Early depth of tumor shrinkage and treatment outcomes in non-small cell lung cancer treated using Nivolumab View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04-01

AUTHORS

Hayato Kawachi, Daichi Fujimoto, Takeshi Morimoto, Kazutaka Hosoya, Yuki Sato, Mariko Kogo, Kazuma Nagata, Atsushi Nakagawa, Ryo Tachikawa, Keisuke Tomii

ABSTRACT

Background It would be useful to have criteria for predicting long-term treatment responses to immune checkpoint inhibitors (ICIs). Maximum depth of response correlates with treatment outcomes among patients receiving programmed death protein 1 axis inhibitors for non-small cell lung cancer (NSCLC). We investigated associations between early depth of response and survival outcomes among patients receiving nivolumab for NSCLC. Methods Using records from prospective observational cohorts, we identified 83 previously treated advanced patients with NSCLC who received nivolumab during 2016–2017. Thirty-one patients who achieved disease control were analyzed. Tumor assessments followed the Response Evaluation Criteria in Solid Tumors (RECIST). Using Kaplan-Meier and receiver operating characteristic (ROC) curve analyses, treatment outcomes were compared with percent tumor reductions from baseline to the first evaluation (8–12 weeks after starting nivolumab). Results Early depth of response was predictive of 6-month progression-free survival (area under the ROC curve, 0.848). Based on ROC results, early tumor shrinkage was defined as a > 10% reduction by the first evaluation. Early tumor shrinkage was associated with significantly longer median progression-free survival (early tumor shrinkage: 16.6 months, 95% confidence interval [CI] 8.5 months–not reached; no early shrinkage: 5.1 months, 95% CI 3.9–6.8 months; P < 0.001) and significantly longer median overall survival (P = 0.046). Conclusions Early depth of tumor shrinkage was associated with outcomes after ICI treatment. Because of its simplicity and predictive ability, early tumor shrinkage may be a promising factor for use in clinical settings. However, confirmation of our results is needed. More... »

PAGES

1257-1265

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10637-019-00770-y

DOI

http://dx.doi.org/10.1007/s10637-019-00770-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113177740

