Gemtuzumab ozogamicin: first clinical experiences in children with relapsed/refractory acute myeloid leukemia treated on compassionate-use basis
Bibliographic record
Abstract
Gemtuzumab ozogamicin (GO; Mylotarg) was developed to treat CD33(+) acute myeloid leukemia (AML). To date, only studies in adults and preliminary data from a phase 1 study in children have been reported. We report data on 15 children with relapsed/refractory CD33(+) AML who were treated with GO monotherapy on compassionate use basis (4-9 mg/m(2) up to 3 courses). Eight children showed a reduction in bone marrow blasts to 5% or less, including 5 in complete remission without full platelet recovery (CRp). Three of the 5 children with CRp received transplants almost directly following the last GO course, without awaiting further platelet regeneration. Hence in these children no clear discrimination between complete remission (CR) and CRp could be made. In 6 of 8 responding patients further treatment was given consisting of stem cell transplantation (SCT). Two patients are still alive, currently 6 and 9 months after SCT. Hematologic toxicity was difficult to assess due to subsequent SCT or leukemia. Side effects, in one patient each included veno-occlusive disease, transient grade 3 hyperbilirubinemia, transient grade 3 transaminase elevation, and grade 3 hypotension during GO administration. No infections or mucositis occurred. This report demonstrates clinical efficacy of GO in a subset of relapsed/refractory pediatric CD33(+) AML patients and suggests that intensive postremission therapy after remission induction by GO may result in durable responses in some patients, although follow-up is still short. Further studies are needed to determine the efficacy and safety of GO in children 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".