Adolescents and young adult acute myeloid leukemia outcomes at pediatric versus adult centers: A population‐based study
Bibliographic record
Abstract
Abstract Background Adolescents and young adult (AYA) acute myeloid leukemia (AML) outcomes remain poor. The impact of locus of care (LOC; adult vs pediatric) in this population is unknown. Procedure The IMPACT cohort comprises detailed data for all Ontario, Canada, AYA aged 15‐21 years diagnosed with AML between 1992 and 2012, linked to population‐based health administrative data. We determined the impact of LOC on event‐free survival (EFS) and overall survival (OS), treatment‐related mortality (TRM), and relapse/progression. Results Among 140 AYA, 51 (36.4%) received therapy at pediatric centers. The five‐year EFS and OS for the whole cohort were 35.0% ± 4.0% and 53.6% ± 4.2%. Cumulative doses of anthracycline were higher among pediatric center AYA [median 355 mg/m 2 , interquartile range (IQR) 135‐492 vs 202 mg/m 2 , IQR 140‐364; P = 0.003]. In multivariable analyses, LOC was not predictive of either EFS [adult vs pediatric center hazard ratio (HR) 1.3, 95% confidence interval (CI) 0.8‐2.2, P = 0.27] or OS (HR 1.0, CI 0.6‐1.6, P = 0.97). However, patterns of treatment failure varied; higher two‐year incidence of TRM in pediatric centers (23.5% ± 6.0% vs.10.1% ± 3.2%; P = 0.046) was balanced by lower five‐year incidence of relapse/progression (33.3% ± 6.7% vs 56.2% ± 5.3%; P = 0.002). Conclusions AYA AML survival outcomes did not vary between pediatric and adult settings. Causes of treatment failure were different, with higher intensity pediatric protocols associated with higher TRM but lower relapse/progression. Careful risk stratification and enhanced supportive care may be of substantial benefit to AYA with AML by allocating maximal treatment intensity to patients who most benefit while minimizing the risk of TRM.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".