Incidence and Treatment of Potentially Lethal Diseases in Transient Leukemia of Down Syndrome: Pediatric Oncology Group Study
Bibliographic record
Abstract
Transient leukemia (TL or transient myeloproliferative disorder) occurs in approximately 10% of newborn infants with Down syndrome. The disorder is characterized by the presence of megakaryoblasts in the peripheral blood; most cases resolve spontaneously within the first 3 months of life, and the child is well thereafter. However, there are cases in which a severe, potentially lethal form of disease develops, manifesting as hepatic fibrosis or cardiopulmonary failure. Hitherto, the incidence of these severe forms of the disease has not been reported. A prospective study of TL was conducted by the Pediatric Oncology Group (POG Study 9481) in which 48 children with TL were identified. Life-threatening disease occurred in nine patients (19%); seven had hepatic fibrosis and two had cardiopulmonary failure. Five children died of the disease within the first 3 months of life, none of whom received antileukemic therapy. One patient died on day 31 after receiving minimal therapy within 1 day of death. Three children received low-dose cytosine arabinoside (Ara-C) (0.4-1.5 mg/kg every 12 hours for 5 or 7 days). In all these patients, the disease resolved. It is concluded that potentially lethal disease is relatively common in TL, and the available evidence suggests that these diseases are responsive to low-dose Ara-C therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".