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30937690


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": "Antineoplastic Agents, Immunological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Carcinoma, Non-Small-Cell Lung", 
        "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": "Kaplan-Meier Estimate", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lung Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Nivolumab", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "ROC Curve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Response Evaluation Criteria in Solid Tumors", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kawachi", 
        "givenName": "Hayato", 
        "id": "sg:person.011470522113.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011470522113.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fujimoto", 
        "givenName": "Daichi", 
        "id": "sg:person.0752614316.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752614316.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Clinical Epidemiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, 663-8131, Nishinomiya, Japan", 
          "id": "http://www.grid.ac/institutes/grid.272264.7", 
          "name": [
            "Clinical Research Center, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
            "Department of Clinical Epidemiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, 663-8131, Nishinomiya, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Morimoto", 
        "givenName": "Takeshi", 
        "id": "sg:person.011273662612.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011273662612.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hosoya", 
        "givenName": "Kazutaka", 
        "id": "sg:person.016016734267.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016016734267.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sato", 
        "givenName": "Yuki", 
        "id": "sg:person.01044701724.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044701724.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kogo", 
        "givenName": "Mariko", 
        "id": "sg:person.0624576212.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624576212.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nagata", 
        "givenName": "Kazuma", 
        "id": "sg:person.01300361475.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01300361475.63"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakagawa", 
        "givenName": "Atsushi", 
        "id": "sg:person.011042354025.34", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011042354025.34"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tachikawa", 
        "givenName": "Ryo", 
        "id": "sg:person.0655423507.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655423507.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410843.a", 
          "name": [
            "Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tomii", 
        "givenName": "Keisuke", 
        "id": "sg:person.01340443712.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01340443712.07"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2019-04-01", 
    "datePublishedReg": "2019-04-01", 
    "description": "Background It would be useful to have criteria for predicting long-term treatment responses to immune checkpoint inhibitors (ICIs). Maximum depth of response correlates with treatment outcomes among patients receiving programmed death protein 1 axis inhibitors for non-small cell lung cancer (NSCLC). We investigated associations between early depth of response and survival outcomes among patients receiving nivolumab for NSCLC. Methods Using records from prospective observational cohorts, we identified 83 previously treated advanced patients with NSCLC who received nivolumab during 2016\u20132017. Thirty-one patients who achieved disease control were analyzed. Tumor assessments followed the Response Evaluation Criteria in Solid Tumors (RECIST). Using Kaplan-Meier and receiver operating characteristic (ROC) curve analyses, treatment outcomes were compared with percent tumor reductions from baseline to the first evaluation (8\u201312\u00a0weeks after starting nivolumab). Results Early depth of response was predictive of 6-month progression-free survival (area under the ROC curve, 0.848). Based on ROC results, early tumor shrinkage was defined as a\u2009>\u200910% reduction by the first evaluation. Early tumor shrinkage was associated with significantly longer median progression-free survival (early tumor shrinkage: 16.6\u00a0months, 95% confidence interval [CI] 8.5\u00a0months\u2013not reached; no early shrinkage: 5.1\u00a0months, 95% CI 3.9\u20136.8\u00a0months; P\u2009<\u20090.001) and significantly longer median overall survival (P\u2009=\u20090.046). Conclusions Early depth of tumor shrinkage was associated with outcomes after ICI treatment. Because of its simplicity and predictive ability, early tumor shrinkage may be a promising factor for use in clinical settings. However, confirmation of our results is needed.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s10637-019-00770-y", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1094201", 
        "issn": [
          "0167-6997", 
          "1573-0646"
        ], 
        "name": "Investigational New Drugs", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "37"
      }
    ], 
    "keywords": [
      "non-small cell lung cancer", 
      "early tumor shrinkage", 
      "immune checkpoint inhibitors", 
      "progression-free survival", 
      "cell lung cancer", 
      "tumor shrinkage", 
      "treatment outcomes", 
      "lung cancer", 
      "longer median progression-free survival", 
      "median progression-free survival", 
      "longer median overall survival", 
      "long-term treatment response", 
      "prospective observational cohort", 
      "median overall survival", 
      "Response Evaluation Criteria", 
      "characteristic curve analysis", 
      "checkpoint inhibitors", 
      "ICI treatment", 
      "observational cohort", 
      "advanced patients", 
      "overall survival", 
      "survival outcomes", 
      "Kaplan-Meier", 
      "tumor reduction", 
      "treatment response", 
      "tumor assessment", 
      "solid tumors", 
      "earlier depth", 
      "patients", 
      "first evaluation", 
      "nivolumab", 
      "response correlates", 
      "clinical setting", 
      "disease control", 
      "curve analysis", 
      "outcomes", 
      "survival", 
      "ROC results", 
      "cancer", 
      "promising factor", 
      "inhibitors", 
      "response", 
      "cohort", 
      "tumors", 
      "predictive ability", 
      "baseline", 
      "treatment", 
      "criteria", 
      "evaluation", 
      "association", 
      "correlates", 
      "reduction", 
      "evaluation criteria", 
      "confirmation", 
      "setting", 
      "assessment", 
      "factors", 
      "records", 
      "control", 
      "background", 
      "shrinkage", 
      "results", 
      "use", 
      "ability", 
      "receiver", 
      "analysis", 
      "method", 
      "depth", 
      "maximum depth", 
      "simplicity"
    ], 
    "name": "Early depth of tumor shrinkage and treatment outcomes in non-small cell lung cancer treated using Nivolumab", 
    "pagination": "1257-1265", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113177740"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10637-019-00770-y"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30937690"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10637-019-00770-y", 
      "https://app.dimensions.ai/details/publication/pub.1113177740"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-11-24T21:05", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/article/article_809.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s10637-019-00770-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.10.1007/s10637-019-00770-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.10.1007/s10637-019-00770-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10637-019-00770-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10637-019-00770-y'


 

