Regional differences in access to hematopoietic stem cell transplantation among pediatric patients with acute myeloid leukemia
Bibliographic record
Abstract
INTRODUCTION: Indications for hematopoietic stem cell transplantation (HSCT) in pediatric acute myeloid leukemia (AML) are primarily dependent on risk stratification at diagnosis and relapse status. We sought to determine whether access to HSCT is influenced by regional and socioeconomic factors. METHODS: Children with newly diagnosed AML aged < 15 years between 2001 and 2015 were identified using the Cancer in Young People in Canada national population-based registry. Factors potentially associated with the receipt of HSCT were studied using univariate and multivariable logistic regression models. RESULTS: Overall, 568 children with newly diagnosed AML were included and 262 (46%) received HSCT. A greater proportion of patients, 103/157 (65.6%), underwent HSCT after first or subsequent relapse compared to 159/411 (38.7%) patients who underwent transplant before relapse. Among patients for whom HSCT would be considered before relapse, factors associated with higher odds of HSCT in a multivariable analysis were: poor versus good-risk cytogenetics (Odds ratio [OR]: 30.0, 95% confidence interval [CI]: 7.7-117.0), diagnosis during 2012-2015 versus 2001-2006 (OR: 3.2, 95% CI: 1.6-6.3), diagnosis in eastern Canada versus central Canada (OR: 3.7, 95% CI: 1.9-7.3), and age 10-14 years versus age < 1 year (OR: 5.4, 95% CI: 2.3-12.8). Among patients for whom HSCT would be considered after first relapse, higher odds of HSCT was associated with diagnosis at a HSCT center (OR: 2.1, 95% CI: 1.1-4.1). CONCLUSION: Patients diagnosed at a HSCT performing center and patients from eastern Canada had higher odds of receiving HSCT. This may suggest preferential access to HSCT for certain patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".