scholarly journals Risk assessment of lymph node metastasis before surgery in endometrial cancer: Do we need a clinical trial for low-risk patients?

2014 ◽  
Vol 40 (2) ◽  
pp. 322-326 ◽  
Author(s):  
Sokbom Kang ◽  
Yukiharu Todo ◽  
Hidemichi Watari
Keyword(s):  
Risk Assessment ◽  
Clinical Trial ◽  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Low Risk ◽  
Node Metastasis ◽  
Risk Patients

scholarly journals Implications of Isolated Para-Aortic Lymph Node Metastasis in Endometrial Cancer: A Large-Scale, Multicenter, and Retrospective Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Wenting Li ◽  
Jie Jiang ◽  
Yu Fu ◽  
Yuanming Shen ◽  
Chuyao Zhang ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Large Scale ◽  
Low Risk ◽  
Surgical Staging ◽  
Node Metastasis ◽  
Aortic Lymph Node ◽  
Risk Patients ◽  
Metastatic Sites

Objective: To systematically evaluate lymph node metastasis (LNM) patterns in patients with endometrial cancer (EC) who underwent complete surgical staging, which included systematic pelvic and para-aortic lymphadenectomy.Methods: Four thousand and one patients who underwent complete surgical staging including systematic pelvic and para-aortic lymphadenectomy for EC were enrolled from 30 centers in China from 2001 to 2019. We systematically displayed the clinical and prognostic characteristics of patients with various LNM patterns, especially the PLN-PAN+ [para-aortic lymph node (PAN) metastasis without pelvic lymph node (PLN) metastasis]. The efficacy of PAN+ (para-aortic lymph node metastasis) prediction with clinical and pathological features was evaluated.Results: Overall, 431 of the 4,001 patients (10.8%) showed definite LNM according to pathological diagnosis. The PAN+ showed the highest frequency (6.6%) among all metastatic sites. One hundred fourteen cases (26.5%) were PLN-PAN+ (PAN metastasis without PLN metastasis), 167 cases (38.7%) showed PLN+PAN-(PLN metastasis without PAN metastasis), and 150 cases (34.8%) showed metastasis to both regions (PLN+PAN+). There was also 1.9% (51/2,660) of low-risk patients who had PLN-PAN+. There are no statistical differences in relapse-free survival (RFS) and disease-specific survival (DSS) among PLN+PAN-, PLN-PAN+, and PLN+PAN+. The sensitivity of gross PLNs, gross PANs, and lymphovascular space involvement (LVSI) to predict PAN+ was 53.8 [95% confidence interval (CI): 47.6–59.9], 74.2 95% CI: 65.6–81.4), and 45.8% (95% CI: 38.7–53.2), respectively.Conclusion: Over one-fourth of EC patients with LMN metastases were PLN-PAN+. PLN-PAN+ shares approximate survival outcomes (RFS and DSS) with other LNM patterns. No effective clinical methods were achieved for predicting PAN+. Thus, PLN-PAN+ is a non-negligible LNM pattern that cannot be underestimated in EC, even in low-risk patients.

scholarly journals DNA ploidy in curettage specimens identifies high-risk patients and lymph node metastasis in endometrial cancer

2015 ◽  
Vol 112 (10) ◽  
pp. 1656-1664 ◽  
Author(s):  
T S Njølstad ◽  
◽  
J Trovik ◽  
T S Hveem ◽  
M L Kjæreng ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
Dna Ploidy ◽  
High Risk Patients ◽  
Node Metastasis ◽  
Risk Patients

Preoperative Identification of a Low-Risk Group for Lymph Node Metastasis in Endometrial Cancer: A Korean Gynecologic Oncology Group Study

2012 ◽  
Vol 30 (12) ◽  
pp. 1329-1334 ◽  
Author(s):  
Sokbom Kang ◽  
Woo Dae Kang ◽  
Hyun Hoon Chung ◽  
Dae Hoon Jeong ◽  
Sang-Soo Seo ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Risk Group ◽  
False Negative ◽  
False Negative Rate ◽  
Low Risk ◽  
Ca 125 ◽  
Node Metastasis ◽  
Negative Rate

