External Validation of the CLOVER Score for Detecting Occult Cancer in Venous Thromboembolism Patients
External Validation of a Predictive Model for Occult Cancer Risk in Patients With Venous Thromboembolism Developed Using Machine Learning
Infanta Leonor University Hospital
500 participants
Dec 1, 2025
OBSERVATIONAL
Conditions
Summary
This study aims to externally validate the CLOVER score, a machine learning-based predictive model designed to identify patients with venous thromboembolism (VTE) who are at increased risk of having an occult cancer. The study includes a retrospective cohort of patients with acute symptomatic VTE diagnosed between 2000 and 2022, and a prospective cohort of consecutively recruited patients from December 2025 to December 2027. The CLOVER model will be applied to all participants, and its ability to discriminate between patients with and without occult cancer will be evaluated. The study also assesses clinicians' satisfaction with the web-based tool (CLOVER-Web) developed to facilitate the use of the score in clinical practice.
Eligibility
Inclusion Criteria3
- Age ≥18 years.
- Objectively confirmed acute symptomatic venous thromboembolism (deep vein thrombosis and/or pulmonary embolism).
- Ability to provide written or electronic informed consent.
Exclusion Criteria3
- Suspicion of cancer during the initial diagnostic evaluation for VTE.
- Participation in another interventional study that may interfere with outcomes.
- Inability or refusal to provide informed consent.
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Locations(12)
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NCT07310693