlated with nodal status and outcome.ResultsThe median age of the patients was 67\u00a0years, and 61.9\u00a0% of the patients were men. The median tumor thickness was 5.5\u00a0mm, and 54 patients (36.7\u00a0%) had a positive SLN. Multivariable analysis showed that only tumor thickness significantly predicted SLN metastasis (odds ratio 1.14; 95\u00a0% confidence interval (CI) 1.02\u20131.28; P\u00a0=\u00a00.02). The overall median follow-up period was 34.6\u00a0months. Overall survival (OS) and melanoma-specific survival (MSS) were significantly worse for the positive versus negative-SLN patients. Multivariable analysis showed that age [hazard ratio (HR) 1.04; 95\u00a0% CI 1.01\u20131.07; P\u00a0=\u00a00.02] and SLN status (HR 2.24; 95\u00a0% CI 1.03\u20134.88; P\u00a0=\u00a00.04) significantly predicted OS, whereas only SLN status (HR 3.85; 95\u00a0% CI 2.13\u20136.97; P\u00a0<\u00a00.01) significantly predicted MSS.ConclusionsTumor thickness predicts SLN status in thick melanomas. Furthermore, SLN status is prognostic for OS and MSS in thick-melanoma patients, with positive-SLN patients having significantly worse OS and MSS. These findings show that SLNB should be recommended for thick-melanoma patients, particularly because detection of SLN metastasis can identify patients for potential systemic therapy and treatment of nodal disease at a microscopic stage.", 
    "genre": "article", 
    "id": "sg:pub.10.1245/s10434-016-5502-y", 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2411237", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1105545", 
        "issn": [
          "1068-9265", 
          "1534-4681"
        ], 
        "name": "Annals of Surgical Oncology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "Suppl 5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "23"
      }
    ], 
    "keywords": [
      "melanoma-specific survival", 
      "thick melanoma patients", 
      "overall survival", 
      "SLN status", 
      "thick melanomas", 
      "SLN metastasis", 
      "multivariable analysis", 
      "tumor thickness", 
      "thick primary cutaneous melanoma", 
      "sentinel lymph node metastasis", 
      "sentinel lymph node status", 
      "intermediate-thickness melanomas", 
      "use of SLNB", 
      "positive SLN patients", 
      "potential systemic therapy", 
      "MethodsA retrospective review", 
      "median tumor thickness", 
      "overall median follow", 
      "single-institution database", 
      "lymph node status", 
      "lymph node metastasis", 
      "worse overall survival", 
      "single-institution study", 
      "primary cutaneous melanoma", 
      "BackgroundSentinel lymph", 
      "positive SLN", 
      "median follow", 
      "SLN patients", 
      "nodal disease", 
      "nodal status", 
      "systemic therapy", 
      "node metastasis", 
      "clinicopathologic characteristics", 
      "median age", 
      "retrospective review", 
      "prognostic significance", 
      "node status", 
      "cutaneous melanoma", 
      "patients", 
      "SLNB", 
      "melanoma", 
      "metastasis", 
      "status", 
      "survival", 
      "outcomes", 
      "age", 
      "lymph", 
      "biopsy", 
      "therapy", 
      "follow", 
      "SLN", 
      "disease", 
      "months", 
      "men", 
      "treatment", 
      "report", 
      "review", 
      "years", 
      "findings", 
      "period", 
      "factors", 
      "database", 
      "significance", 
      "study", 
      "analysis", 
      "microscopic stages", 
      "use", 
      "stage", 
      "detection", 
      "thickness", 
      "characteristics"
    ], 
    "name": "The Prognostic Significance of Sentinel Lymph Node Status for Patients with Thick Melanoma", 
    "pagination": "938-945", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1037963676"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1245/s10434-016-5502-y"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "27527717"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1245/s10434-016-5502-y", 
      "https://app.dimensions.ai/details/publication/pub.1037963676"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T16:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_717.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1245/s10434-016-5502-y"
  }
]
 

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.10.1245/s10434-016-5502-y'

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/s10434-016-5502-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1245/s10434-016-5502-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1245/s10434-016-5502-y'


 

