Aims: Previous concordance studies examining accuracy of breast diagnosis by pathologists, typically targeting difficult, histologically challenging breast lesions using artificial and restrictive environments, have reported aberrantly high levels of diagnostic discordance. The results of these studies may be misinterpreted by non-pathologists and raise concerns relating to routine practice. This study aims to assess the diagnostic agreement among UK breast pathologists.
Methods: Two hundred and forty consecutive breast lesions, submitted by participants from their routine practice, included in the UK National Health Service Breast Screening Programme (NHSBSP) breast pathology EQA scheme during the last 10 years were reviewed. An average of approximately 600 participants viewed each case. Data on diagnostic categories (benign, atypical, in-situ malignant and invasive malignant) were collected. In this study, benign and atypical diagnoses were grouped together.
Results: The overall diagnostic agreement level was in the almost perfect range. Thirty-five cases (14.6%) showed diagnostic concordance of ≤95%. Reasons for discordance included one or more of: (1) scheme methodology limitations such as: (i) miscoding of certain lesions (e.g. phyllodes tumours and lobular neoplasia) (n = 7) and (ii) variable representation of the index lesion on glass slides (n = 18); and (2) diagnostically challenging cases that may be interpreted more easily using immunohistochemistry (n = 28). These latter included benign and malignant papillary lesions (n = 12), complex sclerosing lesions (n = 7), intraductal epithelial proliferative lesions (n = 6) and an unusual special tumour type (n = 1). Further review identified pathologists' misinterpretation in 13 cases (5.4%), with an average discordance rate of only 4.2%.
Conclusions: The performance of breast pathologists is high. Exclusion of the effect of the scheme methodology limitations highlights further the high performance rate and identifies true diagnostically challenging entities. These difficult cases may benefit from additional diagnostic work-up and second opinions.
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http://dx.doi.org/10.1111/his.13117 | DOI Listing |
Biomed Phys Eng Express
January 2025
School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
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New College of Florida, Sarasota, FL, United States.
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View Article and Find Full Text PDFInt J Radiat Biol
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Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei City, Taiwan.
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View Article and Find Full Text PDFPLoS One
January 2025
Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Triple negative breast cancers often contain higher numbers of tumour-infiltrating lymphocytes compared with other breast cancer subtypes, with their number correlating with prolonged survival. Since little is known about tumour-infiltrating lymphocyte trafficking in triple negative breast cancers, we investigated the relationship between tumour-infiltrating lymphocytes and the vascular compartment to better understand the immune tumour microenvironment in this aggressive cancer type. We aimed to identify mechanisms and signaling pathways responsible for immune cell trafficking in triple negative breast cancers, specifically of basal type, that could potentially be manipulated to change such tumours from immune "cold" to "hot" thereby increasing the likelihood of successful immunotherapy in this challenging patient population.
View Article and Find Full Text PDFPLoS One
January 2025
Biology Department, Faculty of Science, Islamic University of Madinah, Madinah, Saudi Arabia.
This study presents a novel approach to modeling breast cancer dynamics, one of the most significant health threats to women worldwide. Utilizing a piecewise mathematical framework, we incorporate both deterministic and stochastic elements of cancer progression. The model is divided into three distinct phases: (1) initial growth, characterized by a constant-order Caputo proportional operator (CPC), (2) intermediate growth, modeled by a variable-order CPC, and (3) advanced stages, capturing stochastic fluctuations in cancer cell populations using a stochastic operator.
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