Neurological management and work-up of neurotoxicity associated with CAR T cell therapy
Bibliographic record
Abstract
INTRODUCTION: Treatment with CD19 chimeric antigen receptor (CAR) T cells is an innovative therapeutic approach for patients with relapsed/refractory diffuse large B cell lymphoma (r/rDLBCL) and B-lineage acute lymphoblastic leukemia (r/rALL). However, convincing therapeutic response rates can be accompanied by cytokine release syndrome (CRS) and severe neurotoxicity termed immune effector cell-associated neurotoxicity syndrome (ICANS). METHODS: Single center, prospective observational study of fifteen consecutive r/r DLBCL patients treated with Tisagenlecleucel within 1 year at Hannover Medical School. Extensive neurological work-up prior to CAR T cell infusion included clinical examination, cognitive testing (Montreal-Cognitive-Assessment), brain MRI, electroencephalogram, electroneurography, and analysis of cerebrospinal fluid. After CAR T cell infusion, patients were neurologically examined for 10 consecutive days. Afterwards, all patients were assessed at least once a week. RESULTS: ICANS occurred in 4/15 patients (27%) within 6 days (4-6 days) after CAR T cell infusion. Patients with ICANS grade 2 (n = 3) exhibited similar neurological symptoms including apraxia, expressive aphasia, disorientation, and hallucinations, while brain MRI was inconspicuous in either case. Treatment with dexamethasone rapidly resolved the clinical symptoms in all three patients. Regarding baseline parameters prior to CAR T cell treatment, patients with and without ICANS did not differ. CONCLUSIONS: In our cohort, ICANS occurred in only every fourth patient and rather low grade neurotoxicity was found during daily examination. Our results demonstrate that a structured neurological baseline examination and close monitoring are helpful to detect CAR T cell related neurotoxicity already at an early stage and to potentially prevent higher grade neurotoxicity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".