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IMS 2025 | Limitations of current risk stratification tools for multiple myeloma
Saurabh Zanwar, MBBS, Mayo Clinic, Rochester, MN, addresses the limitations of current risk stratification tools for multiple myeloma. Dr Zanwar highlights the heterogeneity of current tools and the importance of incorporating immune aspects and transcriptomic features of disease. This interview took place at the 22nd International Myeloma Society (IMS) Annual Meeting in Toronto, Canada.
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Transcript
Multiple myeloma is a very heterogeneous disorder and risk stratification is the heart of how we define which patients are proposed to do better versus worse. One of the challenges is the heterogeneity in various risk stratification tools that exist and there are a bunch of them out there: the revised ISS classification, the R2-ISS system, the Mayo additive scoring system, and most recently validated and hopefully a uniform tool proposed by the IMS and IMWG which will rely heavily on cytogenetic features as well as incorporating elevated beta-2 microglobulin in the presence of normal kidney function...
Multiple myeloma is a very heterogeneous disorder and risk stratification is the heart of how we define which patients are proposed to do better versus worse. One of the challenges is the heterogeneity in various risk stratification tools that exist and there are a bunch of them out there: the revised ISS classification, the R2-ISS system, the Mayo additive scoring system, and most recently validated and hopefully a uniform tool proposed by the IMS and IMWG which will rely heavily on cytogenetic features as well as incorporating elevated beta-2 microglobulin in the presence of normal kidney function. These are all risk stratification schemas that are heavily reliant on the cytogenetic features and they somewhat ignore the frailty aspect; they do not incorporate the immune aspect of a patient’s bone marrow. So, these are limitations that exist and as a result, some of the functional high-risk patients are not captured by the current risk stratification schema. We need to incorporate transcriptomic features, features like an elevated S-phase proportion, which again corroborates with proliferative phenotype, to better prognosticate patients with multiple myeloma.
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