Evaluating the Risk of Postoperative Venous Thromboembolism in Cervical Cancer Patients

Development and Validation of Machine Learning Models to Evaluate the Postoperative Venous Thromboembolism Risk of Cervical Cancer Patients in China

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06556953

Enrollment

1174

Registered

2024-08-16

Start date

2019-01-01

Completion date

2023-12-31

Last updated

2024-08-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Venous Thromboembolism

Keywords

machine learning, postoperative VTE, cervical cancer

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

20 Years to 89 Years

Healthy volunteers

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.

Design outcomes

Primary

Measure	Time frame	Description
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.

Countries

China

Outcome results