Modified geriatric nutrition risk index as a prognostic predictor of esophageal cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2020-11-10

AUTHORS

Keita Kouzu, Hironori Tsujimoto, Hidekazu Sugasawa, Yusuke Ishibashi, Kazuo Hase, Yoji Kishi, Hideki Ueno

ABSTRACT

BackgroundThis study aimed to establish a simple and useful prognostic indicator for elderly esophageal cancer patients. We designed the modified geriatric nutrition risk index (mGNRI) using the inverse of C-reactive protein (CRP) instead of albumin and compared its prognostic value with those of the GNRI and other indices.MethodsWe included 128 patients aged > 65 years who underwent esophagectomy for esophageal cancer. We defined mGNRI as (1.489/CRP in mg/dL) + (41.7 × present/ideal body weight) and divided patients into two groups: the low-mGNRI (mGNRI < 70, n = 50) and high-mGNRI (mGNRI ≥ 70, n = 78) groups. We retrospectively examined the relationship between mGNRI and long-term prognosis.ResultsThe low-mGNRI group had more advanced cancer by stage, higher rates of recurrence, and earlier recurrence than the high-mGNRI group. Univariate analysis identified the following factors as significantly associated with poor overall survival (OS): a lower American society of anesthesiologist performance status (ASA-PS), male gender, CRP-albumin ratio ≥ 0.1, CRP ≥ 1.0, low-mGNRI, tumor depth ≥ T3, Charlson comorbidity index ≥ 2, tumor size ≥ 40 mm, and age > 75 years. A low-mGNRI, ASA-PS 3, age > 75 years, and tumor depth ≥ T3 were independent unfavorable prognostic factors for OS. A low-mGNRI was an independent poor prognostic factor for relapse-free survival. We performed model selection analysis to identify the most clinically useful indices; mGNRI was the best predictive model.ConclusionmGNRI in patients with esophageal cancer correlated with early recurrence and was a useful independent prognostic factor. More... »

PAGES

278-287

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10388-020-00795-w

DOI

http://dx.doi.org/10.1007/s10388-020-00795-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1132476779

