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A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence

NCT06767254 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2025-01-09

No results posted yet for this study

Summary

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

  • Multiple Myeloma (MM)

Sponsors & Collaborators

  • IRCCS Azienda Ospedaliero-Universitaria di Bologna

    lead OTHER

Principal Investigators

  • Elena Zamagni, MD, PhD · IRCCS Azienda Ospedaliero-Universitaria di Bologna

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-10-30
Primary Completion
2026-04-02
Completion
2026-08-31

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06767254 on ClinicalTrials.gov