Early lymphocyte recovery at 28 d post‐transplant is predictive of reduced risk of relapse in patients with acute myeloid leukemia transplanted with peripheral blood stem cell grafts
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (HCT) is potentially curative for acute myeloid leukemia (AML). Impact of lymphocyte recovery on post-transplant outcomes has been suggested but reports are conflicting. We evaluated the impact of lymphocyte recovery at 28 d post-HCT in 191 AML patients using peripheral blood stem cells as graft. Patients were divided into those with absolute lymphocyte count (ALC) ≥ 0.5 × 10(9) /L (n = 111, 58%; high ALC group) and those with ALC < 0.5 × 10(9) /L (n = 80, 42%; low ALC group), at day 28 post-transplant. With a median follow-up of 49 months, overall survival (OS) was significantly improved in the high ALC group (59% at 3 yr) vs. patients with low ALC (40% at 3 yr, P = 0.03). Cumulative incidence of relapse (CIR) was significantly lower in the high ALC group (16% at 3 yr) vs. low ALC group (36% at 3 yr, P = 0.001). Multivariable analysis for CIR demonstrated high ALC group as an independent factor decreasing relapse risk (P = 0.03, HR = 0.49, 95% CI = 0.26-0.92). Multivariable analysis for OS and non-relapse mortality did not demonstrate ALC ≥ 0.5 × 10(9) /L at 28 d post-transplant to be predictive. We conclude that lymphocyte recovery with ALC ≥ 0.5 × 10(9) /L at day 28 post-transplant is associated with less relapse in AML patients undergoing allogeneic peripheral blood HCT, but without survival benefit.
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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 | 0.001 |
| 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 | 0.001 |
| 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".