Machine Learning to Predict Early Relapse in Multiple Myeloma
Uses machine learning to predict treatment response and early relapse in adults with myeloma.
Plain-language title generated from the registry record
Registry title: A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
Key facts
- Where
- Bologna, Cagliari, Meldola, and Naples, ItalySee the 4 sites
Where in Italy
- IRCCS Azienda Ospedaliero-Universitaria di BolognaBologna, ItalyTaking people
- ARNAS "G. Brotzu" di CagliariCagliari, ItalyNot yet recruiting
- Istituto Romagnolo per lo Studio dei Tumori "Dino Amadori" - IRST IRCCSMeldola, ItalyNot yet recruiting
- Azienda Ospedaliera Universitaria Federico IINaples, ItalyNot yet recruiting
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- IRCCS Azienda Ospedaliero-Universitaria di Bologna
- Trial code
- NCT06767254
- Record updated
- 9 January 2025
- Original description
This is a non-interventional, national, multicenter prospective non-profit observational study aiming at improving the accuracy of risk prediction in multiple myeloma (MM) by applying machine-learning tools for data processing to develop model(s) predicting response to therapy and the probability of early relapse for MM patients.Read full original descriptionShow less
A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
This is a non-interventional, national, multicenter prospective non-profit observational study aiming at improving the accuracy of risk prediction in multiple myeloma (MM) by applying machine-learning tools for data processing to develop model(s) predicting response to therapy and the probability of early relapse for MM patients.
Inclusion: Age ≥ 18 years; Signed Informed Consent form for study participation and personal data processing; Diagnosis of active multiple myeloma.
Exclusion: None.