ArticleEuropean journal of breast health2017
Sub-classification of Breast Masses by Fine Needle Aspiration Cytology.
Article in European journal of breast health, 2017. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- International Academy of Cytology Yokohama System for Reporting Breast Cytology and the ACR Breast Imaging Reporting and Data System (BIRADS): Are they Concordant?Iranian journal of pathology · 2024Article
- Cytomorphological patterns of breast lesions among women with palpable breast lumps attending select teaching and referral hospitals in Kenya: a descriptive cross-sectional study.The Pan African medical journal · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study is to evaluate the accuracy of sub-classification of breast diseases using Fine Needle Aspiration cytology (FNAC). MATERIALS AND
methodsA one-year prospective study of 180 consecutive patients with palpable breast lesions who underwent FNAC and subsequently open surgical biopsy for histological confirmation. FNAC was used to sub-classify breast lesions and then correlated with histological diagnosis.
resultsA total of 180 patients were enrolled into the study but only 110 patients with histology report were used for test validity. Seventeen (15.5%) smears were C1; while 46 (41.8%), 5 (4.5%), 4 (3.6%) and 38 (34.6%) were C2, C3, C4 and C5, respectively. FNAC achieved sensitivity of 90.0%, specificity of 95.5%, false positive rate of 5.3%, false negative rate of 8.7%, positive predictive value of 94.7%, negative predictive value of 91.3% and overall diagnostic accuracy of 92.9%. Only 86 (78.2%) of the 110 smears could be sub-classified into different disease conditions of the breast on cytology. FNAC accurately sub-classified 25(78.1%) of fibroadenoma and 28(87.5%) of invasive ductal carcinoma.
conclusionFNAC can reasonably sub-classify fibroadenoma, invasive ductal carcinoma and mastitis but there is still a challenge with lobular carcinomas, metaplastic carcinomas, papillary carcinomas and fibrocystic changes.
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