Clinical trial · Observational
A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
NCT06767254CI-TRIAL-00084522recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Multiple Myeloma (MM) | Multiple Myeloma | CURATED_EXACT | 0.85 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Overall Response Rate
- timeFrame
- 12 months after the start of anti-MM therapy
- description
- Overall Response Rate
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Age ≥ 18 years * Signed Informed Consent form for study participation and personal data processing * Diagnosis of active multiple myeloma Exclusion Criteria: * None
References
Publications (0)
Data not yet available
No reference posted for this study.