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

254 TRIPLES      20 PREDICATES      109 URIs      101 LITERALS      21 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10637-019-00770-y schema:about N0435ea43ab1b46e79174fbc9b03a46e1
2 N3358e3ddae84462bb4321a5634e59df9
3 N36935f69e97342bfa8428306dd988f91
4 N43554ff2e0134b1286d47c2c88dffaca
5 N4a4b53592b1a4c74825117311fd89a4b
6 N63bff75994114f2a9856056103a97f17
7 N6d8d4a7853ad408eb2987eec32d70f83
8 N75156ce3701841c6a70259876973b5a0
9 N9129454ac2d14791b8b764f11c53323f
10 Nbd60fb29894844d7a327624816614ec2
11 Nbdc9f765d80847a2956dc56ae7dc99b2
12 Nea49215c534a4b1382fdff5d1ed2087c
13 Neb9530acf58246edae2377624fb1fdac
14 Neeacd49c709d44f7bf0927baee60efd4
15 anzsrc-for:11
16 anzsrc-for:1112
17 schema:author N007ab38f2e1a4547b54dc8eb978bdaf5
18 schema:datePublished 2019-04-01
19 schema:datePublishedReg 2019-04-01
20 schema:description Background It would be useful to have criteria for predicting long-term treatment responses to immune checkpoint inhibitors (ICIs). Maximum depth of response correlates with treatment outcomes among patients receiving programmed death protein 1 axis inhibitors for non-small cell lung cancer (NSCLC). We investigated associations between early depth of response and survival outcomes among patients receiving nivolumab for NSCLC. Methods Using records from prospective observational cohorts, we identified 83 previously treated advanced patients with NSCLC who received nivolumab during 2016–2017. Thirty-one patients who achieved disease control were analyzed. Tumor assessments followed the Response Evaluation Criteria in Solid Tumors (RECIST). Using Kaplan-Meier and receiver operating characteristic (ROC) curve analyses, treatment outcomes were compared with percent tumor reductions from baseline to the first evaluation (8–12 weeks after starting nivolumab). Results Early depth of response was predictive of 6-month progression-free survival (area under the ROC curve, 0.848). Based on ROC results, early tumor shrinkage was defined as a > 10% reduction by the first evaluation. Early tumor shrinkage was associated with significantly longer median progression-free survival (early tumor shrinkage: 16.6 months, 95% confidence interval [CI] 8.5 months–not reached; no early shrinkage: 5.1 months, 95% CI 3.9–6.8 months; P < 0.001) and significantly longer median overall survival (P = 0.046). Conclusions Early depth of tumor shrinkage was associated with outcomes after ICI treatment. Because of its simplicity and predictive ability, early tumor shrinkage may be a promising factor for use in clinical settings. However, confirmation of our results is needed.
21 schema:genre article
22 schema:isAccessibleForFree false
23 schema:isPartOf N81f324cc41924d249866138a3d1fa8b3
24 N8ee3aba107a44332a876e1bb6f46565a
25 sg:journal.1094201
26 schema:keywords ICI treatment
27 Kaplan-Meier
28 ROC results
29 Response Evaluation Criteria
30 ability
31 advanced patients
32 analysis
33 assessment
34 association
35 background
36 baseline
37 cancer
38 cell lung cancer
39 characteristic curve analysis
40 checkpoint inhibitors
41 clinical setting
42 cohort
43 confirmation
44 control
45 correlates
46 criteria
47 curve analysis
48 depth
49 disease control
50 earlier depth
51 early tumor shrinkage
52 evaluation
53 evaluation criteria
54 factors
55 first evaluation
56 immune checkpoint inhibitors
57 inhibitors
58 long-term treatment response
59 longer median overall survival
60 longer median progression-free survival
61 lung cancer
62 maximum depth
63 median overall survival
64 median progression-free survival
65 method
66 nivolumab
67 non-small cell lung cancer
68 observational cohort
69 outcomes
70 overall survival
71 patients
72 predictive ability
73 progression-free survival
74 promising factor
75 prospective observational cohort
76 receiver
77 records
78 reduction
79 response
80 response correlates
81 results
82 setting
83 shrinkage
84 simplicity
85 solid tumors
86 survival
87 survival outcomes
88 treatment
89 treatment outcomes
90 treatment response
91 tumor assessment
92 tumor reduction
