Acute lymphoblastic leukemia in children with Down syndrome: a retrospective analysis from the Ponte di Legno study group
Why this work is in the frame
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Bibliographic record
Abstract
Children with Down syndrome (DS) have an increased risk of B-cell precursor (BCP) acute lymphoblastic leukemia (ALL). The prognostic factors and outcome of DS-ALL patients treated in contemporary protocols are uncertain. We studied 653 DS-ALL patients enrolled in 16 international trials from 1995 to 2004. Non-DS BCP-ALL patients from the Dutch Child Oncology Group and Berlin-Frankfurt-Münster were reference cohorts. DS-ALL patients had a higher 8-year cumulative incidence of relapse (26% ± 2% vs 15% ± 1%, P < .001) and 2-year treatment-related mortality (TRM) (7% ± 1% vs 2.0% ± <1%, P < .0001) than non-DS patients, resulting in lower 8-year event-free survival (EFS) (64% ± 2% vs 81% ± 2%, P < .0001) and overall survival (74% ± 2% vs 89% ± 1%, P < .0001). Independent favorable prognostic factors include age <6 years (hazard ratio [HR] = 0.58, P = .002), white blood cell (WBC) count <10 × 10(9)/L (HR = 0.60, P = .005), and ETV6-RUNX1 (HR = 0.14, P = .006) for EFS and age (HR = 0.48, P < .001), ETV6-RUNX1 (HR = 0.1, P = .016) and high hyperdiploidy (HeH) (HR = 0.29, P = .04) for relapse-free survival. TRM was the major cause of death in ETV6-RUNX1 and HeH DS-ALLs. Thus, while relapse is the main contributor to poorer survival in DS-ALL, infection-associated TRM was increased in all protocol elements, unrelated to treatment phase or regimen. Future strategies to improve outcome in DS-ALL should include improved supportive care throughout therapy and reduction of therapy in newly identified good-prognosis subgroups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it