Novel therapy for childhood acute lymphoblastic leukemia
Bibliographic record
Abstract
Introduction: During recent decades, the prognosis of childhood acute lymphoblastic leukemia (ALL) has improved dramatically, nowadays, reaching a cure rate of almost 90%. These results are due to a better management and combination of old therapies, refined risk-group stratification and emergence of minimal residual disease (MRD) combined with treatment’s intensification for high-risk subgroups. However, the subgroup of patients with refractory/relapsed ALL still presents a dismal prognosis indicating necessity for innovative therapeutic approaches.Areas covered: We performed an exhaustive review of current first-line therapies for childhood ALL in the worldwide main consortia, summarized the major advances for front-line and relapse treatment and highlighted recent and promising innovative therapies with an overview of the most promising ongoing clinical trials.Expert opinion: Two major avenues marked the beginning of 21st century. First, is the introduction of tyrosine-kinase inhibitor coupled to chemotherapy for treatment of Philadelphia positive ALL opening new treatment possibilities for the recently identified subgroup of Ph-like ALL. Second, is the breakthrough of immunotherapy, notably CAR T-cell and specific antibody-based therapy, with remarkable success observed in initial studies.This review gives an insight on current knowledge in these innovative therapeutic directions, summarizes currently ongoing clinical trials and addresses challenges these approaches are faced with.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".