PET/CT parameters as predictors of early progression risk in newly diagnosed multiple myeloma patients eligible for autologous stem cell transplantation

Abstract Introduction In recent years, the treatment of multiple myeloma (MM) has undergone substantial evolution, resulting in improved overall survival (OS) and progression-free survival (PFS). Risk-stratification strategies for MM progression are constantly being refined. Prognostic tools such as the International Staging System (ISS) and its revised version (R-ISS), cytogenetic profiling, and minimal residual disease (MRD) assessment are now routinely used. One of the most relevant directions is to augment risk stratification by incorporating imaging-derived metrics alongside clinical and laboratory factors. In this context, PET/CT offers prognostic insight in MM by evaluating both the number and location of lesions and their metabolic activity (SUV). However, there is insufficient evidence to definitively confirm the role of PET/CT–derived markers in the early identification of patients at high risk for an unfavorable clinical outcome. Methods In the Blokhin Russian Cancer Research Center, 58 patients with newly diagnosed multiple myeloma (eligible for a stem cell transplant) were enrolled in the study between 2022 and 2025. All of them received VRd regimen as induction therapy. The median age was 53.5 years (34-67), and 32 were males (55%). High-risk cytogenetic abnormalities were detected in 11 of 58 patients (19%). Disease stages were following: R-ISS: I - 31 (54%), II - 10 (18%), III – 16 (28%). Among these, 11 patients (19%) experienced early progression (PFS ≤ 9 months), whereas the remaining 47 had PFS > 12 months (median not reached) and ≥VGPR . Clinical characteristics – specifically cytogenetic risk – did not differ significantly between the two cohorts: high-risk cytogenetic abnormalities were present in 3 of 11 early progressors (27%) versus 8 of 47 sustained responders (17%).Therefore, we assessed PET/CT-derived parameters and compared metrics of the early-progression cohort with those of the sustained-response cohort. ¹⁸F-FDG PET/CT scans were performed at initial diagnosis and again both before and after consolidation/ASCT. In the absence of a universally accepted PET/CT scoring system for MM, we focused on the following key parameters: the absolute SUVₘₐₓ of the most and least metabolically active lesions and their ratio to liver SUVₘₐₓ (rSUV), the presence of soft-tissue plasmacytomas, the total number of ¹⁸F-FDG–avid sites, paramedullary and extramedullary lesions, and peripheral skeletal involvement. Continuous variables were summarized as median and interquartile range (IQR), and categorical variables as absolute and relative frequencies. Group comparisons were performed using nonparametric methods: the Mann–Whitney U test for continuous variables and Fisher's exact test for binary variables. Results Comparison of PET/CT parameters between the two patient cohorts revealed statistically significant differences in one parameter. In the early-progression cohort, the median SUVₘₐₓ of the most metabolically active lesion was 11.61 (IQR 6.80–19.87) versus 7.22 (IQR 4.22–8.47) in the good-response cohort (p = 0.0378). rSUV tended to be higher in the early-progression cohort (median 3.18 vs. 1.96; p = 0.0909), as did the prevalence of soft-tissue plasmacytomas (100% vs. 70%; p = 0.0902), indicating descriptive differences despite not reaching statistical significance; all other parameters likewise failed to reach significance. Nevertheless, these findings underscore the prognostic value of PET/CT, enabling the early identification of markers of aggressive myeloma progression and guiding optimal treatment strategies. Conclusion Limited cohort size and high inter-parameter correlations underscore the need for additional data collection, a broader range of PET/CT metrics, and the integration of clinical variables into the comparative analysis. Nevertheless, early progression detected by PET/CT highlights this modality's prognostic value; its standardization could refine disease stratification and improve treatment efficacy.