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Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer

BACKGROUND: Numerous studies indicate that higher tumour programmed cell death ligand-1 (PD-L1) expression is associated with greater response to anti-programmed cell death-1 (PD-1)/PD-L1 immunotherapy in non-small cell lung cancer (NSCLC). In the era of precision medicine, there is a need to provid...

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Autores principales: Jasani, Bharat, Bänfer, Gudrun, Fish, Rebecca, Waelput, Wim, Sucaet, Yves, Barker, Craig, Whiteley, Jessica L., Walker, Jill, Hovelinck, Rudy, Diezko, Rolf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164334/
https://www.ncbi.nlm.nih.gov/pubmed/32303234
http://dx.doi.org/10.1186/s13000-020-00953-9
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author Jasani, Bharat
Bänfer, Gudrun
Fish, Rebecca
Waelput, Wim
Sucaet, Yves
Barker, Craig
Whiteley, Jessica L.
Walker, Jill
Hovelinck, Rudy
Diezko, Rolf
author_facet Jasani, Bharat
Bänfer, Gudrun
Fish, Rebecca
Waelput, Wim
Sucaet, Yves
Barker, Craig
Whiteley, Jessica L.
Walker, Jill
Hovelinck, Rudy
Diezko, Rolf
author_sort Jasani, Bharat
collection PubMed
description BACKGROUND: Numerous studies indicate that higher tumour programmed cell death ligand-1 (PD-L1) expression is associated with greater response to anti-programmed cell death-1 (PD-1)/PD-L1 immunotherapy in non-small cell lung cancer (NSCLC). In the era of precision medicine, there is a need to provide reliable, standardised training for pathologists to improve their accuracy of interpretation and scoring, as the results are used directly to inform clinical decisions. Here we present findings regarding reader reproducibility of PD-L1 tumour cell (TC) staining scoring for NSCLC using a PD-L1 e-trainer tool as part of a PD-L1 immunohistochemistry reader training course. METHODS: The PD-L1 training course was developed based on the use of VENTANA PD-L1 (SP263) and Dako PD-L1 IHC PharmDx 22C3 stained NSCLC samples in combination with a PD-L1 e-trainer tool. Five-hundred formalin-fixed, paraffin-embedded archival samples were obtained from commercial sources and stained for PD-L1. Slides were scored by two expert pathologists, then scanned to produce digital images and re-scored. Thirty-three cases were selected and sorted into three sets: a training set and two self-assessment tests (pre-test and ‘competence’ test). Participants (all selected board-certified pathologists) received face-to-face training including use of an e-trainer tool. Statistical analyses were performed using the competence test set. Overall percentage agreement (OPA) was assessed between the participant pathologists’ registered scores and the reference scores assigned by expert pathologists at clinically relevant PD-L1 cut-offs (≥1%, ≥25% and ≥ 50%). RESULTS: Seven sessions were held and 69 participant pathologists completed the training. Inter-reader concordance indicated high OPA (85–95%) for PD-L1 TC scoring at clinically relevant cut-offs, with Fleiss’ Kappa > 0.5. CONCLUSIONS: Use of this web-based training tool incorporated into classroom-style training was associated with an overall moderately good level of inter-reader reproducibility at key cut-offs for TC PD-L1 expression testing in NSCLC. Overall, the online training tool offers a means of standardised training for practising pathologists in a clinical setting.
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spelling pubmed-71643342020-04-22 Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer Jasani, Bharat Bänfer, Gudrun Fish, Rebecca Waelput, Wim Sucaet, Yves Barker, Craig Whiteley, Jessica L. Walker, Jill Hovelinck, Rudy Diezko, Rolf Diagn Pathol Research BACKGROUND: Numerous studies indicate that higher tumour programmed cell death ligand-1 (PD-L1) expression is associated with greater response to anti-programmed cell death-1 (PD-1)/PD-L1 immunotherapy in non-small cell lung cancer (NSCLC). In the era of precision medicine, there is a need to provide reliable, standardised training for pathologists to improve their accuracy of interpretation and scoring, as the results are used directly to inform clinical decisions. Here we present findings regarding reader reproducibility of PD-L1 tumour cell (TC) staining scoring for NSCLC using a PD-L1 e-trainer tool as part of a PD-L1 immunohistochemistry reader training course. METHODS: The PD-L1 training course was developed based on the use of VENTANA PD-L1 (SP263) and Dako PD-L1 IHC PharmDx 22C3 stained NSCLC samples in combination with a PD-L1 e-trainer tool. Five-hundred formalin-fixed, paraffin-embedded archival samples were obtained from commercial sources and stained for PD-L1. Slides were scored by two expert pathologists, then scanned to produce digital images and re-scored. Thirty-three cases were selected and sorted into three sets: a training set and two self-assessment tests (pre-test and ‘competence’ test). Participants (all selected board-certified pathologists) received face-to-face training including use of an e-trainer tool. Statistical analyses were performed using the competence test set. Overall percentage agreement (OPA) was assessed between the participant pathologists’ registered scores and the reference scores assigned by expert pathologists at clinically relevant PD-L1 cut-offs (≥1%, ≥25% and ≥ 50%). RESULTS: Seven sessions were held and 69 participant pathologists completed the training. Inter-reader concordance indicated high OPA (85–95%) for PD-L1 TC scoring at clinically relevant cut-offs, with Fleiss’ Kappa > 0.5. CONCLUSIONS: Use of this web-based training tool incorporated into classroom-style training was associated with an overall moderately good level of inter-reader reproducibility at key cut-offs for TC PD-L1 expression testing in NSCLC. Overall, the online training tool offers a means of standardised training for practising pathologists in a clinical setting. BioMed Central 2020-04-17 /pmc/articles/PMC7164334/ /pubmed/32303234 http://dx.doi.org/10.1186/s13000-020-00953-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jasani, Bharat
Bänfer, Gudrun
Fish, Rebecca
Waelput, Wim
Sucaet, Yves
Barker, Craig
Whiteley, Jessica L.
Walker, Jill
Hovelinck, Rudy
Diezko, Rolf
Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title_full Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title_fullStr Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title_full_unstemmed Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title_short Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer
title_sort evaluation of an online training tool for scoring programmed cell death ligand-1 (pd-l1) diagnostic tests for lung cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164334/
https://www.ncbi.nlm.nih.gov/pubmed/32303234
http://dx.doi.org/10.1186/s13000-020-00953-9
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