This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) derived from fluorodeoxyglucose-positron emission tomography/computed tomography (18FFDG-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 18FFDG-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 (p0.001) and OS (p0.001), complementary to R-ISS (p=0.008 and p0.001 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 18FFDG-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.
Bastien et al. (2026) studied this question.