Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading

Zaini, Zuraiza Mohamad and McParland, Helen and Moller, Henrik and Husband, Kate and Odell, Edward W. (2018) Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading. Scientific Reports, 8. p. 15874. ISSN 2045-2322

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Official URL: https://doi.org/10.1038/s41598-018-34165-5

Abstract

The value of image cytometry DNA ploidy analysis and dysplasia grading to predict malignant transformation has been determined in oral lesions considered to be at 'high' risk on the basis of clinical information and biopsy result. 10-year follow up data for 259 sequential patients with oral lesions clinically at 'high' risk of malignant transformation were matched to cancer registry and local pathology database records of malignant outcomes, ploidy result and histological dysplasia grade. In multivariate analysis (n = 228 patients), 24 developed carcinoma and of these, 14 prior biopsy samples were aneuploid. Aneuploidy was a significant predictor (hazard ratio 7.92; 95%CI 3.45, 18.17) compared with diploidy (p < 0.001). The positive predictive value (PPV) for severe dysplasia was 50% (95%CI 31.5, 68.5) and for aneuploid lesions, 33.3% (95%CI 19.0, 47.6). Combined DNA aneuploidy and severe dysplasia increased PPV to 56.3% (95% CI 31.9, 80.6). Diploid-tetraploid and non-dysplastic status had high negative predictive values (NPV) of 94.6% (95% CI 91.4, 97.8) and 99.17% (95% CI 97.4, 100.8) respectively. DNA ploidy predicts malignant transformation well and combining it with dysplasia grading gave the highest predictive value. The predictive values reported here exceed those from other investigations to date.

Item Type: Article
Uncontrolled Keywords: Malignant; High-risk lesions; DNA ploidy analysis; Dysplasia grading
Subjects: R Medicine > RK Dentistry
R Medicine > RK Dentistry > Oral surger
Divisions: Faculty of Dentistry > Dept of Oral & Maxillofacial Surgery
Depositing User: Mr Ahmad Azwan Azman
Date Deposited: 26 Dec 2018 02:32
Last Modified: 26 Dec 2018 02:32
URI: http://eprints.um.edu.my/id/eprint/19805

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