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A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer.

Publication ,  Journal Article
Taylor, CR; Jadhav, AP; Gholap, A; Kamble, G; Huang, J; Gown, A; Doshi, I; Rimm, DL
Published in: Appl Immunohistochem Mol Morphol
April 2019

Assessment of programmed death-ligand 1 (PD-L1) expression is a critical part of patient management for immunotherapy. However, studies have shown that pathologist-based analysis lacks reproducibility, especially for immune cell expression. The purpose of this study was to validate reproducibility of the automated machine-based Optra image analysis for PD-L1 immunohistochemistry for both tumor cells (TCs) and immune cells. We compared conventional pathologists' scores for both tumor and immune cell positivity separately using 22c3 antibody on the Dako Link 48 platform for PD-L1 expression in non-small cell lung carcinoma. We assessed interpretation first by pathologists and second by PD-L1 image analysis scores. Lin's concordance correlation coefficients (LCCs) for each pathologist were measured to assess variability between pathologists and between pathologists and Optra automated quantitative scores in scoring both tumor and immune cells. Lin's LCCs to evaluate the correlation between pathologists for TC was 0.75 [95% confidence interval (CI), 0.64-0.81] and 0.40 (95% CI, 0.40-0.62) for immune cell scoring. Pathologists were highly concordant for tumor scoring, but not for immune cell scoring, which is similar to previously reported studies where agreement is higher in TCs than immune cells. The LCCs between conventional pathologists' read and the machine score were 0.80 (95% CI, 0.74-0.85) for TCs and 0.70 (95% CI, 0.60-0.76) for immune cell population. This is considered excellent agreement for TCs and good concordance for immune cells. The automated scoring methods showed concordance with the pathologists' average scores that were comparable to interpathologist scores. This suggests promise for Optra automated assessment of PD-L1 in non-small cell lung cancer.

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Published In

Appl Immunohistochem Mol Morphol

DOI

EISSN

1533-4058

Publication Date

April 2019

Volume

27

Issue

4

Start / End Page

263 / 269

Location

United States

Related Subject Headings

  • Pathology
  • Neoplasm Proteins
  • Lung Neoplasms
  • Immunohistochemistry
  • Humans
  • Gene Expression Regulation, Neoplastic
  • Carcinoma, Non-Small-Cell Lung
  • Biomarkers, Tumor
  • B7-H1 Antigen
  • Automation, Laboratory
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Taylor, C. R., Jadhav, A. P., Gholap, A., Kamble, G., Huang, J., Gown, A., … Rimm, D. L. (2019). A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer. Appl Immunohistochem Mol Morphol, 27(4), 263–269. https://doi.org/10.1097/PAI.0000000000000737
Taylor, Clive R., Anagha P. Jadhav, Abhi Gholap, Gurunath Kamble, Jiaoti Huang, Allen Gown, Isha Doshi, and David L. Rimm. “A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer.Appl Immunohistochem Mol Morphol 27, no. 4 (April 2019): 263–69. https://doi.org/10.1097/PAI.0000000000000737.
Taylor, Clive R., et al. “A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer.Appl Immunohistochem Mol Morphol, vol. 27, no. 4, Apr. 2019, pp. 263–69. Pubmed, doi:10.1097/PAI.0000000000000737.
Taylor CR, Jadhav AP, Gholap A, Kamble G, Huang J, Gown A, Doshi I, Rimm DL. A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer. Appl Immunohistochem Mol Morphol. 2019 Apr;27(4):263–269.

Published In

Appl Immunohistochem Mol Morphol

DOI

EISSN

1533-4058

Publication Date

April 2019

Volume

27

Issue

4

Start / End Page

263 / 269

Location

United States

Related Subject Headings

  • Pathology
  • Neoplasm Proteins
  • Lung Neoplasms
  • Immunohistochemistry
  • Humans
  • Gene Expression Regulation, Neoplastic
  • Carcinoma, Non-Small-Cell Lung
  • Biomarkers, Tumor
  • B7-H1 Antigen
  • Automation, Laboratory