FDG-PET Medullary Total Tumor Volume Highlights High-Risk Newly Diagnosed Multiple Myeloma Patients in CASSIOPEIA Trial.
Authors
Affiliations (22)
Affiliations (22)
- Centre Hospitalier Universitaire De Nantes, NANTES, France.
- University Hospital of Nantes, Nantes, France.
- Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, France.
- Université de Toulouse, CHU Toulouse, Toulouse, France.
- CHU Bordeaux, Hopital haut Leveque, centre François Magendie, PESSAC, France.
- Institut Cancerologie de Bourgogne, Dijon, France.
- Centre Hospitalier Universitaire (CHU) Lille, Service des Maladies du Sang, University of Lille, Lille, France.
- Hopital La Miletrie, Poitiers, France.
- Hopital Henri Mondor, Creteil, France.
- CHU Henri Mondor, Creteil, France.
- Hôpital Lyon Sud, Pierre-benite, France.
- Nantes University Hospital, Nantes, France.
- Department of Internal Medicine, Albert Schweitzer hospital, Dordrecht, the Netherlands., Dordrecht, Netherlands.
- UMC Utrecht, Utrecht, Netherlands.
- CHU Nantes.
- University Medical Center Utrecht, Utrecht, Netherlands.
- Unité de Genomique du Myélome, IUC- T Oncopole, TOULOUSE, France.
- Erasmus MC Cancer Institute, Department of Hematology, Rotterdam, United States.
- Ecole Centrale de Nantes, Nantes, France.
- Hematology, University Hospital Hôtel-Dieu, Nantes, France.
- University hospital, Nantes, France.
- Nantes Université, CHU Nantes, Nantes Cedex 1, France.
Abstract
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.