Aller au contenu principal
Accès ouvert déclaré 2026 article

FDG-PET Medullary Total Tumor Volume Highlights High-Risk Newly Diagnosed Multiple Myeloma Patients in CASSIOPEIA Trial

0Citations signalées — pas une note de qualité
0Institutions déclarées
0Pays d’affiliation déclarés

Résumé fourni par la source

This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) derived from fluorodeoxyglucose-positron emission tomography/computed tomography ([18F]FDG-PET/CT) compared with conventional PET-derived features and biological/chromosomal abnormalities in patients with newly diagnosed multiple myeloma (NDMM) treated with daratumumab for induction/consolidation and/or maintenance and enrolled in CASSIOPET, a companion study of CASSIOPEIA (NCT02541383), with long-term follow-up. Automated bone/liver CT-based segmentation were applied to the baseline [18F]FDG-PET images, with mTMTV being defined using the median liver background as the cut-off, including focal lesions and diffuse bone marrow (BM) involvement. Both univariate/multivariate Cox and machine learning (ML)-based survival models were performed. A total of 195 patients were included, 81% of them PET-positive. Multivariate analysis demonstrated independent prognostic value of mTMTV for PFS (p<0.001) and OS (p<0.001), complementary to R-ISS (p=0.008 and p<0.001 respectively). The ML model confirmed these findings, achieving C-Index of 0.609 and 0.659 and identifying mTMTV as the most informative feature for PFS and OS. Adding R-ISS, BM SUVmax and anemia to mTMTV accounted for more than 60% of the ML model explanation for PFS and adding R-ISS, the number of focal lesions and BM SUVmax for more than 60% of the model for OS. Combining R-ISS and mTMTV enabled the creation of two new risk subgroups. In conclusion, this prospective study demonstrated the prognostic relevance of [18F]FDG-PET/CT-based parameters in the initial workup of NDMM patients in the era of anti-CD38-based therapy. mTMTV was found to have strong independent prognostic value, complementary to R-ISS and refining risk stratification.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Contrôle bibliographique ouvert

Aucun DOI disponible pour le contrôle Crossref.

Sujets associés

Multiple Myeloma Research and TreatmentsGlioma Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging

BNTIC News n’est pas le producteur de ces données. Recherche à la demande dans Crossref et Europe PMC, sans clé ; OpenAlex reste optionnel. Aucun service payant requis, aucune réponse conservée. Sources et limites.