Abstract 1695: A multi-institutional study to evaluate automated scoring of immunohistochemistry slides for assessment of programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer
Authors: Clive Taylor, Anagha P. Jadhav, Abhi Gholap, Gurunath Kamble, Jiaoti Huang, Allen Gown, Isha Doshi, David Rimm
Journal: Cancer Research (2018)

Abstract Purpose: Assessment of 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 and to assess reproducibility of the automated Optra image analysis for PD-L1 IHC for both tumor cells and immune cells. Experimental Design: We compared conventional pathologists' scores (3 board-certified pathologists active in routine signout of these cases) 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 (NSCLC). We examined interpathologist PD-L1 expression scoring variability for both, tumor and immune cells using ordinal tumor proportion scores for tumor cells and continuous percentage positive scores. The cohort included 230 NSCLCs obtained from Yale School of Medicine, Department of Pathology archives. We assessed interpretation first by pathologists and secondly by the Optra PD-L1 image analysis scores for both tumor and immune cells. The Intra Class Correlation (ICC) for each pathologist was measured to assess variability between pathologists in scoring both tumor and immune cells. The concordance between pathologists using digital manual reads of PD-L1 staining percentages and Optra PD-L1 image analysis quantitative scores was then assessed using the Lin's concordance correlation coefficient for both tumor and immune cells. Results: Intraclass correlation coefficients to evaluate the correlation between pathologists for tumor cell (ICC = 0.750) showed an excellent concordance but lower concordance for immune cell scoring (ICC = 0.4). To compare the pathologist scores to the Optra automated system, the scores from the 3 pathologists were averaged to produce a single conventional read score. The Lin's concordance correlation coefficient between the conventional read and the machine score was 0.83 for tumor cells and 0.6 for immune cell population in intra- and peritumoral compartments. This is considered excellent agreement for tumor cells and good concordance for immune cells. Conclusion: The interpathologist assessment seen in this study is similar to previously reported studies where agreement is higher in tumor cells than immune cells. The Optra PD-L1 image analysis showed concordance with the pathologists' average scores that were comparable to interpathologist scores. This suggests promise for automated assessment of PD-L1 in NSCLC. These results justify similar studies with immunotherapy-treated patients with known outcomes. Citation Format: Clive Taylor, Anagha P. Jadhav, Abhi Gholap, Gurunath Kamble, Jiaoti Huang, Allen Gown, Isha Doshi, David Rimm. A multi-institutional study to evaluate automated scoring of immunohistochemistry slides for assessment of programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1695.