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33170460


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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kouzu", 
        "givenName": "Keita", 
        "id": "sg:person.01006713465.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006713465.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsujimoto", 
        "givenName": "Hironori", 
        "id": "sg:person.01022371461.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01022371461.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sugasawa", 
        "givenName": "Hidekazu", 
        "id": "sg:person.01357636001.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01357636001.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ishibashi", 
        "givenName": "Yusuke", 
        "id": "sg:person.0672465065.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0672465065.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hase", 
        "givenName": "Kazuo", 
        "id": "sg:person.01251324614.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01251324614.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kishi", 
        "givenName": "Yoji", 
        "id": "sg:person.0651772025.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651772025.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ueno", 
        "givenName": "Hideki", 
        "id": "sg:person.01053200431.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053200431.41"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s10388-018-0644-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107553119", 
          "https://doi.org/10.1007/s10388-018-0644-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00268-004-7205-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045424510", 
          "https://doi.org/10.1007/s00268-004-7205-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ejcn.1601208", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043237609", 
          "https://doi.org/10.1038/sj.ejcn.1601208"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature07205", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024729982", 
          "https://doi.org/10.1038/nature07205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10147-016-0994-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051540543", 
          "https://doi.org/10.1007/s10147-016-0994-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10120-010-0568-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028038438", 
          "https://doi.org/10.1007/s10120-010-0568-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1245/s10434-006-9093-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029936937", 
          "https://doi.org/10.1245/s10434-006-9093-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00384-006-0259-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046118686", 
          "https://doi.org/10.1007/s00384-006-0259-6"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2020-11-10", 
    "datePublishedReg": "2020-11-10", 
    "description": "BackgroundThis study aimed to establish a simple and useful prognostic indicator for elderly esophageal cancer patients. We designed the modified geriatric nutrition risk index (mGNRI) using the inverse of C-reactive protein (CRP) instead of albumin and compared its prognostic value with those of the GNRI and other indices.MethodsWe included 128 patients aged\u2009>\u200965\u00a0years who underwent esophagectomy for esophageal cancer. We defined mGNRI as (1.489/CRP in mg/dL)\u2009+\u2009(41.7\u2009\u00d7\u2009present/ideal body weight) and divided patients into two groups: the low-mGNRI (mGNRI\u2009<\u200970, n\u2009=\u200950) and high-mGNRI (mGNRI\u2009\u2265\u200970, n\u2009=\u200978) groups. We retrospectively examined the relationship between mGNRI and long-term prognosis.ResultsThe low-mGNRI group had more advanced cancer by stage, higher rates of recurrence, and earlier recurrence than the high-mGNRI group. Univariate analysis identified the following factors as significantly associated with poor overall survival (OS): a lower American society of anesthesiologist performance status (ASA-PS), male gender, CRP-albumin ratio\u2009\u2265\u20090.1, CRP\u2009\u2265\u20091.0, low-mGNRI, tumor depth\u2009\u2265\u2009T3, Charlson comorbidity index\u2009\u2265\u20092, tumor size\u2009\u2265\u200940\u00a0mm, and age\u2009>\u200975\u00a0years. A low-mGNRI, ASA-PS 3, age\u2009>\u200975\u00a0years, and tumor depth\u2009\u2265\u2009T3 were independent unfavorable prognostic factors for OS. A low-mGNRI was an independent poor prognostic factor for relapse-free survival. We performed model selection analysis to identify the most clinically useful indices; mGNRI was the best predictive model.ConclusionmGNRI in patients with esophageal cancer correlated with early recurrence and was a useful independent prognostic factor.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s10388-020-00795-w", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1033355", 
        "issn": [
          "1612-9059", 
          "1612-9067"
        ], 
        "name": "Esophagus", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "keywords": [
      "Geriatric Nutrition Risk Index", 
      "Nutrition Risk Index", 
      "overall survival", 
      "prognostic factors", 
      "esophageal cancer", 
      "early recurrence", 
      "tumor depth", 
      "elderly esophageal cancer patients", 
      "useful independent prognostic factor", 
      "independent unfavorable prognostic factor", 
      "independent poor prognostic factor", 
      "Anesthesiologists performance status", 
      "CRP-albumin ratio", 
      "Charlson Comorbidity Index", 
      "ASA-PS 3", 
      "poor prognostic factor", 
      "long-term prognosis", 
      "unfavorable prognostic factor", 
      "relapse-free survival", 
      "independent prognostic factor", 
      "useful prognostic indicator", 
      "esophageal cancer patients", 
      "poor overall survival", 
      "lower American Society", 
      "comorbidity index", 
      "performance status", 
      "reactive protein", 
      "advanced cancer", 
      "prognostic predictor", 
      "prognostic value", 
      "tumor size", 
      "prognostic indicator", 
      "cancer patients", 
      "male gender", 
      "BackgroundThis study", 
      "patients", 
      "risk index", 
      "cancer", 
      "recurrence", 
      "American Society", 
      "high rate", 
      "useful index", 
      "survival", 
      "age", 
      "group", 
      "T3", 
      "years", 
      "index", 
      "best predictive model", 
      "esophagectomy", 
      "prognosis", 
      "factors", 
      "CRP", 
      "MethodsWe", 
      "predictors", 
      "albumin", 
      "status", 
      "gender", 
      "predictive model", 
      "study", 
      "protein", 
      "rate", 
      "analysis", 
      "indicators", 
      "stage", 
      "relationship", 
      "ratio", 
      "values", 
      "size", 
      "society", 
      "model", 
      "depth", 
      "model selection analysis", 
      "selection analysis", 
      "inverse", 
      "mGNRI", 
      "mGNRI group", 
      "ConclusionmGNRI"
    ], 
    "name": "Modified geriatric nutrition risk index as a prognostic predictor of esophageal cancer", 
    "pagination": "278-287", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1132476779"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10388-020-00795-w"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33170460"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10388-020-00795-w", 
      "https://app.dimensions.ai/details/publication/pub.1132476779"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:56", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_869.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s10388-020-00795-w"
  }
]
 

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.10.1007/s10388-020-00795-w'

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/s10388-020-00795-w'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10388-020-00795-w'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10388-020-00795-w'


 