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

293 TRIPLES      21 PREDICATES      122 URIs      107 LITERALS      26 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1245/s10434-016-5502-y schema:about N0c89990a93754d4e978c2747747031a4
2 N16764fe472f3441e921fd79b8a02bbaf
3 N194e0f76823f4dc493e90ea7d3549b9d
4 N3108a66aee6c4ae6a0648499590c0dd1
5 N326f17491370452db9ca38132ed11ae2
6 N415cd5a291a54d8fb722f5a6664a403a
7 N45c799a6cc714cf18de6d7f298a95fe7
8 N4dc3449225d44425a90108f1975066df
9 N5293a73958154f08b1bff0c7afb9546a
10 N648e58ab172a48dca65e5ef85e40b114
11 N67a39bd82aed4bbdbd4cc2a19a300a9c
12 N7278ad8cefc74498a959ae398cfec9f1
13 N7bfe9a635a7246fb9f2408980e7a50fe
14 N7e93e466f8c74bafa71c5c6115319638
15 N87b1d0ca1faa4d8f8b0146c4b4cda538
16 Na06116e81827416da535d32500c10f09
17 Nc4024f06a33e4a14aae73fd95064f13c
18 Nce00b2e336424c4bb7daefffe9a971f4
19 Nf139d6e956914ac29a92ea43ca04b936
20 anzsrc-for:11
21 anzsrc-for:1112
22 schema:author N954fa05506fc48d9aabc58fac5fd5ba6
23 schema:citation sg:pub.10.1007/bf02574479
24 sg:pub.10.1007/bf02574492
25 sg:pub.10.1007/s10434-000-0160-4
26 sg:pub.10.1245/aso.2003.03.055
27 sg:pub.10.1245/s10434-010-1203-0
28 sg:pub.10.1245/s10434-012-2826-0
29 sg:pub.10.1245/s10434-015-4894-4
30 schema:datePublished 2016-08-15
31 schema:datePublishedReg 2016-08-15
32 schema:description BackgroundSentinel lymph node biopsy (SLNB) is recommended for patients with intermediate-thickness melanoma, but the use of SLNB for patients with thick melanoma is debated. This report presents a single-institution study investigating factors predictive of sentinel lymph node (SLN) metastasis and outcome for thick-melanoma patients .MethodsA retrospective review of a single-institution database from 1997 to 2012 identified 147 patients with thick primary cutaneous melanoma (≥4 mm) who had an SLNB. Clinicopathologic characteristics were correlated with nodal status and outcome.ResultsThe median age of the patients was 67 years, and 61.9 % of the patients were men. The median tumor thickness was 5.5 mm, and 54 patients (36.7 %) had a positive SLN. Multivariable analysis showed that only tumor thickness significantly predicted SLN metastasis (odds ratio 1.14; 95 % confidence interval (CI) 1.02–1.28; P = 0.02). The overall median follow-up period was 34.6 months. Overall survival (OS) and melanoma-specific survival (MSS) were significantly worse for the positive versus negative-SLN patients. Multivariable analysis showed that age [hazard ratio (HR) 1.04; 95 % CI 1.01–1.07; P = 0.02] and SLN status (HR 2.24; 95 % CI 1.03–4.88; P = 0.04) significantly predicted OS, whereas only SLN status (HR 3.85; 95 % CI 2.13–6.97; P < 0.01) significantly predicted MSS.ConclusionsTumor thickness predicts SLN status in thick melanomas. Furthermore, SLN status is prognostic for OS and MSS in thick-melanoma patients, with positive-SLN patients having significantly worse OS and MSS. These findings show that SLNB should be recommended for thick-melanoma patients, particularly because detection of SLN metastasis can identify patients for potential systemic therapy and treatment of nodal disease at a microscopic stage.
33 schema:genre article
34 schema:isAccessibleForFree false
35 schema:isPartOf N35ea4401314d44458d5f17391036544f
36 N5d255102fd614f0f9b085ea78c9fde63
37 sg:journal.1105545
38 schema:keywords BackgroundSentinel lymph
39 MethodsA retrospective review
40 SLN
41 SLN metastasis
42 SLN patients
43 SLN status
44 SLNB
45 age
46 analysis
47 biopsy
48 characteristics
49 clinicopathologic characteristics
50 cutaneous melanoma
51 database
52 detection
53 disease
54 factors
55 findings
56 follow
57 intermediate-thickness melanomas
58 lymph
59 lymph node metastasis
60 lymph node status
61 median age
62 median follow
63 median tumor thickness
64 melanoma
65 melanoma-specific survival
66 men
67 metastasis
68 microscopic stages
69 months
70 multivariable analysis
71 nodal disease
72 nodal status
73 node metastasis
74 node status
75 outcomes
76 overall median follow
77 overall survival
78 patients
79 period
80 positive SLN
81 positive SLN patients
82 potential systemic therapy
83 primary cutaneous melanoma
84 prognostic significance
85 report
86 retrospective review
87 review
88 sentinel lymph node metastasis
89 sentinel lymph node status
90 significance
91 single-institution database
92 single-institution study
93 stage
94 status
95 study
96 survival
97 systemic therapy
98 therapy
99 thick melanoma patients
100 thick melanomas
101 thick primary cutaneous melanoma
102 thickness
103 treatment
104 tumor thickness
105 use
106 use of SLNB
107 worse overall survival
108 years
109 schema:name The Prognostic Significance of Sentinel Lymph Node Status for Patients with Thick Melanoma
