Outcomes of children with chronic myeloid leukemia: A population‐based cohort study
Bibliographic record
Abstract
OBJECTIVE: Chronic myeloid leukemia (CML) is a rare disease in childhood. While hematopoietic stem cell transplant (HSCT) was the treatment of choice for CML prior to 2000, the introduction of tyrosine kinase inhibitors (TKIs) changed the management of this disease. This population-based analysis was conducted in the province of Ontario, Canada to gather information on treatment choices and outcomes of childhood CML. METHOD: Using a provincial childhood cancer registry and retrospective review of patient medical records for patients < 18 years diagnosed with CML between 1985 and 2018, data on presenting features, treatment, and outcomes were collected from 52 patients. RESULTS: Patients treated before the introduction of TKIs (before 2002) mainly received HSCT and had an overall survival (OS) of 64% at a median follow up of 6 years. The OS of all patients treated in the TKI era (2002 and after) was 90% at a median follow up of 3 years. All three deaths in the TKI era were related to HSCT complications. Survival of patients who remained on a TKI was significantly improved compared to those who underwent HSCT post-TKI therapy (100% vs 66%, P = .008). TKIs were well tolerated. CONCLUSION: Given the increased mortality associated with HSCT in our cohort, further advances in HSCT may be required to outweigh the benefits of a TKI monotherapy approach in the majority of childhood CML patients. We believe HSCT should be considered in only a limited subset of pediatric patients with CML.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".