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

214 TRIPLES      22 PREDICATES      112 URIs      96 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10388-020-00795-w schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author N1f9136dc9fc7415780e0b09aa016f680
4 schema:citation sg:pub.10.1007/s00268-004-7205-y
5 sg:pub.10.1007/s00384-006-0259-6
6 sg:pub.10.1007/s10120-010-0568-x
7 sg:pub.10.1007/s10147-016-0994-9
8 sg:pub.10.1007/s10388-018-0644-6
9 sg:pub.10.1038/nature07205
10 sg:pub.10.1038/sj.ejcn.1601208
11 sg:pub.10.1245/s10434-006-9093-x
12 schema:datePublished 2020-11-10
13 schema:datePublishedReg 2020-11-10
14 schema:description BackgroundThis study aimed to establish a simple and useful prognostic indicator for elderly esophageal cancer patients. We designed the modified geriatric nutrition risk index (mGNRI) using the inverse of C-reactive protein (CRP) instead of albumin and compared its prognostic value with those of the GNRI and other indices.MethodsWe included 128 patients aged > 65 years who underwent esophagectomy for esophageal cancer. We defined mGNRI as (1.489/CRP in mg/dL) + (41.7 × present/ideal body weight) and divided patients into two groups: the low-mGNRI (mGNRI < 70, n = 50) and high-mGNRI (mGNRI ≥ 70, n = 78) groups. We retrospectively examined the relationship between mGNRI and long-term prognosis.ResultsThe low-mGNRI group had more advanced cancer by stage, higher rates of recurrence, and earlier recurrence than the high-mGNRI group. Univariate analysis identified the following factors as significantly associated with poor overall survival (OS): a lower American society of anesthesiologist performance status (ASA-PS), male gender, CRP-albumin ratio ≥ 0.1, CRP ≥ 1.0, low-mGNRI, tumor depth ≥ T3, Charlson comorbidity index ≥ 2, tumor size ≥ 40 mm, and age > 75 years. A low-mGNRI, ASA-PS 3, age > 75 years, and tumor depth ≥ T3 were independent unfavorable prognostic factors for OS. A low-mGNRI was an independent poor prognostic factor for relapse-free survival. We performed model selection analysis to identify the most clinically useful indices; mGNRI was the best predictive model.ConclusionmGNRI in patients with esophageal cancer correlated with early recurrence and was a useful independent prognostic factor.
15 schema:genre article
16 schema:inLanguage en
17 schema:isAccessibleForFree false
18 schema:isPartOf N1dff36e59e054b0d9181287563a8b3d2
19 N7a2f21eb1d404ca4b6e3a52973df9807
20 sg:journal.1033355
21 schema:keywords ASA-PS 3
22 American Society
23 Anesthesiologists performance status
24 BackgroundThis study
25 CRP
26 CRP-albumin ratio
27 Charlson Comorbidity Index
28 ConclusionmGNRI
29 Geriatric Nutrition Risk Index
30 MethodsWe
31 Nutrition Risk Index
32 T3
33 advanced cancer
34 age
35 albumin
36 analysis
37 best predictive model
38 cancer
39 cancer patients
40 comorbidity index
41 depth
42 early recurrence
43 elderly esophageal cancer patients
44 esophageal cancer
45 esophageal cancer patients
46 esophagectomy
47 factors
48 gender
49 group
50 high rate
51 independent poor prognostic factor
52 independent prognostic factor
53 independent unfavorable prognostic factor
54 index
55 indicators
56 inverse
57 long-term prognosis
58 lower American Society
59 mGNRI
60 mGNRI group
61 male gender
62 model
63 model selection analysis
64 overall survival
65 patients
66 performance status
67 poor overall survival
68 poor prognostic factor
69 predictive model
70 predictors
71 prognosis
72 prognostic factors
73 prognostic indicator
74 prognostic predictor
75 prognostic value
76 protein
77 rate
78 ratio
79 reactive protein
80 recurrence
81 relapse-free survival
82 relationship
83 risk index
84 selection analysis
85 size
86 society
87 stage
88 status
89 study
90 survival
91 tumor depth
92 tumor size
93 unfavorable prognostic factor
94 useful independent prognostic factor
95 useful index
96 useful prognostic indicator
97 values
98 years
99 schema:name Modified geriatric nutrition risk index as a prognostic predictor of esophageal cancer
100 schema:pagination 278-287
101 schema:productId Nb507465f31eb492d9d229744e42f1794
102 Nc46c9aa9a6444144bbd341c7bc75c377
103 Nda968db6820f4a8e800a96166a85e063
104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1132476779
105 https://doi.org/10.1007/s10388-020-00795-w
106 schema:sdDatePublished 2022-01-01T18:56
107 schema:sdLicense https://scigraph.springernature.com/explorer/license/
108 schema:sdPublisher N3229dffe48e34d4996135196ec2c8463
109 schema:url https://doi.org/10.1007/s10388-020-00795-w
110 sgo:license sg:explorer/license/
111 sgo:sdDataset articles
112 rdf:type schema:ScholarlyArticle
113 N1a88a71bb680416ca1f36f25f38836e1 rdf:first sg:person.01022371461.19
114 rdf:rest N9c32568d2ab24e348818612dfd10871a
115 N1b2a16c5a54d42e29a395c130d349d6d rdf:first sg:person.0651772025.08
116 rdf:rest Na67e26e94c944ba5bed9406be9f6ea43
117 N1dff36e59e054b0d9181287563a8b3d2 schema:issueNumber 2
