Deoxyribonucleic acid analysis by flow cytometry of uterine leiomyosarcomas and smooth muscle tumors of uncertain malignant potential.

OBJECTIVES

The histologic distinction of uterine benign leiomyomas from leiomyosarcomas is difficult. Ploidy analysis and measurement of the proliferative rate were examined to determine if they could distinguish malignant from benign tumors and if they were independent prognostic factors.

STUDY DESIGN

Paraffin-embedded blocks were recut and prepared for flow cytometry with the technique of Hedley. Mitotic counts and tumor grading were performed on an adjacent hematoxylin and eosin-stained section. Statistical analysis was carried out with chi 2 life-table, and Cox model analysis.

RESULTS

There were 33 patients with deoxyribonucleic acid histograms that were acceptable for analysis. Fourteen tumors were diploid and 19 were aneuploid. There were no significant differences in the clinical characteristics between the patients with diploid tumors and those with aneuploid tumors. Aneuploid tumors were more likely to have cellular atypia (p = 0.085). There was a strong correlation between the percentage of cells in the S phase and the mitotic count (p = 0.0001). Increasing mitotic count, increasing S phase, presence of extrauterine disease, and postmenopausal status were all adverse prognostic factors. However, when multivariant analysis with a Cox model was used, only S phase and presence of extrauterine disease were adverse factors. Diploid tumors have a better overall survival (p = 0.0658) but a similar disease-free survival. In those patients who ultimately have relapses, diploid tumors have a significantly longer interval from relapse to death (p = 0.0045).

CONCLUSIONS

Neither ploidy analysis nor measurement of the proliferative rate will distinguish a benign from a malignant course in an individual patient; however, ploidy is predictive of survival from time of disease progression and proliferative rate is the strongest predictor of overall survival. The time-proven reliability of mitotic count in the diagnosis of smooth muscle tumors reflects its ability to predict proliferative rate.