ASH 2025 | Predictive relapse indicators for myeloma T-cell engagers (PRIME) model

When I was back at Mount Sinai during my fellowship, I was interested in actually trying to predict what is the outcome of patients who are on bispecific antibodies, and I focused on the two major targets, BCMA and GPRC5D. So bispecifics for these targets are becoming more and more readily available for patients, and we have a lot of patients now utilizing these therapies that are very effective. However, while there are a lot of studies that have already started establishing some predictors of response, we don’t still really understand fully the picture or really knowing all the markers or factors that are contributing to response. So what I tried to do is I tried to gather all the patient data from our institution, a single center institution back then, and created a calculator, basically, which we called PRIME, predictors of relapse indicators for myeloma T-cell engagers. And with that calculator, we looked at all clinical variables for over 320 patients at Mount Sinai who received a bispecific antibody. And it was different bispecifics, either targeting BCMA or GPRC5D. And we followed them through across their treatment duration, and we found that out of all the clinical variables we studied, which were almost 25, actually, clinical variables, five of them stood out, and we were able to use those five to create this calculator. So those five factors were having an absolute lymphocyte count that’s either below or above 0.9. That made a difference. Having ferritin elevated versus low ferritin, having high versus low LDH, which is lactate dehydrogenase, or having extramedullary disease, or having high-risk cytogenetics. So those five factors actually when put into this model can give you a prediction of progression-free survival at six months, 12 months, two years, three years, and four years. And of course we found that having a higher absolute lymphocyte count, having lower ferritin, lower LDH, and no extramedullary disease, as well as no high-risk cytogenetics, predicted a very, very long progression-free survival for patients, while having all of those put you at the other end of the spectrum. But then there’s always the patients who are in between, who have different levels or variables out of these five characteristics, which would give you a different prediction. So this calculator right now, we’re actually validating it on an external cohort. So now that I’m at Dana-Farber, actually, we’re collaborating with my previous institution to add a cohort of patients who receive bispecifics and both for BCMA and GPRC5D. And we’re currently validating the calculator. And once that phase is done, we’re going to actually make it accessible online so that both clinicians and patients would be able to access it and they can enter their own information and see where their PFS prediction lies.

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