Prognostic criteria in patients with prostate cancer: correlation with volume weighted mean nuclear volume.
OBJECTIVE
Grading of malignancy in prostate cancer is based on qualitative, morphological examination and suffers from poor reproducibility. On the other hand, estimating the volume weighted mean nuclear volume, which was developed by Gunderson and Jensen based on a stereological technique, is a simple method with high reproducibility. Furthermore, it has been reported that mean nuclear volume is remarkably correlated with prognosis of bladder cancer. We compared mean nuclear volume to 2 histological grading methods and clinical stage to determine the prognosis of prostate cancer using a Cox proportional hazards model.


METHODS
A retrospective, prognostic study of 52 patients with prostate cancer diagnosed by transurethral resection of the prostate or needle punch biopsy between January 1983 and July 1994 was performed. Unbiased estimates of mean nuclear volume were compared to patient age at diagnosis, clinical stage, histological grading according to the World Health Organization (WHO) classification and Gleason score of the prognostic value.


RESULTS
Univariate analysis revealed that estimates of mean nuclear volume (p = 0.0011), clinical stage (p = 0.0014) and WHO classification (p = 0.0010) correlated significantly with progression-free survival, and that clinical stage (p = 0.0005) and estimates of mean nuclear volume (p = 0.0049) correlated significantly with disease-specific survival of patients with prostate cancer. However, multivariate analysis revealed that only estimates of mean nuclear volume and clinical stage were the 2 most powerful independent prognosticators in progression-free and disease-specific survival.


CONCLUSIONS
Our results indicate that estimates of mean nuclear volume are prognostically superior to morphological grading of malignancy, such as Gleason score and WHO classification, in prostate cancer.
D000368:Aged; D002467:Cell Nucleus; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000473:pathology*; D012189:Retrospective Studies