Navigating the evolving management of smoldering multiple myeloma
M Bakri Hammami1,2, Rafael R Canevarolo3, Ariosto S Silva3
1Department of Hematology and Oncology Moffitt Cancer Center and Research Institute Tampa Florida USA.
Hemasphere
|January 12, 2026
Summary
Smoldering multiple myeloma (SMM) is a precursor to symptomatic multiple myeloma (MM). Advanced biomarkers and genomic profiling improve risk prediction, moving beyond traditional models for better patient management.
Area of Science:
- Hematology
- Oncology
- Immunology
Background:
- Smoldering multiple myeloma (SMM) is an intermediate stage between monoclonal gammopathy of undetermined significance (MGUS) and symptomatic multiple myeloma (MM).
- Risk stratification for SMM progression to MM historically relied on static clinical markers, which failed to capture disease heterogeneity.
- Understanding SMM's biological complexity is crucial for accurate prognosis and management.
Purpose of the Study:
- To review the evolution of SMM risk assessment from clinical to biological markers.
- To highlight emerging tools and strategies for improved SMM risk prediction and patient outcomes.
- To discuss the shift towards personalized medicine in SMM management.
Main Methods:
- Review of current literature on SMM progression and risk stratification.
- Analysis of advancements in biomarkers, cytogenetics, and genomic profiling.
- Discussion of evolving clinical trial strategies and personalized medicine approaches.
Main Results:
- Traditional risk models based on tumor burden are limited.
- Dynamic biomarkers, cytogenetics, and genomic profiling offer a more nuanced understanding of SMM progression.
- Immune dysregulation and subclonal evolution are identified as key drivers of progression.
- Early therapeutic interventions are being explored for high-risk SMM.
Conclusions:
- Integrating molecular, immunologic, and clinical data is essential for refining SMM management.
- Biologically informed risk models are improving prognostic accuracy.
- Personalized medicine approaches hold promise for optimizing SMM patient care.
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