AI-based Predictive and Interventional System for Early Detection of Non-compliance Risks With Oral Therapies in Lymphoma Patients.

NCT07546188 | Recruiting DMC

• 1 other identifier: LNH-AI-Tools
• Study Type: observational
• Target: 210
• Locations: 1 country
• Sites: 1

Brief Summary

This research forms part of a continuous quality improvement initiative. It aims to assess patient compliance of oral therapies by artificial intelligence. It could overcome the limitations of current practices and enhance the responsiveness and accuracy of clinical interventions.

Conditions

Lymphoma, Non-Hodgkin; Care Coordination

Keywords

Artificial intelligence; Non-Hodgkin lymphoma; Care pathway

Outcome Measures

Primary Outcomes (1)

• ROC-AUC

  Description: ROC-AUC : Receiver Operating Characteristic - Area Under the Curve is a performance metric for binary classification prediction algorithms. ROC Curve: Plots the True Positive Rate (sensitivity) against the False Positive Rate (1-specificity) at various classification thresholds. AUC: The area under this curve (ranging from 0 to 1). A higher AUC indicates better model performance-1.0 is perfect, 0.5 is random guessing. ROC-AUC evaluates how well the model distinguishes between classes, regardless of the classification threshold. Time Frame: When the data will be avalaible, at the end of 2027

  2027

Secondary Outcomes (1)

• F1-score

  When the data will be avalaible, at the end of 2027

Other Outcomes (1)

• Recall for the positive class

  2027

Study Arms (2)

Retrospective cohort

A retrospective cohort from 2019 to 2024 comprising 350 lymphoma patients who were monitored on an empirical basis.

Other: Retrospective Group

Prospective cohort

A prospective cohort study involving up to 210 consecutive patients, starting in November 2025, with the aim of developing a decision-support tool using machine learning.

Other: Prospective Group

Interventions

Retrospective Group OTHER

For the retrospective group of 20 patients.

Retrospective cohort

Prospective Group OTHER

Follow-up of the patients for the prospective group

Prospective cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients treated in the Haematology Department at Charleroi General Hospital for Non-Hodgkin lymphoma.

You may qualify if:

• All patients aged 18 and over who are treated in the Haematology Department at the Grand Hôpital de Charleroi from November 2025 onwards
• Treated for a lymphoma, Non Hodgkin
• Capable of giving informed consent

You may not qualify if:

• All other patients who did not meet the eligibility criteria

Sponsors & Collaborators

• Grand Hôpital de Charleroi: lead

Study Sites (1)

Grand Hôpital de Charleroi

Charleroi, Hainaut, 6060, Belgium

RECRUITING

MeSH Terms

Conditions

Lymphoma, Non-Hodgkin

Condition Hierarchy (Ancestors)

Lymphoma; Neoplasms by Histologic Type; Neoplasms; Lymphoproliferative Disorders; Lymphatic Diseases; Hemic and Lymphatic Diseases; Immunoproliferative Disorders; Immune System Diseases

Study Officials

• Marie Detrait, MD, PhD

  Grand Hôpital de Charleroi

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Marie Detrait, MD, PhD

CONTACT

0032 60 11 20 08; marie.detrait@ghdc.be

Aline Gillain, MedSciences

CONTACT

0032 60 11 00 89; aline.gillain@ghdc.be

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 8, 2026
• First Posted: April 22, 2026
• Study Start: February 15, 2026
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): February 15, 2029
• Last Updated: April 22, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

BE (1)