Risks of late mortality and morbidity among survivors of childhood acute leukemia with Down syndrome: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: Children with leukemia and Down syndrome (DS) are at higher risk of acute treatment toxicities than those without DS. Whether late toxicity risks are also elevated is unknown. METHODS: The authors identified all patients diagnosed with leukemia before the age of 18 years in Ontario, Canada between 1987 and 2013 and who survived greater than 5 years since their last pediatric cancer event. Survivors were divided into those with and without DS, matched by birth year, sex, leukemia type, and receipt of radiation. DS survivors were matched to individuals with DS without childhood cancer (DS controls) in a 1:10 ratio. Outcomes were identified through linkage to population-based health services databases. RESULTS: DS survivors (n = 79) experienced inferior overall survival compared to non-DS survivors (n = 231) (20-year overall survival, 81.7% ± 6.8% vs 98.3% ± 1.2%; hazard ratio [HR], 12.8; P < .0001) and to DS controls (n = 790; 96.3% ± 1.2%; HR, 5.4 P < .0001). Pulmonary and infectious deaths were noted among DS survivors. There was no difference in the incidence of congestive heart failure between DS survivors and either control cohort, nor of hearing loss or dementia between DS survivors and DS controls. CONCLUSIONS: DS survivors were at substantially higher risk of late mortality than non-DS survivors or DS controls. This excess risk was not attributable to cardiac- or subsequent malignant neoplasm-related late effects, historically main causes of premature death among non-DS survivors. Chronic morbidities associated with DS were not increased compared to DS controls. DS-specific surveillance guidelines may be warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".