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

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.

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).

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).

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.