A novel multivariable prediction model for lymphatic dissemination in endometrioid endometrial cancer: The lymph node Metastasis Risk Index

Author(s):  
Mehmet M. Meydanli ◽  
Koray Aslan ◽  
Murat Oz ◽  
Kamil H. Muftuoglu ◽  
Ibrahim Yalcin ◽  
...  
2017 ◽  
Vol 27 (4) ◽  
pp. 748-753 ◽  
Author(s):  
Alper Karalok ◽  
Taner Turan ◽  
Derman Basaran ◽  
Osman Turkmen ◽  
Gunsu Comert Kimyon ◽  
...  

ObjectiveThe aim of this study was to evaluate the effectiveness of histological grade, depth of myometrial invasion, and tumor size to identify lymph node metastasis (LNM) in patients with endometrioid endometrial cancer (EC).MethodsA retrospective computerized database search was performed to identify patients who underwent comprehensive surgical staging for EC between January 1993 and December 2015. The inclusion criterion was endometrioid type EC limited to the uterine corpus. The associations between LNM and surgicopathological factors were evaluated by univariate and multivariate analyses.ResultsIn total, 368 patients were included. Fifty-five patients (14.9%) had LNM. Median tumor sizes were 4.5 cm (range, 0.7–13 cm) and 3.5 cm (range, 0.4–33.5 cm) in patients with and without LNM, respectively (P = 0.005). No LMN was detected in patients without myometrial invasion, whereas nodal spread was observed in 7.7% of patients with superficial myometrial invasion and in 22.6% of patients with deep myometrial invasion (P < 0.0001). Lymph node metastasis tended to be more frequent in patients with grade 3 disease compared with those with grade 1 or 2 disease (P = 0.131).ConclusionsThe risk of lymph node involvement was 30%, even in patients with the highest-risk uterine factors, that is, those who had tumors of greater than 2 cm, deep myometrial invasion, and grade 3 disease, indicating that 70% of these patients underwent unnecessary lymphatic dissection. A precise balance must be achieved between the desire to prevent unnecessary lymphadenectomy and the ability to diagnose LNM.


2014 ◽  
Vol 292 (1) ◽  
pp. 183-190 ◽  
Author(s):  
Haider Mahdi ◽  
Adnan R. Munkarah ◽  
Rouba Ali-Fehmi ◽  
Jessica Woessner ◽  
Shetal N. Shah ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yuquan Xu ◽  
Renfeng Zhao

The predictive values of region of interest (ROI) target detection algorithm-based radiomics for endometrial cancer (EC) lymph node metastasis was investigate in this work. 143 patients with EC admitted by hospital were selected as the research objects and divided randomly into a training group (group A) and a test group (group B). They received preoperative pelvic-enhanced magnetic resonance imaging (MRI) scanning. The ROI algorithm was applied to extract features to construct an EC lymph node radiomics model that was compared with a comprehensive prediction model of EC lymph node. The receiver operating characteristic (ROC) curve was employed to evaluate the diagnostic efficiency of the radiomic model and comprehensive predictive model. Results showed that both the radiomics model (area under the curve (AUC) of group A = 0.875 and AUC of group B = 0.882) and comprehensive prediction model (AUC of group A = 0.917 and AUC of group B = 0.893) had good predictive effects, and effect of the latter was markedly better than that of the former. It indicated that radiomics parameters of ROI target detection algorithm were effective markers for preoperative prediction of EC lymph node metastasis, and its comprehensive prediction model could play a guiding role in clinical decision-making.


2006 ◽  
Vol 12 (1) ◽  
pp. 83-88 ◽  
Author(s):  
Michael A. Bidus ◽  
John I. Risinger ◽  
Gadisetti V.R. Chandramouli ◽  
Lou A. Dainty ◽  
Tracy J. Litzi ◽  
...  

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