Understanding the Evolution of Risk Stratification for Smoldering Myeloma

More and more evidence is developing on the opportunity to treat smoldering myeloma, but in order to weigh the benefit vs the toxicity of treatment, fully understanding the likelihood of progression to symptomatic multiple myeloma is vital.

During a Case-Based Roundtable event in La Jolla, California, moderator Caitlin Costello, MD, hematologist and professor of medicine at UC San Diego Health, reviewed the current definitions of smoldering and multiple myeloma and the datasets that show the risk patients have of progression in 2 years and beyond, drawing from both laboratory values and cytogenetics. Using these risk stratification systems can identify high-risk patients who could benefit from the recent FDA approval of daratumumab (Darzalex and other treatments being used in clinical trials and in the real world.

This is the second of 2 parts. Read part 1.

Register today to join a Case-Based Roundtable near you.

Targeted Oncology: Could you discuss the definitions of smoldering myeloma and progression to multiple myeloma?

Caitlin Costello, MD: For all intents and purposes, as of 2014 [the SLiM CRAB criteria] is our definition of myeloma, very specifically, different from smoldering myeloma.¹ Smoldering myeloma is having its moment right now, thanks to the FDA, where we are now trying to understand how and if we should treat it. Thinking about smoldering myeloma, we have long wondered to say, “It’s a 50/50 chance of progressing into myeloma over the next 5 years, and after 5 years, maybe it's only 10% more people, and after that, maybe it's only 1% more people.”

But that's kind of vague, and I think patients don't really appreciate saying “It's 50/50 in 5 years.” Wouldn't it be nice if we could home in a little bit? The IMWG [International Myeloma Working Group] 2/20/20 rule was developed to help better risk stratify our [patients with smoldering myeloma]. Can we really get a better sense of, instead of just 5 years of waiting [for] a 50/50 [chance], can we get a sense that in these first couple of years, there is a higher or lower risk for those patients?

That's where the M-spike of greater than 2 g/dL, the ratio of greater than 20 [free light chains], or the bone marrow plasma cells of greater than 20% was initially introduced as a new risk stratification profile.² Zero [risk factors] was low risk, 1 was low-intermediate risk, 2 or more [was intermediate], which does allow you to incorporate in the light chain-only [disease]. That way you can say you have low, intermediate, or high risk for developing multiple myeloma. To further improve it, they started adding in the risk factors of different genetics and the FISH abnormalities, which now we finally have 4 discrete groups of patients that we can actually have a conversation with patients and say, “This is where you lie. This is what your future looks like or doesn't look like.”

How does this risk stratification help with counseling patients about treatment?

We've all had our [patients with smoldering myeloma] who either [appreciate] the smoldering diagnosis because they can do absolutely nothing and just sit and watch, and we have the complete opposite, who will sit there and sweat it out every moment of every day…. I found this to be helpful, at least to some regard, to understand that that the low-risk group has a very low risk of progression. If you have none of these risk factors, at least you can tell these patients your risk of progressing in 2 years is [only] 6% vs people with high risk [with 63.1% risk]. If you're in that group, it exponentially rises there in the beginning of those first couple years, where afterwards, we're not in the clear, but we're feeling a little bit better. It's nice to at least have some risk stratification profile where we can really personalize this a little better, as opposed to saying all comers are 50/50.

How have genomics been incorporated into this risk stratification?

Other people are trying to say, are there other criteria we should be looking at? Should we be incorporating more of our genomic profiling? Can we look at different ways to include that into our IMWG data sets already, so that we can have some training[and] validation sets? …The Mayo Clinic and [The University of Texas] MD Anderson [Cancer Center] put theirs in there, to say, are there specific genomic drivers?³ Are there some that have no genomic drivers? [They are trying to] understand how we myeloma physicians can catch up with the rest of oncology, to incorporate in some of these genetic or genomic abnormalities, which we have historically not done terribly well.

Then there is the PANGEA model, which is trying to say, can we have this more continuous model that is…one when you're first diagnosed, we plug it into a dataset to say, from the moment you're diagnosed today, over these next 2 years, this is what your risk is. But what if comes in the in the fifth year?⁴ Are we not in the clear? Can we look for something that's more dynamic and incorporate in those most recent data points to say, this is what our risk is looking like moving forward, as opposed to just starting at the starting line and say this is what the next 2 years look like? This allows it to be a little bit more dynamic, which I think a lot of patients want. They want to say, “You told me [to be observed for] 2 years, we're at 3 years. Am I good?” We can start plugging in some of this information to say, we think that your risk is a little bit further out than others.

Register today to join a Case-Based Roundtable near you.

_{DISCLOSURES: Costello previously reported receiving research funding to her institution from AstraZeneca, Bristol Myers Squibb, Janssen, Takeda, Kite, Poseida, and Pfizer; and honoraria from AstraZeneca, Bristol Myers Squibb, Janssen, and Pfizer.}

REFERENCES

1. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538-e548. doi:10.1016/S1470-2045(14)70442-5

2. Mateos MV, Kumar S, Dimopoulos MA, et al. International Myeloma Working Group risk stratification model for smoldering multiple myeloma (SMM). Blood Cancer J. 2020;10(10):102. Published 2020 Oct 16. doi:10.1038/s41408-020-00366-3

3. Maura F, Bergsagel PL, Ziccheddu B, et al. Genomics define malignant transformation in myeloma precursor conditions. J Clin Oncol. 2026;44(3):188-199. doi:10.1200/JCO-25-01733

4. Cowan A, Ferrari F, Freeman SS, et al. Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study. Lancet Haematol. 2023;10(3):e203-e212. doi:10.1016/S2352-3026(22)00386-6