Nuclear morphometry for improved prediction of the prognosis of human bladder carcinoma

35Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Background. Histologic grade and clinical stage generally are used for estimating the prognosis of bladder carcinoma. However, both methods have been reported to have a rather low reproducibility and to be unsatisfactory for predicting the recurrence and progression of superficial bladder carcinoma. Recently, nuclear morphometry was used to quantitate the malignant potential of cancer cells in a more objective and reproducible manner. The authors quantitatively analyzed the malignant potential of bladder carcinoma at initial presentation using a combination of several nuclear morphometric variables. Methods. The subjects were 156 patients with previously untreated bladder carcinoma. Three morphometric variables were measured in each subject: the mean nuclear volume (MNV), the nuclear roundness factor (NRF), and the variation of nuclear area (VNA). Results. Univariate analysis showed that MNV and NRF were significant prognostic indicators for survival (MNV, P < 0.0001; NRF, P = 0.008). In addition, MNV was a prognostic indicator for tumor recurrence (P = 0.001), whereas MNV and NRF were prognostic indicators for invasive progression (MNV, P = 0.02; NRF, P = 0.009). For accurate prediction of the prognosis of patients with bladder carcinoma, a prognostic score, a recurrence score, and a progression score were designed using the coefficients of MNV and NRF in a proportional hazards model. The prognostic score clearly divided the patients into two different groups with 5‐year survival rates of 88% and 64% (P = 0.0002). In addition, patients with superficial bladder carcinoma and a low recurrence score had a significantly higher 5‐year recurrence free rate than those with a high recurrence score (40% vs. 23%, P = 0.0004), and the 5‐year progression free rate of patients with a low progression score was significantly higher than that of those with a high progression score (98% vs. 73%, P = 0.0006). Conclusions. These findings suggest that nuclear morphometry is a reliable technique with which to identify prognostic indicators for human bladder carcinoma. A combination of several nuclear morphometric variables provides a more accurate indication of prognosis than any single parameter. Cancer 1995; 76:1790‐6. Copyright © 1995 American Cancer Society

References Powered by Scopus

Nuclear overexpression of p53 protein in transitional cell bladder carcinoma: A marker for disease progression

510Citations
N/AReaders
Get full text

Stereological estimation of the volume‐weighted mean volume of arbitrary particles observed on random sections

477Citations
N/AReaders
Get full text

Prognostic factors for recurrence and follow-up policies in the treatment of superficial bladder cancer: Report from the British Medical Research Council subgroup on superficial bladder cancer (urological cancer working party)

233Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Cancer biology and the nuclear envelope: A convoluted relationship

70Citations
N/AReaders
Get full text

The nuclear envelope and cancer: A diagnostic perspective and historical overview

42Citations
N/AReaders
Get full text

An objective morphologic parameter to aid in the diagnosis of flat urothelial carcinoma in situ

34Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Fukuzazva, S., Hashimura, T., Sasaki, M., Yamabe, H., & Yoshida, O. (1995). Nuclear morphometry for improved prediction of the prognosis of human bladder carcinoma. Cancer, 76(10), 1790–1796. https://doi.org/10.1002/1097-0142(19951115)76:10<1790::AID-CNCR2820761017>3.0.CO;2-J

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

80%

Researcher 1

20%

Readers' Discipline

Tooltip

Agricultural and Biological Sciences 2

33%

Medicine and Dentistry 2

33%

Biochemistry, Genetics and Molecular Bi... 2

33%

Save time finding and organizing research with Mendeley

Sign up for free