NCT07439991

Study of Risk Factors and Prediction of Blood Clots After Lung Cancer Surgery

Prospective Cohort Study on Risk Factors and Machine Learning-Based Prediction of Postoperative Venous Thromboembolism in Patients Undergoing Lung Cancer Surgery

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 900 (estimated)
• Sponsor: The First Hospital of Jilin University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to learn about the risk factors and prediction of postoperative venous thromboembolism (VTE) in patients undergoing lung cancer surgery. The main question it aims to answer is: Which clinical, surgical, and laboratory factors are associated with the development of postoperative deep vein thrombosis (DVT) in lung cancer surgery patients, and can machine learning models accurately predict individual risk? Participants undergoing lung cancer surgery will be prospectively followed for 30 days after surgery. Perioperative clinical data, laboratory results, and imaging findings will be collected to identify VTE risk factors and to develop a predictive model.

Conditions

• Lung Cancer (Diagnosis)
• Deep Vein Thrombosis (DVT)
• Venous Thromboembolism (VTE)

Interventions

Type	Name	Description
OTHER	Prospective Perioperative Data Collection	The intervention involves the prospective collection of perioperative clinical, laboratory, and imaging data from adult patients undergoing lung cancer surgery. No therapeutic or diagnostic procedures beyond standard care are applied. Collected data will be used to identify risk factors for postoperative deep vein thrombosis (DVT) and to develop machine learning-based predictive models.

Timeline

• Start date: 2024-11-01
• Primary completion: 2029-11-01
• Completion: 2029-11-30
• First posted: 2026-02-27
• Last updated: 2026-02-27

Locations

1 site across 1 country: China