Improved Early Event-Free Survival With Imatinib in Philadelphia Chromosome–Positive Acute Lymphoblastic Leukemia: A Children's Oncology Group Study
Bibliographic record
Abstract
PURPOSE: Imatinib mesylate is a targeted agent that may be used against Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukemia (ALL), one of the highest risk pediatric ALL groups. PATIENTS AND METHODS: We evaluated whether imatinib (340 mg/m(2)/d) with an intensive chemotherapy regimen improved outcome in children ages 1 to 21 years with Ph+ ALL (N = 92) and compared toxicities to Ph- ALL patients (N = 65) given the same chemotherapy without imatinib. Exposure to imatinib was increased progressively in five patient cohorts that received imatinib from 42 (cohort 1; n = 7) to 280 continuous days (cohort 5; n = 50) before maintenance therapy. Patients with human leukocyte antigen (HLA) -identical sibling donors underwent blood and marrow transplantation (BMT) with imatinib given for 6 months following BMT. RESULTS: Continuous imatinib exposure improved outcome in cohort 5 patients with a 3-year event-free survival (EFS) of 80% +/- 11% (95% CI, 64% to 90%), more than twice historical controls (35% +/- 4%; P < .0001). Three-year EFS was similar for patients in cohort 5 treated with chemotherapy plus imatinib (88% +/- 11%; 95% CI, 66% to 96%) or sibling donor BMT (57% +/- 22%; 95% CI, 30.4% to 76.1%). There were no significant toxicities associated with adding imatinib to intensive chemotherapy. The higher imatinib dosing in cohort 5 appears to improve survival by having an impact on the outcome of children with a higher burden of minimal residual disease after induction. CONCLUSION: Imatinib plus intensive chemotherapy improved 3-year EFS in children and adolescents with Ph+ ALL, with no appreciable increase in toxicity. BMT plus imatinib offered no advantage over BMT alone. Additional follow-up is required to determine the impact of this treatment on long-term EFS and determine whether chemotherapy plus imatinib can replace BMT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".