IMS 2023 | Criteria used to define high-risk SMM and how this is being improved
Irene Ghobrial, MD, Dana-Farber Cancer Institute, Boston, MA, discusses the clinical criteria used to define high-risk smoldering multiple myeloma (HR-SMM), and shares insights into the PANGEA model, which uses dynamic changes in M-spikes and free light chain (FLC) levels to predict the risk of progression from SMM to multiple myeloma. This interview took place at the 20th International Myeloma Society (IMS) Annual Meeting, held in Athens, Greece.
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Transcript (edited for clarity)
High-risk smoldering myeloma and the definition is very critical these days. Especially if we want to decide who will go on therapy and who should not go on therapy and may have a good long-term outcome without actually being treated. We have clinical criteria, like the 2/20/20 we have some Spanish criteria and other criteria. We recently published the PANGEA model and that’s based on a dynamic model of progression, so instead of using just one number at the time that you’re diagnosed, can I serially follow up the evolving numbers, the evolving M-spike, the evolving light chain, and that gives you the biology of the disease...
High-risk smoldering myeloma and the definition is very critical these days. Especially if we want to decide who will go on therapy and who should not go on therapy and may have a good long-term outcome without actually being treated. We have clinical criteria, like the 2/20/20 we have some Spanish criteria and other criteria. We recently published the PANGEA model and that’s based on a dynamic model of progression, so instead of using just one number at the time that you’re diagnosed, can I serially follow up the evolving numbers, the evolving M-spike, the evolving light chain, and that gives you the biology of the disease. Now, we would like to layer on it much more than that. We know that the cytogenetics are important, we know now that circulating tumor cells are important. We are incorporating our genomic data, our immune data, circulating tumor cells, with the clinical markers, so that a patient can put all those markers into their app, and they can have their own risk stratification, a personalized risk stratification. It’s critical so that we don’t over-treat or under-treat certain patients.
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