118 rdf:type schema:PublicationIssue
119 N1f9136dc9fc7415780e0b09aa016f680 rdf:first sg:person.01006713465.24
120 rdf:rest N1a88a71bb680416ca1f36f25f38836e1
121 N2201374793f84820a1b6a0750e3764d2 rdf:first sg:person.0672465065.31
122 rdf:rest Nec530f9b51814e83a684710497e775e3
123 N3229dffe48e34d4996135196ec2c8463 schema:name Springer Nature - SN SciGraph project
124 rdf:type schema:Organization
125 N7a2f21eb1d404ca4b6e3a52973df9807 schema:volumeNumber 18
126 rdf:type schema:PublicationVolume
127 N9c32568d2ab24e348818612dfd10871a rdf:first sg:person.01357636001.44
128 rdf:rest N2201374793f84820a1b6a0750e3764d2
129 Na67e26e94c944ba5bed9406be9f6ea43 rdf:first sg:person.01053200431.41
130 rdf:rest rdf:nil
131 Nb507465f31eb492d9d229744e42f1794 schema:name dimensions_id
132 schema:value pub.1132476779
133 rdf:type schema:PropertyValue
134 Nc46c9aa9a6444144bbd341c7bc75c377 schema:name doi
135 schema:value 10.1007/s10388-020-00795-w
136 rdf:type schema:PropertyValue
137 Nda968db6820f4a8e800a96166a85e063 schema:name pubmed_id
138 schema:value 33170460
139 rdf:type schema:PropertyValue
140 Nec530f9b51814e83a684710497e775e3 rdf:first sg:person.01251324614.42
141 rdf:rest N1b2a16c5a54d42e29a395c130d349d6d
142 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
143 schema:name Medical and Health Sciences
144 rdf:type schema:DefinedTerm
145 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
146 schema:name Oncology and Carcinogenesis
147 rdf:type schema:DefinedTerm
148 sg:journal.1033355 schema:issn 1612-9059
149 1612-9067
150 schema:name Esophagus
151 schema:publisher Springer Nature
152 rdf:type schema:Periodical
153 sg:person.01006713465.24 schema:affiliation grid-institutes:grid.416614.0
154 schema:familyName Kouzu
155 schema:givenName Keita
156 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006713465.24
157 rdf:type schema:Person
158 sg:person.01022371461.19 schema:affiliation grid-institutes:grid.416614.0
159 schema:familyName Tsujimoto
160 schema:givenName Hironori
161 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01022371461.19
162 rdf:type schema:Person
163 sg:person.01053200431.41 schema:affiliation grid-institutes:grid.416614.0
164 schema:familyName Ueno
165 schema:givenName Hideki
166 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053200431.41
167 rdf:type schema:Person
168 sg:person.01251324614.42 schema:affiliation grid-institutes:grid.416614.0
169 schema:familyName Hase
170 schema:givenName Kazuo
171 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01251324614.42
172 rdf:type schema:Person
173 sg:person.01357636001.44 schema:affiliation grid-institutes:grid.416614.0
174 schema:familyName Sugasawa
175 schema:givenName Hidekazu
176 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01357636001.44
177 rdf:type schema:Person
178 sg:person.0651772025.08 schema:affiliation grid-institutes:grid.416614.0
179 schema:familyName Kishi
180 schema:givenName Yoji
181 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651772025.08
182 rdf:type schema:Person
183 sg:person.0672465065.31 schema:affiliation grid-institutes:grid.416614.0
184 schema:familyName Ishibashi
185 schema:givenName Yusuke
186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0672465065.31
187 rdf:type schema:Person
188 sg:pub.10.1007/s00268-004-7205-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1045424510
189 https://doi.org/10.1007/s00268-004-7205-y
190 rdf:type schema:CreativeWork
191 sg:pub.10.1007/s00384-006-0259-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046118686
192 https://doi.org/10.1007/s00384-006-0259-6
193 rdf:type schema:CreativeWork
194 sg:pub.10.1007/s10120-010-0568-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1028038438
195 https://doi.org/10.1007/s10120-010-0568-x
196 rdf:type schema:CreativeWork
197 sg:pub.10.1007/s10147-016-0994-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051540543
198 https://doi.org/10.1007/s10147-016-0994-9
199 rdf:type schema:CreativeWork
200 sg:pub.10.1007/s10388-018-0644-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107553119
201 https://doi.org/10.1007/s10388-018-0644-6
202 rdf:type schema:CreativeWork
203 sg:pub.10.1038/nature07205 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024729982
204 https://doi.org/10.1038/nature07205
205 rdf:type schema:CreativeWork
206 sg:pub.10.1038/sj.ejcn.1601208 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043237609
207 https://doi.org/10.1038/sj.ejcn.1601208
208 rdf:type schema:CreativeWork
209 sg:pub.10.1245/s10434-006-9093-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1029936937
210 https://doi.org/10.1245/s10434-006-9093-x
211 rdf:type schema:CreativeWork
212 grid-institutes:grid.416614.0 schema:alternateName Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan
213 schema:name Department of Surgery, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan
214 rdf:type schema:Organization
 




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


...