Personalized Prognostic Risk Score for Long-Term Survival for Children with Acute Leukemia after Allogeneic Transplantation
Bibliographic record
Abstract
We studied leukemia-free (LFS) and overall survival (OS) in children with acute myeloid (AML, n = 790) and acute lymphoblastic leukemia (ALL, n = 1096) who underwent transplantation between 2000 and 2010 and who survived for at least 1 year in remission after related or unrelated donor transplantation. Analysis of patient-, disease-, and transplantation characteristics and acute and chronic graft-versus-host disease (GVHD) was performed to identify factors with adverse effects on LFS and OS. These data were used to develop risk scores for survival. We did not identify any prognostic factors beyond 4 years after transplantation for AML and beyond 3 years for ALL. Risk score for survival for AML includes age, disease status at transplantation, cytogenetic risk group, and chronic GVHD. For ALL, the risk score includes age at transplantation and chronic GVHD. The 10-year probabilities of OS for AML with good (score 0, 1, or 2), intermediate (score 3), and poor risk (score 4, 5, 6, or 7) were 94%, 87%, and 68%, respectively. The 10-year probabilities of OS for ALL were 89% and 80% for good (score 0 or 1) and poor risk (score 2), respectively. Identifying children at risk for late mortality with early intervention may mitigate some excess late mortality.
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 | 0.004 |
| 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 | 0.001 |
| 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".