RESUMEN
This study was performed in order to investigate the role of the apoptotic index (AI) as a prediction parameter for the prognosis of patients with primary breast cancer. AI was determined by DNA fragmentation on 298 primary breast cancer samples and compared to clinically established breast cancer parameters. Additionally, we determined the expression of functional parameters including proliferating cell nuclear antigen, p21waf and p27kip by immunohistochemistry. The mean AI was found to be 11.9% (range, 0-90%). 189 tumors (63.4%) were negative for apoptosis, while 109 tissue samples (36.6%) were apoptotic with >5% positive cells. Using univariate analysis (chi2 test), the AI did not show any significant correlation to one of the established prognostic parameters of primary breast cancer (p > 0.05). In contrast, we found a significant positive correlation to the expression of the cell cycle inhibitors p21waf (p = 0.04) and p27kip (p = 0.024). During the clinical follow-up (median observation time for disease-free survival 87 months), several clinically established prognostic parameters including menopausal status, nodal status, tumor size, tumor grade, and hormone receptor expression could be confirmed and were analyzed with respect to the AI in the tumor. Furthermore, AI displayed a significant positive correlation to disease-free survival using Kaplan-Meier survival analysis (log-rank test, p = 0.04). However, AI lost its prognostic significance in multivariate analysis based on the Cox proportional hazard model (relative risk 0.8, confidence interval 0.52-1.33, p = 0.44). Our data indicate that high apoptotic rates in cancer tissues are indicative of a favorable patient outcome. However, the AI was not an independent factor. The study provides indirect evidence that this process may involve cell cycle inhibitors physiologically.