Cytokine Release Syndrome and Neurotoxicity Following CD19 CAR-T in B-Cell Lymphoma
Bibliographic record
Abstract
Chimeric antigen receptor T cell (CAR-T) therapy is an effective treatment for relapsed-refractory large B-cell lymphoma (LBCL). However, toxicities, particularly cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), remain significant concerns. Analyze temporal trends, risk factors, and associations between these toxicities and their severity. In this registry study by the Center for International Blood and Marrow Transplant Research, we studied CRS and ICANS in 1916 LBCL patients treated with commercial CAR-T therapies (axicabtagene ciloleucel 74.9%, tisagenlecleucel 25.1%) between 2018 and 2020. Outcomes include development of CRS/ICANS, timing and severity according to ASTC grading, overall survival (OS). Risk factors were assessed using Cox proportional hazards model. Among patients developing CRS (75.2%), 11.3% had grade ≥3 CRS. Among patients developing ICANS (43.5%), 47.7% had grade ≥3 ICANS. Among patients developing CRS, severe CRS rates decreased from 14.0% in 2018 to 9.2% in 2020 (P< .01). However, the proportion of severe ICANS in patients who developed ICANS remained statistically unchanged (41.5% in 2018 to 53.7% in 2020, P= .10). CRS and ICANS were correlated: 57.1% of patients with CRS also experienced ICANS, and CRS was reported in 97.5% of ICANS cases, suggesting a potential continuum between toxicities. Axicabtagene ciloleucel was associated with higher risk of any grade CRS (OR, 4.6; 95% CI, 3.65 to 5.81) and ICANS (OR, 5.85; 95% CI, 4.48 to 7.64) as well as early and severe forms of both complications. Older age, lower performance status, and elevated lactate dehydrogenase levels prior to infusion also variably predicted these toxicities. In a landmark analysis starting 30 days postinfusion, patients with severe CRS or severe ICANS had shorter OS compared to those without these toxicities. High grades of CRS improved over time likely related to earlier intervention, development of ICANS is intrinsically related with CRS. These findings underscore the need for effective strategies to mitigate these toxicities and improve CAR-T 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".