Cytokeratin 15 is a novel and independent predictor of poor outcome in luminal B HER2-negative breast carcinomas.

Cytokeratin 15 (CK15) has been described as a stem cell marker in human organs and its expression is seen in breast tissue. CK15 expression is associated with aggressive features in endometrial and oesophageal cancers, but data on the breast are lacking. This study aims to investigate the clinicopathological associations and prognostic significance of CK15 in breast carcinomas. A multi-institute cohort of breast carcinomas were retrieved. Clinicopathological and outcome data were obtained and compared with immunohistochemical expression CK15 and a panel of biomarkers. In total, 1,476 cases were included, with an expression rate of 3.5%, preferentially expressed in luminal subtypes (p=0.024), with luminal B carcinomas being the highest (4.7%), as opposed to basal-like (1%) and HER2-overexpressed carcinomas (0%). Except for nodal stage (p=0.013) and nodal metastasis (p=0.048), oestrogen (p=0.035) and progesterone receptor (p=0.001) positivity, there were no associations with other clinicopathological parameters. A trend was observed with shorter breast cancer specific survival (BCSS) in CK15-positive luminal B carcinomas (p=0.062). On further subgroup multivariate analysis of luminal B HER2-negative carcinomas, CK15 expression exhibited robust correlation with shorter BCSS (HR=9.004, p=0.001) and disease-free survival (HR=7.085, p<0.001). Restricted to luminal breast carcinomas, specifically luminal B HER2-negative, CK15 is demonstrated to be a robust independent predictor of higher risk of recurrence and shorter survival, with potential as a clinical prognostic marker and an exclusive stem cell marker for this subgroup of carcinomas.

Detection rates and factors affecting thereof in endometrial hyperplasia, endometrial carcinoma, and cervical glandular lesions on cervical smear.

INTRODUCTION: Endometrial lesions are morphologically diverse and uncommon on cervical smears, with its detection rate and associated diagnostic categories uncharacterized. In this study, cervical smears matched to histologically proven endometrial hyperplasias and carcinomas were reviewed and compared with cervical in-situ-carcinomas/carcinomas, aiming to detail the diagnostic performance of cervical smears for upper tract and glandular lesions. METHODS: Pathology reports of cervical smears, hysterectomies, endometrial and cervical biopsies from 1995 to 2021 were retrieved. Diagnoses of cervical smears were matched to endometrial hyperplasias and carcinomas, or cervical carcinomas and reviewed. RESULTS: Totally 832 cervical smears (272 cervical carcinomas, 312 endometrial carcinomas, and 248 hyperplasias) were included. Considering all cytologic glandular diagnosis as positive, the detection rate of cervical adenocarcinoma-in-situ was the highest (64.3%), followed by cervical adenocarcinoma (63.8%), endometrial carcinoma (31.7%), and hyperplasia (with atypia-8.5%; without atypia-2.3%) (p < 0.001). Endometrial hyperplasia was most often diagnosed as atypical squamous cells of undetermined significance (ASCUS) (5.0%) or atypical glandular cells, not otherwise specified (3.6%) without indication of endometrial origin. For endometrial carcinomas, higher FIGO grading and endocervical involvement were associated with higher detection rates across all diagnostic categories (p = 0.002-0.028). High FIGO grade was associated with suspicious/favor neoplastic (C4) (31.1%vs10.3%, p < 0.001) and carcinoma (C5) (17.8% vs. 5.6%, p = 0.005) categories, but not for all glandular diagnoses combined (33.3% vs. 31.0%, p = 0.761). CONCLUSION: Detection rates for endometrial lesions are lower than cervical lesions but not insignificant. Endometrial hyperplasia should be recognized as a differential of human papilloma virus-negative ASCUS and prompt consideration of investigation of the upper genital tract.

A method for encoding clinical datasets with SNOMED CT.

BACKGROUND: Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clinical applications and vocabulary systems, there are few detailed encoding instructions and examples available to show how this can be done and the issues involved. This paper describes a heuristic method that can be used to encode clinical terms in SNOMED CT and an illustration of how it was applied to encode an existing palliative care dataset. METHODS: The encoding process involves: identifying input data items; cleaning the data items; encoding the cleaned data items; and exporting the encoded terms as output term sets. Four outputs are produced: the SNOMED CT reference set; interface terminology set; SNOMED CT extension set and unencodeable term set. RESULTS: The original palliative care database contained 211 data elements, 145 coded values and 37,248 free text values. We were able to encode ~84% of the terms, another ~8% require further encoding and verification while terms that had a frequency of fewer than five were not encoded (~7%). CONCLUSIONS: From the pilot, it would seem our SNOMED CT encoding method has the potential to become a general purpose terminology encoding approach that can be used in different clinical systems.