External Validation of the CLOVER Score for Detecting Occult Cancer in Venous Thromboembolism Patients

NCT ID: NCT07310693

Last Updated: 2025-12-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-12-01

Study Completion Date

2028-12-31

Brief Summary

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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.

Detailed Description

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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 combines a retrospective and a prospective cohort.

Retrospective cohort:

Patients aged ≥18 years with objectively confirmed symptomatic deep vein thrombosis (DVT) and/or pulmonary embolism (PE) diagnosed between January 1, 2000, and August 31, 2022, in participating hospitals across Spain will be included. Patients from centers involved in the model derivation (Hospital Universitario Infanta Leonor and Hospital Universitario de Fuenlabrada) will be excluded. Cases are defined as patients with a histologically confirmed cancer diagnosis occurring between 1 and 24 months after the index VTE event. Controls are defined as patients without a cancer diagnosis during the same period. All variables required for the CLOVER model (age, D-dimer, systolic blood pressure, ALT, hemoglobin, creatinine, total cholesterol, platelet count, triglycerides, leukocyte count, weight, chronic lung disease, heart rate, sex, and previous VTE recurrence) will be extracted from electronic health records using a standardized data collection form. The CLOVER model will be applied to each patient to assess its discrimination for cancer prediction in the retrospective cohort.

Prospective cohort:

From December 1, 2025, to December 31, 2027, consecutive adult patients with objectively confirmed symptomatic VTE will be recruited in participating hospitals. All patients will undergo a standard clinical evaluation including medical history, physical examination, basic laboratory testing (complete blood count and biochemistry), chest X-ray, and age- and sex-appropriate cancer screening tests according to clinical practice guidelines. The CLOVER score will be calculated at the time of VTE diagnosis using a dedicated web-based tool (CLOVER-Web). Patients will be classified as "low risk" or "high risk" based on the optimal F1-score threshold (0.487), corresponding to a sensitivity of 51%, specificity of 95%, PPV of 46%, and NPV of 96%. All participants will be followed for at least two years to determine whether an occult cancer is diagnosed. Further diagnostic testing for suspected cancer will be performed at the discretion of the treating physician, regardless of CLOVER result.

Model performance and bias assessment:

The external validation will evaluate model discrimination using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the ROC curve (AUC). Additional analyses will assess potential prediction bias across demographic and clinical subgroups (e.g., age, sex, comorbidities). Model calibration and temporal performance will also be reviewed, with predefined procedures for identifying deviations from expected behavior. Weekly reports during the prospective phase will alert investigators to performance drift or potential implementation issues in the web-based tool.

Clinician satisfaction:

A secondary objective is to evaluate clinician satisfaction with the CLOVER-Web tool. An online questionnaire specifically designed for this study will be administered to participating clinicians to assess usability, clarity, and clinical utility.

Ethical considerations:

The study follows the Declaration of Helsinki and Spanish regulations on biomedical research and data protection. Retrospective data collection will request exemption from informed consent due to the use of anonymized clinical information. Prospective participants will provide written or electronic informed consent. All data will be pseudonymized and stored securely.

Conditions

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Venous Thromboembolism (VTE) Occult Cancer

Keywords

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Occult Cancer Venous thromboembolism Machine learning Prediction model External validation CLOVER score

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Prospective VTE Cohort

Adults with objectively confirmed symptomatic venous thromboembolism (deep vein thrombosis and/or pulmonary embolism) consecutively enrolled from December 2025 to December 2027 in participating hospitals. All participants will undergo routine clinical evaluation, laboratory testing, and cancer screening according to standard practice. The CLOVER score will be calculated at baseline using the web-based tool (CLOVER-Web).

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* 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 Criteria

* 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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Fundación para la Investigación e Innovación Biomédica del Hospital Universitario Infanta Leonor

UNKNOWN

Sponsor Role collaborator

Infanta Leonor University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Anabel Franco Moreno

Specialist in Internal Medicine

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Anabel Franco-Moreno, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Hospital Universitario Infanta Leonor

Franco-Moreno, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Hospital Universitario Infanta Leonor

Locations

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Hospital Clínic

Barcelona, Barcelona, Spain

Site Status RECRUITING

Hospital Universitario Infanta Leonor

Madrid, Madrid, Spain

Site Status RECRUITING

Hospital Universitario La Paz

Madrid, Madrid, Spain

Site Status RECRUITING

Hospital Universitario Príncipe de Asturias

Madrid, Madrid, Spain

Site Status RECRUITING

Hospital Universitatio del Sureste

Madrid, Madrid, Spain

Site Status RECRUITING

Hospital Universitario de Móstoles

Madrid, Madrid, Spain

Site Status RECRUITING

Hospital Clínico Universitario Virgen de la Arrixaca

Murcia, Murcia, Spain

Site Status RECRUITING

Hospital Universitario Morales Meseguer

Murcia, Murcia, Spain

Site Status RECRUITING

Hospital San Agustín

Avilés, Principality of Asturias, Spain

Site Status RECRUITING

Hospital Universitario Son Llatzer

Balea, , Spain

Site Status RECRUITING

Hospital Universitario 12 de Octubre

Madrid, , Spain

Site Status RECRUITING

Hospital Universitario de Fuenlabrada

Madrid, , Spain

Site Status RECRUITING

Countries

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Spain

Central Contacts

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Anabel Franco Moreno, MD, PhD

Role: CONTACT

Phone: +34686102661

Email: [email protected]

Anabel Franco Moreno

Role: CONTACT

Phone: MD, PhD

Email: [email protected]

Facility Contacts

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JESUS AIBAR, MD, PhD

Role: primary

Anabel Franco Moreno, MD, PhD

Role: primary

Teresa Sancho, MD

Role: primary

f garcia sanchez, MD

Role: primary

Ana Mancebo Plaza, MD

Role: primary

Andrea Pérez, MD

Role: primary

Leticia Guirado Torrecillas, MD

Role: primary

Javier Pagán, MD, PhD

Role: primary

José Ferreiro Celeiro, MD

Role: primary

Elena Cisneros de la Fuente, MD

Role: primary

Jose Bascuñana Morejon de Giron, MD, PhD

Role: primary

Cristina De Ancos Aracil, MD

Role: primary

References

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Franco-Moreno A, Madronal-Cerezo E, de Ancos-Aracil CL, Farfan-Sedano AI, Munoz-Rivas N, Bascunana Morejon-Giron J, Ruiz-Giardin JM, Alvarez-Rodriguez F, Prada-Alonso J, Gala-Garcia Y, Casado-Suela MA, Bustamante-Fermosel A, Alfaro-Fernandez N, Torres-Macho J; CLOVER Research Group. Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study. Medicina (Kaunas). 2024 Dec 27;61(1):18. doi: 10.3390/medicina61010018.

Reference Type BACKGROUND
PMID: 39859000 (View on PubMed)

Other Identifiers

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CLOVER_validation

Identifier Type: -

Identifier Source: org_study_id