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Stereologically estimated mean nuclear volume of prostatic cancer is a reliable prognostic parameter
- Source :
- British Journal of Cancer
- Publication Year :
- 1997
-
Abstract
- 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.
- Subjects :
- Male
Cancer Research
medicine.medical_specialty
Pathology
Multivariate analysis
Urology
World health
Prostate
medicine
Nuclear volume
Humans
Grading (tumors)
Retrospective Studies
Cell Nucleus
business.industry
Hazard ratio
Cancer
Prostatic Neoplasms
Reproducibility of Results
medicine.disease
Prognosis
Survival Analysis
medicine.anatomical_structure
Oncology
Adenocarcinoma
business
Research Article
Subjects
Details
- ISSN :
- 00070920
- Volume :
- 76
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- British journal of cancer
- Accession number :
- edsair.doi.dedup.....249b13298e21b7bee49f25b3986d58cf