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

Sponsor
Grand Hôpital de Charleroi
Study ID
NCT07546188
Status
Recruiting
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Conditions

  • Care Coordination
  • Lymphoma, Non-Hodgkin

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Retrospective Group — OTHER
    For the retrospective group of 20 patients.
  • Prospective Group — OTHER
    Follow-up of the patients for the prospective group

Study Details

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.

Key Dates

First listed
Apr 22, 2026
Start date
Feb 15, 2026
Status verified
Apr 2026
Primary completion
Dec 31, 2027
Completion
Feb 15, 2029

Study Design

Enrollment
210 participants (estimated)

Arms

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

Primary Outcome Measure

ROC-AUC [ Time Frame: 2027 ]

Central Contacts

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