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ASH 2025 | The CRS-RS.5p predictive model of CRS after glofitamab treatment in patients with R/R DLBCL
Haifaa Abdulhaq, MD, University of California, San Francisco, CA, discusses the CRS-RS.5p predictive model to inform risk stratification and cytokine release syndrome (CRS) management following glofitamab treatment in patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL). This interview took place at the 67th ASH Annual Meeting and Exposition, held in Orlando, FL.
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Transcript
This is a paper that looked at a predictive model for cytokine release syndrome in patients who were treated with glofitamab GemOx on the STARGLO study. This model includes five points only or five factors. So it’s a more simplified model compared with the older model that was studied in this patient group. It looks mainly at the age, the LDH, the white count, as well as the stage of the lymphoma, stage three or four, and also the sum of the diameter of the lymph nodes...
This is a paper that looked at a predictive model for cytokine release syndrome in patients who were treated with glofitamab GemOx on the STARGLO study. This model includes five points only or five factors. So it’s a more simplified model compared with the older model that was studied in this patient group. It looks mainly at the age, the LDH, the white count, as well as the stage of the lymphoma, stage three or four, and also the sum of the diameter of the lymph nodes. And each one of these factors has a certain number of points. Then patients were classified as either low risk or high risk based on this predictive model. Patients who had a score of less than four, those are the patients who had low risk. And what we found in this study, that it was quite predictive of the risk of grade two or higher CRS. Patients on this trial had a CRS in 33% of the patients of grade two or higher. And what we found is it predicted, having high risk of CRS-RS.5p predicted having grade two or higher CRS with a positive predictive value of about 67%. In patients who were on third line or later, the positive predictive value was even better, and it was about 83%. What was most impressive to me, though, is the negative predictive value of this model was actually quite high, and it was more than 90%. So what I would conclude from that, this is actually a useful tool that can further guide the management of patients who are treated with glofit GemOx. And to me, it’s quite reassuring when a patient has low risk of this, that this is likely a patient who will not have grade 2 or higher CRS.
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