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Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter.
Although different histological grading systems of prostatic cancer refer to well-described characteristics, results are hard to reproduce. The aim of this study was to obtain morphometric data that would enable objective and reproducible grading of prostatic cancers by stereological estimation of m...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
1997
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2223932/ https://www.ncbi.nlm.nih.gov/pubmed/9231924 |
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author | Arima, K. Sugimura, Y. Hioki, T. Yamashita, A. Kawamura, J. |
author_facet | Arima, K. Sugimura, Y. Hioki, T. Yamashita, A. Kawamura, J. |
author_sort | Arima, K. |
collection | PubMed |
description | Although different histological grading systems of prostatic cancer refer to well-described characteristics, results are hard to reproduce. The aim of this study was to obtain morphometric data that would enable objective and reproducible grading of prostatic cancers by stereological estimation of mean nuclear volume (MNV). The clinical records and tissue specimens from 100 patients who were newly diagnosed as having prostatic cancer from 1973 to 1990 and who were followed up for 5 years or longer were retrospectively examined. We analysed the relationship between MNV and clinical stage, Gleason score and histological grading according to the World Health Organization (WHO) classification. To evaluate prognostic predictors, a multivariate analysis of factors associated with cause-specific survival was performed. We found a good correlation between the MNV and clinical stage and between the MNV and histological grading. There was no correlation between MNVs and Gleason scores. Multivariate analysis revealed that the MNV was the only predictor of survival time (coefficient 0.005; P < 0.0001; hazard ratio 1.005). We consider that the MNV is an excellent predictor of the prognosis in patients with prostatic cancer. Moreover, stereological estimation of MNV is a simple, quick, inexpensive and reliable morphometric procedure that enables the quantitative analysis of the histological and biological character of prostatic cancer. |
format | Text |
id | pubmed-2223932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 1997 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-22239322009-09-10 Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. Arima, K. Sugimura, Y. Hioki, T. Yamashita, A. Kawamura, J. Br J Cancer Research Article Although different histological grading systems of prostatic cancer refer to well-described characteristics, results are hard to reproduce. The aim of this study was to obtain morphometric data that would enable objective and reproducible grading of prostatic cancers by stereological estimation of mean nuclear volume (MNV). The clinical records and tissue specimens from 100 patients who were newly diagnosed as having prostatic cancer from 1973 to 1990 and who were followed up for 5 years or longer were retrospectively examined. We analysed the relationship between MNV and clinical stage, Gleason score and histological grading according to the World Health Organization (WHO) classification. To evaluate prognostic predictors, a multivariate analysis of factors associated with cause-specific survival was performed. We found a good correlation between the MNV and clinical stage and between the MNV and histological grading. There was no correlation between MNVs and Gleason scores. Multivariate analysis revealed that the MNV was the only predictor of survival time (coefficient 0.005; P < 0.0001; hazard ratio 1.005). We consider that the MNV is an excellent predictor of the prognosis in patients with prostatic cancer. Moreover, stereological estimation of MNV is a simple, quick, inexpensive and reliable morphometric procedure that enables the quantitative analysis of the histological and biological character of prostatic cancer. Nature Publishing Group 1997 /pmc/articles/PMC2223932/ /pubmed/9231924 Text en https://creativecommons.org/licenses/by/4.0/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 https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Article Arima, K. Sugimura, Y. Hioki, T. Yamashita, A. Kawamura, J. Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title | Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title_full | Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title_fullStr | Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title_full_unstemmed | Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title_short | Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
title_sort | stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter. |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2223932/ https://www.ncbi.nlm.nih.gov/pubmed/9231924 |
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