uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Interobserver Variation among Pathologists and Refinement of Criteria in Distinguishing Separate Primary Tumors from Intrapulmonary Metastases in Lung
Royal Brompton & Harefield Natl Hlth Serv Fdn Tru, London, England.;Imperial Coll, Natl Heart & Lung Inst, London, England..
Univ Colorado, Anschutz Med Campus, Aurora, CO USA..
Royal Brompton & Harefield Natl Hlth Serv Fdn Tru, London, England.;Imperial Coll, Natl Heart & Lung Inst, London, England..
Sullivan Nicolaides Pathol, Taringa, Qld, Australia..
Show others and affiliations
2018 (English)In: Journal of Thoracic Oncology, ISSN 1556-0864, E-ISSN 1556-1380, Vol. 13, no 2, p. 205-217Article in journal (Refereed) Published
Abstract [en]

Multiple tumor nodules are seen with increasing frequency in clinical practice. On the basis of the 2015 WHO classification of lung tumors, we assessed the reproducibility of the comprehensive histologic assessment to distinguish second primary lung cancers (SPLCs) from intrapulmonary metastases (IPMs), looking for the most distinctive histologic features. An international panel of lung pathologists reviewed a scanned sequential cohort of 126 tumors from 48 patients and recorded an agreed set of histologic features, including tumor typing and predominant pattern of adenocarcinoma, thereby opining whether the case was SPLC, IPM, or a combination thereof. Cohen kappa statistics of 0.60 on overall assessment of SPLC or IPM indicated a good agreement. Likewise, there was good agreement (kappa score 0.64, p < 0.0001) between WHO histologic pattern in individual cases and SPLC or IPM status, but the proportions diversified for histologic pattern and SPLC or IPM status (McNemar test, p < 0.0001). The strongest associations for distinguishing between SPLC and IPM were observed for nuclear pleomorphism, cell size, acinus formation, nucleolar size, mitotic rate, nuclear inclusions, intraalveolar clusters, and necrosis. Conversely, the associations for lymphocytosis, mucin content, lepidic growth, vascular invasion, macrophage response, clear cell change, acute inflammation keratinization, and emperipolesis did not reach significance with tumor extent. Comprehensive histologic assessment is recommended for distinguishing SPLC from IPM with good reproducibility among lung pathologists. In addition to main histologic type and predominant patterns of histologic subtypes, nuclear pleomorphism, cell size, acinus formation, nucleolar size, and mitotic rate strongly correlate with pathologic staging status.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE INC , 2018. Vol. 13, no 2, p. 205-217
Keywords [en]
Lung cancer, Pathology, Multiple tumors, Interobserver variation
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:uu:diva-349848DOI: 10.1016/j.jtho.2017.10.019ISI: 000424963400007PubMedID: 29127023OAI: oai:DiVA.org:uu-349848DiVA, id: diva2:1203313
Funder
AstraZenecaAvailable from: 2018-05-03 Created: 2018-05-03 Last updated: 2018-05-03Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Authority records BETA

Botling, Johan

Search in DiVA

By author/editor
Botling, Johan
By organisation
Clinical and experimental pathology
In the same journal
Journal of Thoracic Oncology
Cancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 20 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf