The Outcome of Allogeneic Hematopoietic Cell Transplantation for Children with FMS-Like Tyrosine Kinase 3 Internal Tandem Duplication–Positive Acute Myelogenous Leukemia
Bibliographic record
Abstract
FMS-like tyrosine kinase 3 (FLT3) internal tandem duplication (ITD) is a somatic mutation associated with poor outcome when treated with chemotherapy alone. In children, hematopoietic stem cell transplantation (HSCT) is recommended, but very limited data on outcome are reported. We determined the outcome of 29 children with FLT3/ITD-positive acute myelogenous leukemia (AML) who underwent allogeneic HSCT in 4 pediatric centers. Eleven patients (38%) received matched related donor hematopoietic stem cells and 18 (62%) received alternative donors. Eighteen patients (62%) received total body irradiation (TBI)-based regimens. No patients experienced transplantation-related mortality. Eleven patients (38%) experienced relapsed disease. The cumulative incidence of relapse at 2 years was 34.7% (95% confidence interval [CI], 20.4% to 54.9%). Two-year disease-free survival (DFS) and overall survival (OS) were 65.3% (95% CI, 45.1% to 79.6%) and 82.2% (95% CI, 58.5% to 91.3%), respectively. There was no difference in the DFS of patients who received transplants from related donors versus the DFS of those who received transplants from alternative donors (hazard ratio [HR], 2.64; 95% CI, .79 to 8.76; P = .10), using univariate analysis. Patients with higher FLT3/ITD ratio at diagnosis had significantly worse DFS (HR, 1.42; 95% CI, 1.04 to 1.93; P = .03). The use of TBI in the preparative regimen was associated with superior DFS (HR, .29; 95% CI, .08 to .99; P = .04) and OS (HR, .07; 95% CI, .01 to .62; P = .002). We conclude that allogeneic HSCT improves DFS and OS in children with FLT3/ITD-positive AML compared with what has been reported in those treated with chemotherapy alone.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".