Adequate tumour cellularity is essential for accurate PD-L1 immunohistochemistry assessment on cytology cell-block specimens.
Cytopathology
; 31(2): 90-95, 2020 03.
Article
em En
| MEDLINE
| ID: mdl-31808243
ABSTRACT
OBJECTIVES:
PD-L1 immunohistochemistry (IHC) is an essential predictive biomarker for patients with non-small cell lung cancer (NSCLC), required to inform treatment decisions regarding anti-PD-1 immune checkpoint inhibitor therapy. This study aims to investigate the concordance between PD-L1 IHC assessed on NSCLC cytology and histology specimens and to determine the impactce of tumour cellularity.METHODS:
Matched cytology and histology NSCLC specimens were retrieved from the archives of the Royal Melbourne Hospital and the Royal Prince Alfred Hospital. PD-L1 IHC was performed concurrently on both specimens at the Peter MacCallum Cancer Centre using the SP263 assay kit on the Ventana Benchmark Ultra staining platform and scored by two experienced pathologists.RESULTS:
Overall agreement between matched cytology and histology specimens was good (intraclass correlation coefficient = 0.653, n = 58); however, markedly increased when the analysis was limited to cell-blocks with >100 tumour cells (intraclass correlation coefficient = 0.957, n = 29). Specificity at both 1% and 50% cut-offs was high regardless of cellularity; however, sensitivity decreased in samples with <100 tumour cells.CONCLUSIONS:
PD-L1 IHC on cytology cell-block specimens in NSCLC is an acceptable alternative to histological specimens, provided adequate tumour cells are present. Clinicians and pathologists should be mindful of the risk of false negative PD-L1 IHC in samples with low tumour cellularity, to avoid excluding patients from potentially beneficial treatment.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Carcinoma Pulmonar de Células não Pequenas
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Citodiagnóstico
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Antígeno B7-H1
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Receptor de Morte Celular Programada 1
Tipo de estudo:
Prognostic_studies
Limite:
Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article