Complexity of baseline cognitive and psychological status in haematology patients planned for chimeric antigen receptor T-cell therapy
Bibliographic record
Abstract
Abstract Background Immune effector cell-associated neurotoxicity syndrome (ICANS) is a relatively common consequence of chimeric antigen receptor T-cell (CAR-T) therapy, with a wide range of possible cognitive presentations. The aim of this study was to characterise a real-word cognitive and psychological status of patients with advanced haematologic and solid organ malignancies planned for CAR-T. We also aimed to examine utility of two cognitive screening approaches. Methods Patients underwent specialist cognitive assessment, including a self-report questionnaire of psychopathology and subjective cognitive function. A subset of individuals also completed the Montreal Cognitive Assessment (MoCA). Results Of 60 patients included, 15-16 (25%-27%) presented with evidence of cognitive impairment, with six unique patterns of dysfunction. Impaired patients were more likely to have B-cell acute lymphoblastic leukaemia ( BF 10 =9.30), be younger ( BF 10 =7.76), have bone marrow involvement ( BF 10 =5.18), report history of anxiety ( BF 10 =4.85), or have evidence of psychopathology ( BF 10 =31.30). Analyses did not support the utility of cognitive screening. Of those patients who completed a self-report measure of psychopathology, nine (15.8%) were elevated on at least one symptom domain. Conclusions The findings demonstrate a broad spectrum of dysfunction and psychopathology in this cohort, emphasising the importance of baseline evaluation for detecting cognitive neurotoxicity symptoms that might arise after CAR-T infusion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".