This is a retrospective, observational, single-center study conducted at the Hematology Unit of the IRCCS Azienda Ospedaliero-Universitaria di Bologna. The study aims to integrate genomic, clinical, and imaging data-all previously collected and pseudonymized-from earlier spontaneous studies carried out by the Hematology Unit. The main goal is to explore how genetic, clinical, and imaging features relate to disease outcomes and to develop predictive models using artificial intelligence (AI) and machine learning (ML). These models may help forecast disease progression and treatment response in the future. By combining different types of data, the research team hopes to develop new methods to predict disease progression and treatment outcomes. No new procedures, tests, or patient visits are required for this study. All the information analyzed will come from existing data collected as part of past clinical practice or previous research projects. Once anonymized, it will no longer be possible to identify individual patients. The anonymized dataset will be securely developed and stored by the bioinformatics team at the Hematology Unit of IRCCS AOUBO.

Inclusion Criteria:

• Age ≥18 years
• Signed Informed Consent
• Patients with confirmed diagnosis of MM, previously enrolled in spontaneous trial conducted at the UOC Ematologia, IRCCS AOU di Bologna, from 2021, for whom pseudonymized datasets are already available at the start of this study.

Exclusion Criteria:

• None

Existent pseudonymized data have been collected from adult patients (i.e., aged ≥18 years) with a confirmed diagnosis of active MM, according to the International Myeloma Working Group (IMWG) criteria. All patients whose data will be anonymized have previously been enrolled in spontaneous trials conducted from 2021 at the UOC Ematologia, IRCCS AOUBO. No further data collection is required other than data already collected both at diagnosis and after treatment in the context of previous studies, upon anonymization.