Treatment options for patients with acute myeloid leukemia with a matched sibling donor
Bibliographic record
Abstract
BACKGROUND: The role of allogeneic bone marrow transplantation (BMT) in the consolidation of young adults with acute myeloid leukemia (AML) with matched sibling donors (MSD) is controversial. Although BMT is associated with increased event free survival compared with intensive chemotherapy (CT) consolidation, BMT also is associated with increased treatment-related mortality and likely decreased quality of life and life expectancy in patients who do not develop recurrent disease. METHODS: The authors used decision analysis to compare three strategies for maximizing quality-adjusted life years (QALYs) in patients with AML in first remission with an MSD: BMT All, BMT None (consolidation CT only), or BMT in high-risk patients, as defined by baseline cytogenetic testing (Test strategy). A second decision-analysis tree was then constructed that compared BMT with CT specifically for patients with intermediate cytogenetics. RESULTS: Using expected QALYs as the outcome measure, the Test, BMT All, and BMT None strategies were associated with 20.10 QALYs, 19.63 QALYs, and 18.38 QALYs, respectively. Thus, the Test strategy, with CT for low-risk patients and BMT for intermediate risk and high-risk patients, was expected to be the optimal strategy. In the intermediate cytogenetic decision analysis, although the expected QALY for BMT recipients was higher compared with CT recipients (19.78 QALYs vs. 18.75 QALYs), because of uncertainty in variable estimates, the optimal choice was less clear. CONCLUSIONS: CT consolidation is a reasonable option for patients with AML who have favorable cytogenetics, even if an MSD is available. This model provides a framework from which patients with AML and their physicians can make decisions about consolidation therapy.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".