Evaluation of factors influencing lymph node metastasis in endometrial cancers: A retrospective study.

Deepak Bose, P Rema, S Suchetha,Dhanya Dinesh, J Sivaranjith, T R Preethi,Aleyamma Mathew

Indian journal of cancer(2024)

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摘要
OBJECTIVES:The role of lymphadenectomy in the management of early endometrial cancer remains controversial. The aim of our study was to evaluate risk factors associated with nodal metastases in endometrial cancer and to devise a predictive risk model based on the significant risk factors in predicting node metastasis. MATERIALS AND METHODS:A retrospective study was conducted on women diagnosed with uterus-confined endometrial cancer, and who underwent surgical staging with pelvic and/or paraaortic lymphadenectomy from our center during July 1, 2017 to June 30, 2019. Clinical details, Magnetic Resonance imaging (MRI)-detected myometrial invasion, and pre and post-operative histological details of tumor were correlated with pelvic and/or para-aortic lymph node metastasis. Risk factors were assessed using logistic regression model and risk models devised. RESULTS:128 patients were included in the study. Paraaortic lymphadenectomy was done in 72.7% patients. Nodal metastasis was seen in 14.8% of patients. Logistic regression analyses revealed lymphovascular invasion (P = 0.002), parametrial involvement (P = 0.017) and nonendometrioid histology (P = 0.004) to be significant risk factors. Tumor size >2 cm, grade 3 and deep myometrial invasion had higher risk for nodal metastasis, although non-significant. Risk models were derived with sensitivity of 79-89.5%, specificity of 58.7-69.7%, Negative predictive value (NPV) of 95-97% and accuracy of 63-71%. CONCLUSION:Lymphovascular invasion, nonendometrioid histology and parametrial involvement are independent predictors of lymph node metastasis in endometrial cancer. Risk models using these risk factors can better predict the risk of nodal metastasis and thus avoid lymph node dissection in low risk patients. Our risk models had reasonably good sensitivity in nodal metastasis prediction and require further validation.
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