110 schema:pagination 938-945
111 schema:productId N41621899547243a78080be6fe6fd48e8
112 Nad9af8634f894655b95fc30af34c1b94
113 Nf8e07e514f0a4b108abebd6abfdacedd
114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037963676
115 https://doi.org/10.1245/s10434-016-5502-y
116 schema:sdDatePublished 2022-09-02T16:00
117 schema:sdLicense https://scigraph.springernature.com/explorer/license/
118 schema:sdPublisher N5217010a165a43fe94ceee5f79157918
119 schema:url https://doi.org/10.1245/s10434-016-5502-y
120 sgo:license sg:explorer/license/
121 sgo:sdDataset articles
122 rdf:type schema:ScholarlyArticle
123 N042518effb3a442c8b5bdad82ed4bcce schema:affiliation grid-institutes:grid.47100.32
124 schema:familyName Bello
125 schema:givenName Danielle M.
126 rdf:type schema:Person
127 N06fb3cf054fb4f71a3b11a7bdc7e28e0 rdf:first sg:person.013413612021.89
128 rdf:rest N25db01adf4784532bbcbfdbbf40067a7
129 N0c89990a93754d4e978c2747747031a4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Aged, 80 and over
131 rdf:type schema:DefinedTerm
132 N16764fe472f3441e921fd79b8a02bbaf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Melanoma
134 rdf:type schema:DefinedTerm
135 N194e0f76823f4dc493e90ea7d3549b9d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Female
137 rdf:type schema:DefinedTerm
138 N25db01adf4784532bbcbfdbbf40067a7 rdf:first sg:person.014265505777.28
139 rdf:rest N78c4b1e8efcb4550997c32da4f815a60
140 N3108a66aee6c4ae6a0648499590c0dd1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
141 schema:name Neoplasm Recurrence, Local
142 rdf:type schema:DefinedTerm
143 N326f17491370452db9ca38132ed11ae2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name Aged
145 rdf:type schema:DefinedTerm
146 N35ea4401314d44458d5f17391036544f schema:issueNumber Suppl 5
147 rdf:type schema:PublicationIssue
148 N415cd5a291a54d8fb722f5a6664a403a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
149 schema:name Humans
150 rdf:type schema:DefinedTerm
151 N41621899547243a78080be6fe6fd48e8 schema:name dimensions_id
152 schema:value pub.1037963676
153 rdf:type schema:PropertyValue
154 N45c799a6cc714cf18de6d7f298a95fe7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Middle Aged
156 rdf:type schema:DefinedTerm
157 N4dc3449225d44425a90108f1975066df schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Tumor Burden
159 rdf:type schema:DefinedTerm
160 N5217010a165a43fe94ceee5f79157918 schema:name Springer Nature - SN SciGraph project
161 rdf:type schema:Organization
162 N5293a73958154f08b1bff0c7afb9546a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
163 schema:name Follow-Up Studies
164 rdf:type schema:DefinedTerm
165 N5d255102fd614f0f9b085ea78c9fde63 schema:volumeNumber 23
166 rdf:type schema:PublicationVolume
167 N648e58ab172a48dca65e5ef85e40b114 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name Sentinel Lymph Node Biopsy
169 rdf:type schema:DefinedTerm
170 N67a39bd82aed4bbdbd4cc2a19a300a9c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
171 schema:name Proportional Hazards Models
172 rdf:type schema:DefinedTerm
173 N6db91e2430094fb19079c81066608723 rdf:first sg:person.0607026044.65
174 rdf:rest rdf:nil
175 N7278ad8cefc74498a959ae398cfec9f1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
176 schema:name Retrospective Studies
177 rdf:type schema:DefinedTerm
178 N7552d3cb6691475aa3676a122bf68f9c rdf:first sg:person.0723254444.14
179 rdf:rest Nc7f5bfbe4df34bbb80e121f493a5c3c6
180 N78c4b1e8efcb4550997c32da4f815a60 rdf:first sg:person.01006374045.51
181 rdf:rest Nf45a45e4495b4df3a4dc796721323262
182 N7bfe9a635a7246fb9f2408980e7a50fe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
183 schema:name Age Factors
184 rdf:type schema:DefinedTerm
185 N7e93e466f8c74bafa71c5c6115319638 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
186 schema:name Prognosis
187 rdf:type schema:DefinedTerm
188 N87b1d0ca1faa4d8f8b0146c4b4cda538 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
189 schema:name Sentinel Lymph Node
190 rdf:type schema:DefinedTerm
191 N954fa05506fc48d9aabc58fac5fd5ba6 rdf:first N042518effb3a442c8b5bdad82ed4bcce
192 rdf:rest N7552d3cb6691475aa3676a122bf68f9c
193 Na06116e81827416da535d32500c10f09 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
194 schema:name Lymph Node Excision
195 rdf:type schema:DefinedTerm
196 Nad9af8634f894655b95fc30af34c1b94 schema:name pubmed_id
197 schema:value 27527717
198 rdf:type schema:PropertyValue
199 Nc4024f06a33e4a14aae73fd95064f13c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
200 schema:name Survival Rate
201 rdf:type schema:DefinedTerm
202 Nc7f5bfbe4df34bbb80e121f493a5c3c6 rdf:first sg:person.015414304135.16
203 rdf:rest N06fb3cf054fb4f71a3b11a7bdc7e28e0