93 tumor shrinkage
94 tumors
95 use
96 schema:name Early depth of tumor shrinkage and treatment outcomes in non-small cell lung cancer treated using Nivolumab
97 schema:pagination 1257-1265
98 schema:productId Naedfc44e68134aaea7722a202eea3012
99 Nb37d0fd467764195bee2dc5b7da14c50
100 Nc0cad47e8ccb46c9ba05742bfeff308e
101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113177740
102 https://doi.org/10.1007/s10637-019-00770-y
103 schema:sdDatePublished 2022-11-24T21:05
104 schema:sdLicense https://scigraph.springernature.com/explorer/license/
105 schema:sdPublisher N3181aa56c0e74a46ba3a568c90227fa7
106 schema:url https://doi.org/10.1007/s10637-019-00770-y
107 sgo:license sg:explorer/license/
108 sgo:sdDataset articles
109 rdf:type schema:ScholarlyArticle
110 N007ab38f2e1a4547b54dc8eb978bdaf5 rdf:first sg:person.011470522113.61
111 rdf:rest Ne2817274fdf24cef96adcaa936686689
112 N0435ea43ab1b46e79174fbc9b03a46e1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Antineoplastic Agents, Immunological
114 rdf:type schema:DefinedTerm
115 N04e71758534244d1951e45f135df82b2 rdf:first sg:person.01300361475.63
116 rdf:rest N31e5cd3436804e42b994e4e6d9fc58da
117 N0b38e86c9a2f46b8947d11950342e5a3 rdf:first sg:person.01340443712.07
118 rdf:rest rdf:nil
119 N0b3ef2e18a5e4c5fb8cf77bfd8cc92a2 rdf:first sg:person.0655423507.20
120 rdf:rest N0b38e86c9a2f46b8947d11950342e5a3
121 N3181aa56c0e74a46ba3a568c90227fa7 schema:name Springer Nature - SN SciGraph project
122 rdf:type schema:Organization
123 N31e5cd3436804e42b994e4e6d9fc58da rdf:first sg:person.011042354025.34
124 rdf:rest N0b3ef2e18a5e4c5fb8cf77bfd8cc92a2
125 N3358e3ddae84462bb4321a5634e59df9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name ROC Curve
127 rdf:type schema:DefinedTerm
128 N36935f69e97342bfa8428306dd988f91 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Lung Neoplasms
130 rdf:type schema:DefinedTerm
131 N43554ff2e0134b1286d47c2c88dffaca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Nivolumab
133 rdf:type schema:DefinedTerm
134 N4a4b53592b1a4c74825117311fd89a4b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Humans
136 rdf:type schema:DefinedTerm
137 N594f7f0078d84588ae8d0a4f5a35b5d3 rdf:first sg:person.011273662612.03
138 rdf:rest Nebb3c15b72c34ee48c55e72d32998a65
139 N5a4824eb3e3a4a1a90f9a277873b0ca1 rdf:first sg:person.01044701724.61
140 rdf:rest N7f6f9da4681c4eada052ad2c1c2df877
141 N63bff75994114f2a9856056103a97f17 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Adult
143 rdf:type schema:DefinedTerm
144 N6d8d4a7853ad408eb2987eec32d70f83 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Aged
146 rdf:type schema:DefinedTerm
147 N75156ce3701841c6a70259876973b5a0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Female
149 rdf:type schema:DefinedTerm
150 N7f6f9da4681c4eada052ad2c1c2df877 rdf:first sg:person.0624576212.46
151 rdf:rest N04e71758534244d1951e45f135df82b2
152 N81f324cc41924d249866138a3d1fa8b3 schema:volumeNumber 37
153 rdf:type schema:PublicationVolume
154 N8ee3aba107a44332a876e1bb6f46565a schema:issueNumber 6
155 rdf:type schema:PublicationIssue
156 N9129454ac2d14791b8b764f11c53323f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
157 schema:name Aged, 80 and over
158 rdf:type schema:DefinedTerm
159 Naedfc44e68134aaea7722a202eea3012 schema:name dimensions_id
160 schema:value pub.1113177740
161 rdf:type schema:PropertyValue
162 Nb37d0fd467764195bee2dc5b7da14c50 schema:name pubmed_id
163 schema:value 30937690
164 rdf:type schema:PropertyValue
165 Nbd60fb29894844d7a327624816614ec2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
166 schema:name Middle Aged
167 rdf:type schema:DefinedTerm
168 Nbdc9f765d80847a2956dc56ae7dc99b2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
169 schema:name Response Evaluation Criteria in Solid Tumors
170 rdf:type schema:DefinedTerm
171 Nc0cad47e8ccb46c9ba05742bfeff308e schema:name doi
172 schema:value 10.1007/s10637-019-00770-y
173 rdf:type schema:PropertyValue
174 Ne2817274fdf24cef96adcaa936686689 rdf:first sg:person.0752614316.52
175 rdf:rest N594f7f0078d84588ae8d0a4f5a35b5d3
