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      저자 : Hanifi Sahin (검색결과 1 건)
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        Comparison of three different risk-stratification models for predicting lymph node involvement in endometrioid endometrial cancer clinically confined to the uterus

        Vakkas Korkmaz,Mehmet Mutlu Meydanli,Ibrahim Yalçın,Mustafa Erkan Sarı,Hanifi Sahin,Eda Kocaman,Ali Haberal,Polat Dursun,Tayfun Güngör,Ali Ayhan 대한부인종양학회 2017 Journal of Gynecologic Oncology Vol.28 No.6

        Objective: To compare the clinical validity of the Gynecologic Oncology Group-99 (GOG-99), the Mayo-modified and the European Society for Medical Oncology (ESMO)-modified criteria for predicting lymph node (LN) involvement in women with endometrioid endometrial cancer (EC) clinically confined to the uterus. Methods: A total of 625 consecutive women who underwent comprehensive surgical staging for endometrioid EC clinically confined to the uterus were divided into low- and high-risk groups according to the GOG-99, the Mayo-modified, and the ESMO-modified criteria. Lymphovascular space invasion is the cornerstone of risk stratification according to the ESMO-modified criteria. These 3 risk stratification models were compared in terms of predicting LN positivity. Results: Systematic LN dissection was achieved in all patients included in the study. LN involvement was detected in 70 (11.2%) patients. LN involvement was correctly estimated in 51 of 70 LN-positive patients according to the GOG-99 criteria (positive likelihood ratio [LR+], 3.3; negative likelihood ratio [LR−], 0.4), 64 of 70 LN-positive patients according to the ESMO-modified criteria (LR+, 2.5; LR−, 0.13) and 69 of the 70 LN-positive patients according to the Mayo-modified criteria (LR+, 2.2; LR−, 0.03). The area under curve of the Mayo-modified, the GOG-99 and the ESMO-modified criteria was 0.763, 0.753, and 0.780, respectively. Conclusion: The ESMO-modified classification seems to be the risk-stratification model that most accurately predicts LN involvement in endometrioid EC clinically confined to the uterus. However, the Mayo-modified classification may be an alternative model to achieve a precise balance between the desire to prevent over-treatment and the ability to diagnose LN involvement.

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