CRS or ICANS Are Rare Beyond 2 Weeks After Lisocabtagene Maraleucel Infusion: Data From Clinical Trials and the Real-World Setting
Bibliographic record
Abstract
Improved understanding of the timing of cytokine release syndrome (CRS) and immune effector cell-mediated neurotoxicity syndrome (ICANS)/neurological events (NE) after chimeric antigen receptor (CAR) T-cell therapy infusion can inform patient safety monitoring. To report CRS and ICANS/NE outcomes, including incidence, onset, and resolution, in patients treated with lisocabtagene maraleucel (liso-cel) in clinical trials and the real-world setting. This analysis included patients treated with liso-cel in 5 clinical trials across different B-cell non-Hodgkin lymphoma indications (n = 702) and in the real-world setting for large B-cell lymphoma, as captured in the Center for International Blood and Marrow Transplant Research (CIBMTR) Registry (n = 877). All outcomes are reported descriptively. Among 702 patients in clinical trials, 54% had any-grade CRS (grade ≥3 at onset, 1%), with 98% of events occurring ≤day 15 after infusion; median time to resolution was 5 days. Any-grade NEs occurred in 31% of patients (grade ≥3 at onset, 5%), with 88% of events occurring ≤day 15 after infusion; median time to resolution was 7 days. Among 877 patients in the real-world setting, 49% had any-grade CRS (maximum grade ≥3, 3%), with 97% of events occurring ≤day 15 after infusion; median time to resolution was 4 days. Any-grade ICANS occurred in 27% of patients (maximum grade ≥3, 10%). Of 150 patients with reported onset date, 95% had onset ≤day 15 after infusion; median time to resolution was 5.5 days. The vast majority of CRS or ICANS/NEs occurred ≤day 15 after liso-cel infusion. These results support the recently updated United States Food and Drug Administration monitoring requirements aimed to improve treatment access while maintaining patient safety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".