Spots Global Cancer Trial Database for Predictors of Para-aortic Lymph Node Metastasis of Cervical Cancer

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Trial Identification

Brief Title: Predictors of Para-aortic Lymph Node Metastasis of Cervical Cancer

Official Title: Predictors of Para-aortic Lymph Node Metastasis in Patients With Locally Advanced Cervical Cancer Based on the Pooled Analysis of Surgical Staging Results

Study ID: NCT05717751

Conditions

Locally Advanced Cervical Cancer

Interventions

surgical staging

Study Description

Brief Summary: The goal of this observational study is to identify predictive factors and to develop a risk model predicting para-aortic lymph node metastasis in patients with locally advanced cervical cancer based on the analysis of surgical staging results. The main questions it aims to answer are: * What are the risk factors to predict para-aortic lymph node metastasis in patients with locally advanced cervical cancer? * What is the indication for prophylactic extended-field radiation therapy in patients with locally advanced cervical cancer Individual data of patients with locally advanced cervical cancer treated with surgical staging at our institution from 2020 to 2022 were pooled analysed.Multivariate Logistic regression analysis was used to identify the predictive factors and to develop the prediction model.

Detailed Description: Individual data of 336 patients with locally advanced cervical cancer treated with surgical staging at our institution from January 2020 to August 2022 were pooled analysed. The following factors were collected from each patient to identify variables predicting para-aortic lymph node metastasis: age, T-staging，histopathological type，tumor size, differentiation, pretreatment tumor markers (squamous carcinoma antigen, carcinoembryonic antigen, Carbohydrate antigen 125 and cytokeratin fragment 21-1 , human papilloma virus type, the status of pelvic lymph node on images, common iliac lymph node and the short-axis diameter of the largest positive and the status of para-aortic lymph node on surgical staging results. Multivariate Logistic regression analysis was used to develop the prediction model. A simplified scoring system for each independent predictive factors was developed according to its coefficient. Internal validation was performed to assess the model. An independent validation cohort contained 116 patients with the same criteria from March 2018 to December 2019.