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IMS 2025 | The SCOPE-MM score: a prediction model for risk groups of patients with RRMM treated with CAR-T

David Cordas dos Santos, MD, Dana-Farber Cancer Institute, Boston, MA, comments on the development and validation of the SCOPE-MM score, a novel prediction model that identifies risk groups for patients with relapsed/relapsed multiple myeloma (RRMM) treated with CAR T-cells. This score, developed from a large international cohort of over 1,200 patients, predicts toxicities and treatment outcomes at an early time point, allowing for pre-emptive mitigation strategies to be implemented. This interview took place at the 22nd International Myeloma Society (IMS) Annual Meeting in Toronto, Canada.

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Transcript

This study is really like an interesting study that we did together with Kai Rejeski, Doris Hansen and Yi Lin. In this study we wanted to know when we look at how can we predict toxicities or survival outcomes for patients with relapsed myeloma who get treated with CAR T-cells. There are prediction models at the moment which is like the CAR-Hematotox score or the MyCare model...

This study is really like an interesting study that we did together with Kai Rejeski, Doris Hansen and Yi Lin. In this study we wanted to know when we look at how can we predict toxicities or survival outcomes for patients with relapsed myeloma who get treated with CAR T-cells. There are prediction models at the moment which is like the CAR-Hematotox score or the MyCare model. But these scores, they are applied at a time point of CAR-T infusion or lymphodepletion. And this is like a very late time point. So at this time point, we already have the CAR T-cells. They were manufactured. There’s money that went into this and also maybe psychological consequences for the patients. So when we look back at the time when actually the decision is made to confer the CAR T-cells, so the indication, that’s two to three months before the time point that we give the CAR T-cells. So we were wondering if we can find predictors or variables with which we can predict treatment outcomes and toxicities already at this very first time point. Because obviously then we have like a huge time to maybe modify treatment or to select patients which are at high risk or low risk for treatment response and toxicities. That was kind of the idea for this entire project and we combined data from over 1,200 CAR-T patients, a very large cohort of data set, from nine US myeloma centers but also German centers, so it was international collaboration, and we actually found a couple of variables at this very early time point that predicted toxicities and outcomes and we developed the score in a way that is prognostic. So we can use it for cilta-cel or ide-cel and we called it SCOPE-MM so it stands for Stratification of Outcome at a Pre-apheresis Time point and it’s interesting for us to see that we can find these risk groups we distinguish three different risk groups, low, intermediate and high risk group that have like different outcomes in terms of PFS and OS but also for toxicity. And this kind of has a lot of clinical implications. So if we do this very early time point, obviously we can maybe intensify bridging therapy or we can for patients at high risk for bad outcomes or for patients at high risk for toxicities, we are then able to already do pre-emptive mitigation strategies for the patients so that they do not develop these toxicities.

 

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