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ONEST (Observers Needed to Evaluate Subjective Tests) Analysis of Stromal Tumour-Infiltrating Lymphocytes (sTILs) in Breast Cancer and Its Limitations
B. Cserni, D. Kilmartin, M. O'Loughlin, X. Andreu, Z. Bagó-Horváth, S. Bianchi, E. Chmielik, P. Figueiredo, G. Floris, MP. Foschini, A. Kovács, P. Heikkilä, J. Kulka, AV. Laenkholm, I. Liepniece-Karele, C. Marchiò, E. Provenzano, P. Regitnig, A....
Status neindexováno Jazyk angličtina Země Švýcarsko
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2010
Free Medical Journals
od 2009
PubMed Central
od 2009
Europe PubMed Central
od 2009
ProQuest Central
od 2009-01-01
Open Access Digital Library
od 2009-01-01
Open Access Digital Library
od 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2009
PubMed
36831541
DOI
10.3390/cancers15041199
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the reliable estimation of inter-observer agreement of TIL categorisation. This has not been explored previously in relation to TILs. ONEST analyses, using an open-source software developed by the first author, were performed on TIL quantification in breast cancers taken from two previous studies. These were one reproducibility study involving 49 breast cancers, 23 in the first circulation and 14 pathologists in the second circulation, and one study involving 100 cases and 9 pathologists. In addition to the estimates of the number of observers required, other factors influencing the results of ONEST were examined. The analyses reveal that between six and nine observers (range 2-11) are most commonly needed to give a robust estimate of reproducibility. In addition, the number and experience of observers, the distribution of values around or away from the extremes, and outliers in the classification also influence the results. Due to the simplicity and the potentially relevant information it may give, we propose ONEST to be a part of new reproducibility analyses.
Department of Clinical Pathology Sahlgrenska University Hospital 41345 Gothenburg Sweden
Department of Medical Physics and Informatics University of Szeged 6720 Szeged Hungary
Department of Medical Sciences University of Turin 10126 Turin Italy
Department of Pathology Bács Kiskun County Teaching Hospital 6000 Kecskemét Hungary
Department of Pathology Helsinki University Central Hospital 00029 Helsinki Finland
Department of Pathology Klinikum Donaustadt 1090 Vienna Austria
Department of Pathology Medical University of Vienna Währinger Gürtel 18 20 1090 Vienna Austria
Department of Pathology School of Medicine University of Patras 26504 Rion Greece
Department of Pathology University of Szeged 6720 Szeged Hungary
Department of Surgical Pathology Zealand University Hospital 4000 Roskilde Denmark
Diagnostic and Research Institute of Pathology Medical University of Graz 8010 Graz Austria
Laboratório de Anatomia Patológica IPO Coimbra 3000 075 Coimbra Portugal
National Institute for Health Research Cambridge Biomedical Research Centre Cambridge CB2 0QQ UK
Pathology Department Atryshealth Co Ltd 08039 Barcelona Spain
Pathology Department Herlev University Hospital DK 2730 Herlev Denmark
School of Medicine University College Dublin D04 V1W8 Dublin Ireland
TNG Technology Consulting GmbH Király u 26 1061 Budapest Hungary
Unit of Pathology Candiolo Cancer Institute FPO IRCCS 10060 Candiolo Italy
Citace poskytuje Crossref.org
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