RESUMO
INTRODUCTION: Complete tumor cytoreduction seems to be beneficial for platinum-sensitive women with recurrent ovarian cancer (ROC). Selection of patients who might have a chance for complete debulking constitutes a real challenge. Several predictive models defining a chance for complete cytoreduction and help in patient selection for surgery have been developed. OBJECTIVES: The aim of the study was to evaluate the effectiveness of selected models in one clinical center and the impact of complete resection on treatment outcome. MATERIAL AND METHODS: A total of 17 patients with ROC, diagnosed at least 6 months after first-line chemotherapy were recruited for the study. The inclusion criteria were based on the AGO-score (DESKTOP I trial). The group were retrospectively analyzed based on the predictive model International Collaborative Cohort Score (Tian- score). The end point was the percentage of complete cytoreduction. Also, postoperative complications and progression-free survival (PFS) were evaluated. RESULTS: Out of 17 patients who meet the criteria of the the AGO-score, complete debulking was achieved in 13 (76.47%) cases. Comparing the results of the Tian-score, 12 (100%) patients who were considered to be at 'low-risk of surgical failure' were debulked optimally In addition, complete debulking was achieved in 1 patient from the high-risk group. In all optimally operated patients, the number of changes detected during pre-operative imaging was ≤ 3. In 11 patients after complete cytoreduction there was another relapse. The median of PFS was 16 months. CONCLUSIONS: The applied predictive models have proven to be effective in selecting patients who will benefit from surgical treatment of ROC.
