, Volume 285, Issue 2, pp 521-527
Date: 22 Jul 2011

Endometrial cancer: prognostic significance of risk classification based on pre-intraoperative findings

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Abstract

Purpose

The aim of this study was to determine whether a pre-intraoperative prognostic classification of endometrial cancer (EC) patients may accurately predict prognosis.

Methods

Prognostic factors achievable before and during surgery (histotype, grade, myoinvasion, cervical spread, abdominal spread) were utilized to classify patients in low-risk (endometrial adenocarcinoma, grade 1–2, myoinvasion <50%, no evidence of abdominal spread), and in intermediate/high risk (serous papillary and clear cell, grade 3, myoinvasion >50%, cervical invasion, abdominal spread). Risk classification obtained pre-intraoperatively was compared with the classification obtained from definitive surgical-pathological assessment in 130 consecutive patients with EC treated with surgery.

Results

Pre-intraoperative risk assessment correctly identified risk classification in 125 (96%) patients; sensitivity, specificity, PPV and NPV were 98%, 94%, 94%, and 98%, respectively. Median follow-up was 38 months (range 6–93), and 14 (10%) patients relapsed (median time 14 months, range 3–60). Relative risk of relapse was higher in intermediate/high-risk patients with both classifications (pre-intraoperative RR 3.37, CI 0.99–11.5; surgical-pathological RR 4.56, CI 1.2–17.3). As regards survival 11 patients have died, 6 due to endometrial cancer and 5 due to intercurrent disease. Five-years DFS according to pre-intraoperative assessment was 89% and 71% for low-risk and intermediate high-risk patients (p = 0.028), respectively; according to definitive assessment was 91% and 70% for low-risk and intermediate/high-risk patients (p = 0.009), respectively.

Conclusion

This classification, giving an accurate risk and prognostic estimate with parameters routinely utilized in clinical practice, may help the surgeon when undertaking the decision to perform limited or extended surgical staging according to tumor and patient characteristics.