Clinical Outcome after Cellular Therapies in Children with Acute Leukemia
Bibliographic record
Abstract
Immunotherapy has significantly improved overall survival of pediatric patients with acute leukemia. Nevertheless, procedure-related life-threatening complications, together with relapsed disease, hamper the life-saving effect of immunotherapy and highlight the need for improvement. The goal of this thesis was to investigate potential enhancements for two currently applied immunotherapies in clinical care, thereby aiming to improve clinical outcome in pediatric patients with acute leukemia. These two therapies include allogeneic hematopoietic cell transplantation and chimeric antigen receptor T cell therapy. This thesis shows that immunosuppressive therapies influence the recovery of the immune system and that individualized dosing strategies can be crucial for improving clinical outcome. Furthermore, the identification of risk factors for therapy failure or for the onset of life-threatening complications are essential for the development and implementation of preventative measures and adjusted or alternative treatment options. The data presented in this thesis thereby contribute to further optimization of cellular therapies to eventually improve clinical outcome of pediatric patients with acute leukemia.
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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 | 0.000 | 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".