Evaluating the Risk of Postoperative Venous Thromboembolism in Cervical Cancer Patients

Completed

• Conditions: Venous Thromboembolism

• Registration Number: NCT06556953
• Lead Sponsor: Haike Lei

Brief Summary

The aim of this study is to develop a machine learning model to accurately predict the risk of venous thromboembolism in patients with cervical cancer after surgery.

Detailed Description

Venous thromboembolism (VTE) is a common and life-threatening complication in patients with cervical cancer following surgery. The objective of this study is to develop a machine learning model with the potential to predict the risk of VTE in these patients postoperatively. We plan to employ partial dependence (PD) curves, breakdown (BD) curves, Ceteris-paribus (CP), and SHapley additive exPlanations (SHAP) values for a comprehensive analysis. The goal is to explore how different machine learning algorithms can be utilized as tools for personalized postoperative VTE risk assessment in cervical cancer patients.

Study Timeline

• Study Start: 2019-01-01
• Primary Completion: 2023-12-31
• Study Completion: 2023-12-31
• Status Verified: 2024-08
• Study First Submitted: 2024-08-06
• Study First Submitted QC: 2024-08-15
• Last Update Submitted: 2024-08-15
• Study First Posted: 2024-08-16
• Last Update Posted: 2024-08-16

Recruitment & Eligibility

• Status: COMPLETED
• Sex: Female
• Target Recruitment: 1174

Inclusion Criteria

• Confirmation of cervical cancer through pathological examination.
• Receipt of surgical treatment for cervical cancer at Chongqing University Cancer Hospital in China.
• Provision of comprehensive case information.

Exclusion Criteria

• Patients under the age of 18.
• History of VTE caused by other reasons before surgery.
• Secondary cervical cancer or accompanying primary malignant tumor.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Whether the patient has developed VTE is determined based on the diagnostic criteria in the "Guidelines for the Prevention and Treatment of Tumor-Associated Venous Thromboembolism (2019 Edition)."	December 31, 2023	The diagnosis of VTE primarily includes the diagnosis of DVT and PE. According to the guidelines, DVT is diagnosed using venous compression ultrasound or venography, while PE is diagnosed using CT pulmonary angiography (CTPA) or nuclear lung ventilation/perfusion imaging.

Trial Locations

Locations (1)

Chongqing University Cancer Hospital; 🇨🇳 Chongqing, Chongqing, China