Accuracy of preoperative endometrial sampling diagnosis for predicting the final pathology grading in uterine endometrioid carcinoma

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• 作者：T.P. Batista^a ; ^b ; ^{t.paulo@bol.com.br" class="auth_mail" title="E-mail the corresponding author} ; C.L.C. Cavalcanti^b ; A.A.G. Tejo^b ; A.L.R. Bezerra^a ; ^b
• 关键词：Endometrial neoplasm ; Lymphadenectomy ; Neoplasm staging ; Surgical pathology ; Dilatation and curettage ; Hysteroscopy
• 刊名：European Journal of Surgical Oncology (EJSO)
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：42
• 期：9
• 页码：1367-1371
• 全文大小：158 K

文摘

To explore the accuracy of preoperative endometrial sampling diagnosis for predicting the final pathology grading in endometrial cancer.

Methods

A cross-sectional study was carried out on patients who underwent surgical treatment for clinically early-stage endometrioid carcinoma of uterus at our Centers from March, 1991 to June, 2012. The agreement levels for the histological grading between the preoperative endometrial sampling diagnosis and the final surgical pathology were analyzed by the Kappa (κ) statistics with 95% confidence intervals (CI). The statistical analyses were also based on frequency data and diagnostic agreement of the procedures.

Results

We retrospectively selected 79 patients that fit the criteria of this analysis. The overall level of agreement between preoperative and postoperative grading was “fair” according to Kappa (κ) statistics (κ = 0.221; 95%CI = 0.389–0.053; p = 0.01). Accordingly, the overall concordance was 48/79 (60.75%)–39/58 (67.24%) for G1, 7/16 (43.75%) for G2, and 2/5 (40%) for G3 tumors. The preoperative grade 1 diagnosis was upgraded to grade 2 (n = 6) or 3 (n = 1) in 15.2% of patients after hysterectomy. Sensitivity, specificity, NPV, PPV, and accuracy of preoperative endometrial sampling diagnosis to predict grade 1 at the final surgical pathology was 67.2%, 66.7%, 42.4%, 84.8% and 67.1%, respectively.

Conclusions

Preoperative endometrial sampling was found to be only a modest overall predictor of postoperative histological grading. A selective staging policy based on predictive models to avoid lymph node dissections in endometrial cancer should take into account additional parameters.