ArticleCancer cytopathology2025
InterobServer AgreeMent in Pd-l1 evaLuatIoN on cytoloGical samples-SAMPLING project: A multi-institutional, international study.
Article in Cancer cytopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Optimizing preoperative assessment of salivary gland lesions: updates and practical implications in the Milan System 2nd edition.Virchows Archiv : an international journal of pathology · 2026Review
- InterobServer AgreeMent in Pd-l1 evaLuatIoN on cytoloGical samples-SAMPLING project: A multi-institutional, international study.Cancer cytopathology · 2025Article
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48 authors.
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Abstract
introductionThe aim of this project is to assess interobserver agreement for programmed death-ligand 1 (PD-L1) scoring on of non-small cell lung cancer (NSCLC) on cytological specimens in a large-scale multicenter study, by exploiting the cell block-derived tissue microarray (cbTMA) approach.
methodsA total of 65 cell blocks (CB) diagnosed as NSCLC were retrospectively collected and selected for TMA preparation. Hematoxylin-eosin and PD-L1 stained slides were digitized and uploaded on a free web sharing platform. Participants were asked to provide PD-L1 assessment by using the clinically relevant cutoff of tumor proportion score (TPS) (<1%; 1%-49%; >50%). Interobserver agreement was calculated using Fleiss's κ.
resultsOf 65 CBs, 11 were deemed not suitable; therefore, an overall number of 54 cores were used for the preparation of four TMAs. A total of 1674 evaluations were provided by 31 cytopathologists from 21 different institutions in nine countries. The statistical analysis showed a moderate overall agreement (κ = 0.49). The highest agreement was achieved in the TPS >50% category (κ = 0.57); moderate agreement was observed in TPS <1% category (κ = 0.51) and the lowest κ value was obtained for TPS 1%-49% category (k = 0.32).
conclusionsThe overall moderate agreement observed showed that there is still room for improvement in inter-pathologist agreement for PD-L1 evaluation on cytological samples, highlighting the need for standardization in sample preparation, focused training in PD-L1 evaluation on cytological material, and the integration of machine learning tools to improve interobserver consistency.
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