Pretransplant bone marrow cellularity and blood count recovery are not associated with relapse or survival risk following allogeneic stem cell transplant for AML in CR
Bibliographic record
Abstract
INTRODUCTION: Allogeneic hematopoietic cell transplantation (HCT) can be curative for acute myeloid leukemia (AML). Novel therapies may render patients' bone marrow hypocellularity and lead to prolonged post-therapy pancytopenia. Patients' bone marrow cellularity (BMC) at pretransplant assessment and post-treatment pancytopenia (classification CR-incomplete [CRi]) may manifest AML persistence. METHODOLOGY: We retrospectively examined the impact of BMC and ELN response (ELNr) on a single-center cohort of 337 patients who underwent allogeneic HCT for AML in CR1. RESULTS: Median follow-up was 33 months. Overall survival (OS) for the whole cohort was 55.8% at 2 years, while cumulative incidence of relapse (CIR) was 20.8%, and non-relapse mortality was 27.5%. OS and CIR were not significantly different between BMC groups; and neither was ELNr. ELNr CRi was associated with BMC aplastic and hypocellular marrow states (P < 2.6e-8). Multivariate analysis confirmed neither BMC nor attainment of ELNr CR vs CRi affected OS or relapse. Significant factors for survival included age at transplant, cytogenetic risk, development of acute Gr II-IV GvHD, and moderate-severe chronic GvHD, while cytogenetic risk and chronic GvHD affected relapse. CONCLUSION: Neither ELNr status nor pretransplant BMC influenced relapse post-HCT or OS. Hypocellularity and CRi are not negative prognostic factors for post-HCT outcomes of AML.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".