Central nervous system disease in pediatric acute myeloid leukemia: A report from the Children's Oncology Group
Bibliographic record
Abstract
BACKGROUND: The prognostic impact of central nervous system (CNS) involvement in children with acute myeloid leukemia (AML) has varied in past trials, and controversy exists over the degree of involvement requiring intensified CNS therapy. Two recent Children's Oncology Group protocols, AAML03P1 and AAML0531, directed additional intrathecal (IT) therapy to patients with CNS2 (≤5 white blood cell [WBC] with blasts) or CNS3 (>5 WBC with blasts or CNS symptoms) disease at diagnosis. METHODS: We examined disease characteristics and outcomes of the 1,344 patients on these protocols, 949 with CNS1 (no blasts), 217 with CNS2, and 178 with CNS3, with the latter two receiving additional IT therapy. RESULTS: Young age (P = 0.003), hyperleukocytosis (P < 0.001), and the presence of inversion 16 (P < 0.001) were the only factors more prevalent in patients with CNS2 or CNS3 disease. Complete remission at the end of induction (EOI) 2 was achieved less often in patients with CNS involvement (P < 0.001). From diagnosis, event-free survival (EFS) for patients with CNS involvement was significantly worse (P < 0.001), whereas overall survival (OS) was not (P = 0.16). From the EOI1, there was a higher relapse rate (RR) and worse disease-free survival (DFS), but less impact on OS (CNS1:DFS 58.9%, RR 34.1%, OS 69.3%; CNS2:DFS 53.2%, RR 40.9%, OS 74.7%; CNS3:DFS 45.2%, RR 48.8%, OS 60.8%; P = 0.006, P < 0.001, P = 0.045, respectively). Multivariable analysis showed that independently CNS2 and CNS3 status adversely affected RR and DFS. Traumatic diagnostic lumbar puncture was not associated with worse outcome. CONCLUSIONS: CNS leukemia confers greater relapse risk despite more aggressive locally directed therapy. Novel approaches need to be investigated in this group of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".