Purpose The aim of this study was to develop a preoperative risk prediction model for lymph node metastasis in patients with endometrial cancer and to identify a low-risk group before surgery. Patients and Methods The medical records of 360 patients with endometrial cancer who underwent surgical staging were collected from four institutions and were retrospectively reviewed. By using serum CA-125 levels, preoperative biopsy data, and magnetic resonance imaging (MRI) data, a multivariate logistic model was created. Patients whose predicted probability was less than 4% were defined as low risk. The developed model was externally validated in 180 patients from two independent institutions. Results Serum CA-125 levels and three MRI parameters (deep myometrial invasion, lymph node enlargement, and extension beyond uterine corpus) were found to be independent risk factors for nodal metastasis. The model classified 53% of patients as part of a low-risk group, and the false negative rate was 1.7%. In the validation cohort, the model classified 43% of patients as low-risk, and the false negative rate was 1.4%. The model showed good discrimination (area under the receiver operator characteristic curve = 0.85) and was calibrated well. The negative likelihood ratio of our low-risk criteria was 0.11 (95% CI, 0.04 to 0.29), which was equivalent to the false-negative rate of 1.3% (95% CI, 0.5% to 3.3%) at the assumed prevalence of nodal metastasis of 10%. Conclusion Using serum CA-125 and MRI as criteria resulted in the accurate identification of a low-risk group for lymph node metastasis among patients with endometrial cancer.

Construction and Validation of a Prognostic Model Based on 11 Lymph Node Metastasis Related Genes for Overall Survival in Endometrial Cancer

2021 ◽  
Author(s):  
Hong Wu ◽  
haiqin Feng ◽  
Xiaoli Miao ◽  
jiancai Ma ◽  
Cairu Liu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Endometrial Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Low Risk ◽  
Node Metastasis

Abstract Background: Endometrial cancer (EC) is one of the most common malignant tumor in the female reproductive system. The incidence of lymph node metastasis (LNM) is only about 10% in clinically suspected early-stage EC patients. Discovering prognostic model and effective biomarkers for early diagnosis is important to reduce the mortality rate. Methods: We downloaded the RNA-sequencing data and clinical information from the TCGA database. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to analyze the differentially expressed genes (DEGs). A least absolute shrinkage and selection operator (LASSO) regression was conducted to identify the characteristic dimension decrease and distinguish prognosis-related LNM related genes signature. Subsequently, a novel prognosis-related nomogram to predict overall survival (OS). A survival analysis was carried out to explore the individual prognostic significance of the risk model and key gene was validated in vitro. Results: In total, 89 LRGs were identified. Based on the LASSO Cox regression, 11 genes were selected for the development of a risk evaluation model. The Kaplan–Meier curve indicated that patients in the low-risk group had considerably better OS (P = 3.583e−08). The area under the curve (AUC) of this model was 0.718 at 5 years of OS. Then, we developed an OS-associated nomogram that included the risk score and clinicopathological features. The concordance index of the nomogram was 0.769. The survival verification performed in three subgroups from the nomogram demonstrated the validity of the model. The AUC of the nomogram was 0.787 at 5 years OS. Proliferation and metastasis of HMGB3 were explored in EC cell line. Finally, we revealed that the most frequently mutated genes in the low-risk and high-risk groups are PTEN and TP53, respectively. Conclusions: Our results suggest that LNM plays an important role in the prognosis, and HMGB3 was potential as a biomarker for EC patients. By detecting the mutation of the risk signature, clinicians can accurately treat patients with targeted therapy, thereby improving their survival rate.

Stathmin Overexpression Identifies High-Risk Patients and Lymph Node Metastasis in Endometrial Cancer

2011 ◽  
Vol 17 (10) ◽  
pp. 3368-3377 ◽  
Author(s):  
Jone Trovik ◽  
Elisabeth Wik ◽  
Ingunn M. Stefansson ◽  
Janusz Marcickiewicz ◽  
Solveig Tingulstad ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Lymph Node Metastasis ◽  
High Risk Patients ◽  
Node Metastasis ◽  
Risk Patients
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