176 Nea49215c534a4b1382fdff5d1ed2087c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
177 schema:name Kaplan-Meier Estimate
178 rdf:type schema:DefinedTerm
179 Neb9530acf58246edae2377624fb1fdac schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
180 schema:name Male
181 rdf:type schema:DefinedTerm
182 Nebb3c15b72c34ee48c55e72d32998a65 rdf:first sg:person.016016734267.92
183 rdf:rest N5a4824eb3e3a4a1a90f9a277873b0ca1
184 Neeacd49c709d44f7bf0927baee60efd4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
185 schema:name Carcinoma, Non-Small-Cell Lung
186 rdf:type schema:DefinedTerm
187 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
188 schema:name Medical and Health Sciences
189 rdf:type schema:DefinedTerm
190 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
191 schema:name Oncology and Carcinogenesis
192 rdf:type schema:DefinedTerm
193 sg:journal.1094201 schema:issn 0167-6997
194 1573-0646
195 schema:name Investigational New Drugs
196 schema:publisher Springer Nature
197 rdf:type schema:Periodical
198 sg:person.01044701724.61 schema:affiliation grid-institutes:grid.410843.a
199 schema:familyName Sato
200 schema:givenName Yuki
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044701724.61
202 rdf:type schema:Person
203 sg:person.011042354025.34 schema:affiliation grid-institutes:grid.410843.a
204 schema:familyName Nakagawa
205 schema:givenName Atsushi
206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011042354025.34
207 rdf:type schema:Person
208 sg:person.011273662612.03 schema:affiliation grid-institutes:grid.272264.7
209 schema:familyName Morimoto
210 schema:givenName Takeshi
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011273662612.03
212 rdf:type schema:Person
213 sg:person.011470522113.61 schema:affiliation grid-institutes:grid.410843.a
214 schema:familyName Kawachi
215 schema:givenName Hayato
216 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011470522113.61
217 rdf:type schema:Person
218 sg:person.01300361475.63 schema:affiliation grid-institutes:grid.410843.a
219 schema:familyName Nagata
220 schema:givenName Kazuma
221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01300361475.63
222 rdf:type schema:Person
223 sg:person.01340443712.07 schema:affiliation grid-institutes:grid.410843.a
224 schema:familyName Tomii
225 schema:givenName Keisuke
226 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01340443712.07
227 rdf:type schema:Person
228 sg:person.016016734267.92 schema:affiliation grid-institutes:grid.410843.a
229 schema:familyName Hosoya
230 schema:givenName Kazutaka
231 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016016734267.92
232 rdf:type schema:Person
233 sg:person.0624576212.46 schema:affiliation grid-institutes:grid.410843.a
234 schema:familyName Kogo
235 schema:givenName Mariko
236 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624576212.46
237 rdf:type schema:Person
238 sg:person.0655423507.20 schema:affiliation grid-institutes:grid.410843.a
239 schema:familyName Tachikawa
240 schema:givenName Ryo
241 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655423507.20
242 rdf:type schema:Person
243 sg:person.0752614316.52 schema:affiliation grid-institutes:grid.410843.a
244 schema:familyName Fujimoto
245 schema:givenName Daichi
246 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752614316.52
247 rdf:type schema:Person
248 grid-institutes:grid.272264.7 schema:alternateName Department of Clinical Epidemiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, 663-8131, Nishinomiya, Japan
249 schema:name Clinical Research Center, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan
250 Department of Clinical Epidemiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, 663-8131, Nishinomiya, Japan
251 rdf:type schema:Organization
252 grid-institutes:grid.410843.a schema:alternateName Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan
253 schema:name Department of Respiratory Medicine, Kobe City Medical Center General Hospital, 2-1-1 Minatojima-Minamimachi, Chuo-ku, 650-0047, Kobe, Japan
254 rdf:type schema:Organization
 




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


...