System to Evaluate the Risk of Lymph Node Metastasis Preoperatively in Cervical Cancer

Completed

• Conditions: Cervical Cancer

• Registration Number: NCT06032481
• Lead Sponsor: Fujian Maternity and Child Health Hospital

Brief Summary

The lymph node status is difficult to be assessed preoperatively, this study aimed to develop a scoring system for predicting the risk of LNM in cervical cancer patients before operation.

Detailed Description

Lymph nodes metastasis (LNM) was proved to be a critical risk factor related to the survival to cervical cancer survival. However, preoperative pelvic magnetic resonance imaging (MR) or computed tomography (CT) tests are less sensitive to assess the risk of lymph node metastasis. PET-CT is too expensive and radiative to be widely used in clinical practice. A model was constructed based on clinical indicators to predict lymph node metastasis preoperatively, providing a reference for clinical treatment.

Study Timeline

• Study Start: 2012-01-01
• Primary Completion: 2019-12-01
• Study Completion: 2023-03-15
• Study First Submitted: 2023-08-26
• Status Verified: 2023-09
• Study First Submitted QC: 2023-09-04
• Last Update Submitted: 2023-09-04
• Study First Posted: 2023-09-13
• Last Update Posted: 2023-09-13

Recruitment & Eligibility

• Status: COMPLETED
• Sex: Female
• Target Recruitment: 426

Inclusion Criteria

• Clinical diagnosis of cervical cancer
• FIGO stage IB1-IIA1
• Undergone radical hysterectomy with pelvic lymphadenectomy
• Peformed pelvic MRI examination preoperatively

Exclusion Criteria

• Had distant metastases diagnosed before or during the surgery
• Underwent neoadjuvant radiotherapy preoperatively
• Underwent neoadjuvant chemotherapy preoperatively
• Incomplete or inaccuratemedical records

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Overall survival	60 months	death or loss of follow-up

Secondary Outcome Measures

Name	Time	Method
The accuracy of the model	60 months	The AUC curve was used to assess the discrimination of the scoring system. The comparison between predicted (mean ± SD) and observed rates of LNM was used to test the calibration. The Hosmer-Lemeshow test evaluated the model fit.
Risk factors influenced LNM	60 months	A multivariable logistic regression analysis was used to analysis the independent factors that contribute to LNM.