Philadelphia chromosome-positive acute lymphoblastic leukemia in children: new and emerging treatment options
Bibliographic record
Abstract
Philadelphia chromosome-positive (Ph(+)) acute lymphoblastic leukemia (ALL) in children and adolescents has, until recently, been considered one of the poorest-risk subgroups of ALL. With chemotherapy alone, only 20-30% of children with Ph(+) ALL are cured. Allogeneic hematopoietic cell transplantation in first complete remission cures 60% of patients with a closely matched donor. Although targeted tyrosine kinase inhibitors (TKIs) have limited activity against Ph(+) ALL as a single agent, they have been evaluated in combination with chemotherapy with promising results. The early results of Children's Oncology Group trial AALL0031 have shown 88% 3-year event-free survival for Ph(+) patients treated with intensive chemotherapy plus continuous-dosing imatinib. This suggests that chemotherapy plus TKIs may be the initial treatment of choice for Ph(+) ALL in children. However, the numbers are small in this trial and confirmatory results are not yet available from the European Intergroup Study on Post Induction Treatment of Philadelphia Positive Acute Lymphoblastic Leukaemia with Imatinib trial. Additional issues include determining the most effective TKI (imatinib, dasatinib or nilotinib) and the most effective, least toxic chemotherapy backbone. The experience of adding a targeted agent such as a TKI to the standard chemotherapy regimen suggests that this strategy might be applied to other ALL subtypes to achieve both increased efficacy and decreased toxicity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".