Using machine learning to predict early recurrence in multiple myeloma patients
Official title: A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
Run by IRCCS Azienda Ospedaliero-Universitaria di Bologna · NCT06767254 · Data updated 2026-11-12
This study is testing if using machine learning can help doctors predict which patients with multiple myeloma are at higher risk for early relapse after treatment.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 200 (estimated) |
| Sponsor | IRCCS Azienda Ospedaliero-Universitaria di Bologna Academic / other |
| Locations | 4 sites (Meldola, Forlì-Cesena and 3 other locations) |
| Status | Recruiting |
| Started | October 30, 2024 |
| Main results expected | April 2, 2026 |
| Study ends | August 31, 2026 |
| Registry record updated | January 9, 2025 |
| Trial ID | NCT06767254 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are adults aged 18 years and older who have been diagnosed with active multiple myeloma.
✕Probably not a fit
Patients who do not have a diagnosis of multiple myeloma or are under 18 years of age will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to enhance risk prediction for patients with multiple myeloma (MM) by utilizing machine learning techniques to analyze clinical, genomic, and imaging data. The goal is to develop models that can accurately predict patient responses to therapy and the likelihood of early disease relapse. By integrating various data sources, the study seeks to identify high-risk patients who may not be adequately recognized by current risk stratification methods. This approach addresses the unmet clinical need for better management of MM, particularly for those at risk of rapid disease progression.
Why it matters
Potential benefit: If successful, this study could lead to improved risk assessment and personalized treatment strategies for multiple myeloma patients.
How similar studies have gone: Other studies have shown promise in using machine learning for risk prediction in various cancers, indicating potential success for this novel approach in multiple myeloma.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 18 years * Signed Informed Consent form for study participation and personal data processing * Diagnosis of active multiple myeloma Exclusion Criteria: * None
Where it's running
-
IRCCS Azienda Ospedaliero-Universitaria di Bologna
Bologna, Italy Recruiting -
Istituto Romagnolo per lo Studio dei Tumori "Dino Amadori" - IRST IRCCS
Meldola, Forlì-Cesena, Italy Not yet recruiting -
ARNAS "G. Brotzu" di Cagliari
Cagliari, Italy Not yet recruiting -
Azienda Ospedaliera Universitaria Federico II
Naples, Italy Not yet recruiting
Study contacts
- Principal investigator: Elena Zamagni, MD, PhD — IRCCS Azienda Ospedaliero-Universitaria di Bologna
- Study coordinator: Elena Zamagni, MD, PhD
- Email: e.zamagni@unibo.it
- Phone: +39 051 214 3680
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.