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Published on: February 28, 2019
The Spectrum of Sinonasal Respiratory Epithelial Malignancies in North Indian Cohort: Histological and
Pawan Kumar1, Suvradeep Mitra1, Amanjit Bal1
1Department of Histopathology, PGIMER, Chandigarh, India.
Abstract:
BackgroundThe WHO-fifth edition classified the sinonasal respiratory epithelial malignancies (SREMs) based on their histomorphological, immunohistochemical, and molecular features, due to their diverse manifestations.AimsWe aimed to ambispectively reclassify the SREMs at a North Indian tertiary care center, to understand the clinico-pathological spectrum of the WHO-defined entities and their prognostic implications.Material and MethodsHistopathologically proven, 162 patients with SREMs from 8 years (2016-2023) were retrieved, and re-examined for histomorphology, and relevant immunohistochemistry was performed to reclassify them. The clinical details and the follow-up data were also retrieved.ResultsKeratinizing squamous cell carcinoma (KSCC) was the most common sinonasal carcinoma (n = 76; 46.9%), followed by non-keratinizing squamous cell carcinoma (NKSCC) (n = 29; 17.9%), sinonasal undifferentiated carcinoma (SNUC) (n = 23; 14.2%), sinonasal adenocarcinoma (n = 22; 13.6%), SWI/SNF-deficient carcinoma (n = 6; 3.7%), lymphoepithelial carcinoma (n = 2; 1.2%), NUT carcinoma (n = 2; 1.2%), and teratocarcinosarcoma (n = 2; 1.2%). The median age of presentation of SREMs was 54 (IQR 45-62) years, with a male:female ratio of 2.4:1. Sinonasal adenocarcinoma showed a significantly lower median age of presentation (43.5 years) (P-value = .036). SWI/SNF-deficient carcinoma, NUT carcinoma, and teratocarcinosarcoma showed dismal prognosis irrespective of treatment. The median overall survivals of KSCC, NKSCC, SNUC, and sinonasal adenocarcinoma were 31, 63, 17, and 53 months, respectively, and showed a significant difference (P -value = .047).ConclusionReclassification of the SREMs according to the WHO-fifth edition elucidated their clinico-pathological spectrum and prognosis. This study highlights the relevance of the accurate classification of these entities for accurate treatment options and prognostication.