204 Nce00b2e336424c4bb7daefffe9a971f4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
205 schema:name Male
206 rdf:type schema:DefinedTerm
207 Nf139d6e956914ac29a92ea43ca04b936 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
208 schema:name Skin Neoplasms
209 rdf:type schema:DefinedTerm
210 Nf45a45e4495b4df3a4dc796721323262 rdf:first sg:person.0757247334.39
211 rdf:rest N6db91e2430094fb19079c81066608723
212 Nf8e07e514f0a4b108abebd6abfdacedd schema:name doi
213 schema:value 10.1245/s10434-016-5502-y
214 rdf:type schema:PropertyValue
215 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
216 schema:name Medical and Health Sciences
217 rdf:type schema:DefinedTerm
218 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
219 schema:name Oncology and Carcinogenesis
220 rdf:type schema:DefinedTerm
221 sg:grant.2411237 http://pending.schema.org/fundedItem sg:pub.10.1245/s10434-016-5502-y
222 rdf:type schema:MonetaryGrant
223 sg:journal.1105545 schema:issn 1068-9265
224 1534-4681
225 schema:name Annals of Surgical Oncology
226 schema:publisher Springer Nature
227 rdf:type schema:Periodical
228 sg:person.01006374045.51 schema:affiliation grid-institutes:grid.47100.32
229 schema:familyName Narayan
230 schema:givenName Deepak
231 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006374045.51
232 rdf:type schema:Person
233 sg:person.013413612021.89 schema:affiliation grid-institutes:grid.47100.32
234 schema:familyName Bulloch
235 schema:givenName Kaleigh
236 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013413612021.89
237 rdf:type schema:Person
238 sg:person.014265505777.28 schema:affiliation grid-institutes:grid.47100.32
239 schema:familyName Ariyan
240 schema:givenName Stephan
241 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014265505777.28
242 rdf:type schema:Person
243 sg:person.015414304135.16 schema:affiliation grid-institutes:grid.47100.32
244 schema:familyName Jackson
245 schema:givenName Laura
246 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015414304135.16
247 rdf:type schema:Person
248 sg:person.0607026044.65 schema:affiliation grid-institutes:grid.47100.32
249 schema:familyName Han
250 schema:givenName Dale
251 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0607026044.65
252 rdf:type schema:Person
253 sg:person.0723254444.14 schema:affiliation grid-institutes:grid.264756.4
254 schema:familyName Han
255 schema:givenName Gang
256 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0723254444.14
257 rdf:type schema:Person
258 sg:person.0757247334.39 schema:affiliation grid-institutes:grid.47100.32
259 schema:familyName Rothberg
260 schema:givenName Bonnie Gould
261 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757247334.39
262 rdf:type schema:Person
263 sg:pub.10.1007/bf02574479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049525477
264 https://doi.org/10.1007/bf02574479
265 rdf:type schema:CreativeWork
266 sg:pub.10.1007/bf02574492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023933653
267 https://doi.org/10.1007/bf02574492
268 rdf:type schema:CreativeWork
269 sg:pub.10.1007/s10434-000-0160-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035530171
270 https://doi.org/10.1007/s10434-000-0160-4
271 rdf:type schema:CreativeWork
272 sg:pub.10.1245/aso.2003.03.055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010115773
273 https://doi.org/10.1245/aso.2003.03.055
274 rdf:type schema:CreativeWork
275 sg:pub.10.1245/s10434-010-1203-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010303932
276 https://doi.org/10.1245/s10434-010-1203-0
277 rdf:type schema:CreativeWork
278 sg:pub.10.1245/s10434-012-2826-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041968267
279 https://doi.org/10.1245/s10434-012-2826-0
280 rdf:type schema:CreativeWork
281 sg:pub.10.1245/s10434-015-4894-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022565055
282 https://doi.org/10.1245/s10434-015-4894-4
283 rdf:type schema:CreativeWork
284 grid-institutes:grid.264756.4 schema:alternateName Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, USA
285 schema:name Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, USA
286 rdf:type schema:Organization
287 grid-institutes:grid.47100.32 schema:alternateName Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
288 Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA
289 Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA
290 schema:name Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
291 Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA
292 Section of Surgical Oncology, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA
293 rdf:type schema:Organization
 




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


...