Patterns of care and outcomes in adolescent and young adult acute lymphoblastic leukemia: a population-based study
Bibliographic record
Abstract
Adolescents and young adults (AYAs, 15-39 years) with acute lymphoblastic leukemia (ALL) represent a heterogeneous population who receive care in pediatric or adult cancer settings. Using the California Cancer Registry, we describe AYA ALL patterns of care and outcomes over the past decade. Sociodemographics, treatment location, and front-line therapies administered to AYAs diagnosed with ALL between 2004 and 2014 were obtained. Cox regression models evaluated associations between ALL setting and regimen and overall survival (OS) and leukemia-specific survival (LSS) for the entire cohort, younger AYA (<25 years), and AYAs treated in the adult cancer setting only. Of 1473 cases, 67.7% were treated in an adult setting; of these, 24.8% received a pediatric ALL regimen and 40.7% were treated at a National Cancer Institute (NCI)-designated center. In multivariable analyses, front-line treatment in a pediatric (vs adult) setting (OS HR = 0.53, 95% confidence interval [CI], 0.37-0.76; LSS HR = 0.51, 95% CI, 0.35-0.74) and at an NCI/Children's Oncology Group (COG) center (OS HR = 0.80, 95% CI, 0.66-0.96; LSS HR = 0.80, 95% CI, 0.65-0.97) were associated with significantly superior survival. Results were similar when analyses were limited to younger AYAs. Outcomes for AYAs treated in an adult setting did not differ following front-line pediatric or adult ALL regimens. Our population-level findings demonstrate that two-thirds of AYAs with newly diagnosed ALL are treated in an adult cancer setting, with the majority receiving care in community settings. Given the potential survival benefits, front-line treatment of AYA ALL at pediatric and/or NCI/COG-designated cancer centers should be considered.
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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 | 0.000 | 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".