A comprehensive analysis of the fatal toxic effects associated with CD19 CAR-T cell therapy
Bibliographic record
Abstract
To determine the incidence, spectrum, timing, and clinical features of CD19 Chimeric antigen receptor (CAR-T) cell therapy-associated fatal toxic effects. We initiated a comprehensive analysis. First, we retrospectively queried the real-world data from a World Health Organization (WHO) pharmacovigilance database (Vigilyze). Furthermore, we performed a meta-analysis of published trials of CD19 CAR-T cell therapy. From screening the WHO database, we identified 1200 patients: 499 received Kymriah therapy, and 701 received Yescarta therapy. We compared the adverse reactions of the two drugs. We evaluated all published clinical trials, comprising 19 trials and 890 patients. Our meta-analysis showed that the incidence of fatal toxic effects associated with death was 5.4%. Infections and infestations appeared to present the highest risk of death. The toxic effect specific median time to death was 30, 30, and 68 days for total, cytokine release syndrome (CRS), and nervous system disorders (NSD), respectively. We observed a high mortality rate for some toxic effects and an early onset of death with varied causes, indicating the need for clinicians to pay more attention to the monitoring and treatment of these fatal toxic effects when using CD19 CAR-T cell therapy, especially for infections and infestations.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.017 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".