Gemtuzumab Ozogamicin in Children and Adolescents With De Novo Acute Myeloid Leukemia Improves Event-Free Survival by Reducing Relapse Risk: Results From the Randomized Phase III Children's Oncology Group Trial AAML0531
Bibliographic record
Abstract
PURPOSE: To improve survival rates in children with acute myeloid leukemia (AML), we evaluated gemtuzumab-ozogamicin (GO), a humanized immunoconjugate targeted against CD33, as an alternative to further chemotherapy dose escalation. Our primary objective was to determine whether adding GO to standard chemotherapy improved event-free survival (EFS) and overall survival (OS) in children with newly diagnosed AML. Our secondary objectives examined outcomes by risk group and method of intensification. PATIENTS AND METHODS: Children, adolescents, and young adults ages 0 to 29 years with newly diagnosed AML were enrolled onto Children’s Oncology Group trial AAML0531 and then were randomly assigned to either standard five-course chemotherapy alone or to the same chemotherapy with two doses of GO (3 mg/m2/dose) administered once in induction course 1 and once in intensification course 2 (two of three). RESULTS: There were 1,022 evaluable patients enrolled. GO significantly improved EFS (3 years: 53.1% v. 46.9%; hazard ratio [HzR], 0.83; 95% CI, 0.70 to 0.99; P.04) but not OS (3 years: 69.4% v. 65.4%; HzR, 0.91; 95% CI, 0.74 to 1.13; P = .39). Although remission was not improved (88% v. 85%; P = .15), posthoc analyses found relapse risk (RR) was significantly reduced among GO recipients overall (3 years: 32.8% v. 41.3%; HzR, 0.73; 95% CI, 0.58 to 0.91; P = .006). Despite an increased postremission toxic mortality (3 years: 6.6% v. 4.1%; HzR, 1.69; 95% CI, 0.93 to 3.08; P = .09), disease-free survival was better among GO recipients (3 years: 60.6% v. 54.7%; HzR, 0.82; 95% CI, 0.67 to 1.02; P = .07). CONCLUSION: GO added to chemotherapy improved EFS through a reduction in RR for children and adolescents with AML.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".