One of the good presentations we’ve had here, which we’ve done as a sort of consortium with the people at Mayo and at MSK, is to really look at the pattern of mutations present in the different myeloma precursor states to understand how you might better identify patients who are destined to progress to myeloma or those who are destined to stay in the precursor stages. And so to just sum up a long story, I think you can integrate the pattern of mutations with the 2-20-20 classifier to really hone down on the different subgroups of precursors and then use those to identify ones more likely to progress and a group of patients that lacks genomic features of myeloma that really is destined to stay stable forever...
One of the good presentations we’ve had here, which we’ve done as a sort of consortium with the people at Mayo and at MSK, is to really look at the pattern of mutations present in the different myeloma precursor states to understand how you might better identify patients who are destined to progress to myeloma or those who are destined to stay in the precursor stages. And so to just sum up a long story, I think you can integrate the pattern of mutations with the 2-20-20 classifier to really hone down on the different subgroups of precursors and then use those to identify ones more likely to progress and a group of patients that lacks genomic features of myeloma that really is destined to stay stable forever. And at some level, what would be really good about that is to find those people that are genomically simple and then never treat them, don’t follow them up, because you can be pretty sure that they’ll never transition to a clinical phase disease. So I think there’s a lot of promise for integrating molecular diagnostics into the management of smoldering myeloma and the definition of high-risk smoldering myeloma.
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