The Chronic Lymphocytic Leukemia Channel on VJHemOnc is an independent medical education platform, supported with funding from AstraZeneca (Diamond), AbbVie (Platinum), BeOne Medicines (Silver) and Lilly (Silver). Supporters have no influence on the production of content. The levels of sponsorship listed are reflective of the amount of funding given.
The Lymphoma Channel on VJHemOnc is an independent medical education platform, supported with funding from AstraZeneca (Diamond), BMS (Gold), Johnson & Johnson (Gold), Takeda (Silver) and Galapagos (Bronze). Supporters have no influence on the production of content. The levels of sponsorship listed are reflective of the amount of funding given.
CAR-T Meeting 2025 | Patient-reported side-effects for CAR-T vs other therapies in patients with relapsed lymphomas & CLL
Natacha Bolaños, Lymphoma Coalition Europe, Madrid, Spain, comments on an analysis of data from the Lymphoma Coalition’s Global Patient Survey investigating patient-reported side effects for CAR T-cell therapy versus other therapies in patients with relapsed lymphomas and chronic lymphocytic leukemia (CLL). Ms Bolaños highlights a 65% increased likelihood of experiencing side effects for those receiving CAR-T, noting that the data validates previous findings and may guide clinicians in monitoring and managing these patients. This interview took place at the EHA-EBMT 7th European CAR T-cell Meeting, held in Strasbourg, France.
These works are owned by Magdalen Medical Publishing (MMP) and are protected by copyright laws and treaties around the world. All rights are reserved.
Transcript (AI-generated)
The data we will be presenting in this meeting builds upon data from the Global Patient Survey 2022 that we presented at ASH in 2022 and we presented last year at the CAR T-cell meeting in 2023. By that time, we presented aggregated side effects, comparing the odds of experiencing side effects in patients receiving CAR-T versus patients receiving other therapies. We collected new data through the Global Patient Survey in 2024 with over 11,000 respondents in general and we selected a dataset of relapsed cases, patients experiencing relapse lymphomas, to check on those receiving CAR-T...
The data we will be presenting in this meeting builds upon data from the Global Patient Survey 2022 that we presented at ASH in 2022 and we presented last year at the CAR T-cell meeting in 2023. By that time, we presented aggregated side effects, comparing the odds of experiencing side effects in patients receiving CAR-T versus patients receiving other therapies. We collected new data through the Global Patient Survey in 2024 with over 11,000 respondents in general and we selected a dataset of relapsed cases, patients experiencing relapse lymphomas, to check on those receiving CAR-T.
For those who met the eligibility criteria we had 169 patients who received CAR T-cell therapy and we established comparisons between those patients receiving CAR-T versus the patients not receiving CAR-T, and the higher odds of having more side effects. The data this year was more robust and we can report that there is 65% more likely to experience side effects for those receiving CAR-T versus those that didn’t receive CAR-T by the…
I didn’t mention before, the median age of the total sample was 65 years, the youngest 18 years old, and the oldest 91 years old. Among the total sample of patients receiving CAR-T, there were different 19 lymphoma subtypes. However, I want to remark that there were five more prevalent among the sample, and these were chronic lymphocytic leukemia, follicular lymphoma, Waldenström macroglobulinemia, large B-cell lymphoma, and follicular lymphoma.
So with this new data, it really confirms, it validates previous findings. Why this data matters? Because it could be guiding clinicians on observing those patients who experience these symptoms and get prepared earlier to provide management strategies. So what we plan to do next is to try to track the likely to have symptoms, determine symptoms together. And that could help us probably to build an algorithm to predict the patients that will be more likely to experience several side effects, symptoms, for clinicians to help them with their management strategies in general practice.
This transcript is AI-generated. While we strive for accuracy, please verify this copy with the video.
Read more...
