Value of quantitative pathological variables as prognostic factors in advanced ovarian carcinoma.
Open Access
- 1 February 1996
- journal article
- research article
- Published by BMJ in Journal of Clinical Pathology
- Vol. 49 (2) , 142-148
- https://doi.org/10.1136/jcp.49.2.142
Abstract
AIMS: To evaluate correlations among clinical, pathological, morphometric, stereological, and DNA flow cytometric variables and their prognostic value in advanced ovarian cancer. METHODS: Tissue was collected from 180 patients with advanced ovarian cancer. All 180 had undergone debulking surgery and were being treated with cisplatin. Long term follow up was available for all patients. The mitotic activity index (MAI), volume % of epithelium (VPE), mean nuclear area (MNA), standard deviation of the nuclear area (SDNA), estimates of volume weighted mean nuclear volume (nu v), and variables obtained from minimum spanning tree (MST) analysis were assessed in the least differentiated tumour section in each case. DNA flow cytometry was also performed. RESULTS: Quantitative pathological features differed significantly with respect to histological grade. The MAI, MNA, SDNA, and the number of points connected to three neighbours differed significantly among the different DNA ploidy groups. The VPE and number of points connected to two or three neighbours differed significantly between FIGO stages III and IV. Fifty two (29%) patients survived. FIGO stage, residual disease and SDNA had prognostic significance on both univariate and multivariate survival analysis. In patients with FIGO III stage disease and residual tumour nodes < or = 2 cm in diameter (67 patients, 29 (43%) survivors) a prognostic index was established based on SDNA and of the line length of the MST. The median survival time was not reached in a subgroup of patients with favourable prognosis (overall survival 57%). Median survival was 32 months for patients with an unfavourable index score (overall survival 28%). CONCLUSION: Morphometric variables have important additional value in predicting prognosis in patients with advanced ovarian cancer.Keywords
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