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Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203726/ https://www.ncbi.nlm.nih.gov/pubmed/30367100 http://dx.doi.org/10.1038/s41598-018-34165-5 |
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author | Zaini, Zuraiza Mohamad McParland, Helen Møller, Henrik Husband, Kate Odell, Edward W. |
author_facet | Zaini, Zuraiza Mohamad McParland, Helen Møller, Henrik Husband, Kate Odell, Edward W. |
author_sort | Zaini, Zuraiza Mohamad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6203726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62037262018-10-31 Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading Zaini, Zuraiza Mohamad McParland, Helen Møller, Henrik Husband, Kate Odell, Edward W. Sci Rep Article 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. Nature Publishing Group UK 2018-10-26 /pmc/articles/PMC6203726/ /pubmed/30367100 http://dx.doi.org/10.1038/s41598-018-34165-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zaini, Zuraiza Mohamad McParland, Helen Møller, Henrik Husband, Kate Odell, Edward W. Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title | Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title_full | Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title_fullStr | Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title_full_unstemmed | Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title_short | Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading |
title_sort | predicting malignant progression in clinically high-risk lesions by dna ploidy analysis and dysplasia grading |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203726/ https://www.ncbi.nlm.nih.gov/pubmed/30367100 http://dx.doi.org/10.1038/s41598-018-34165-5 |
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