Similar 5-Year Survival after Peripheral Blood Autotransplants (AutoPB) Versus HLA Matched Sibling Myeloablative Transplants (AlloBMT) for Acute Myeloid Leukemia (AML) in First Complete Remission (CR1).
Bibliographic record
Abstract
Abstract Optimum post-remission strategies for AML CR1 remain uncertain. Previous studies comparing autotransplants with alloBMT favored the latter because of less relapse despite treatment-related mortality (TRM) rates of 20–30%. In those studies, the autotransplants were exclusively with bone marrow (BM) and reported TRM of 12–20%. We were interested in determining the effect of lower TRM with AutoPB shown in many series to be 5–10%. We compared TRM, relapse, leukemia-free survival (LFS), and overall survival (OS) of 1133 patients 19–60 years of age in CR1 who underwent HLA-identical myeloablative BM or peripheral blood (PB) allogeneic transplants or AutoPB for AML reported to the CIBMTR from 1995–2004. For alloBM, alloPB and autoPB, median ages were 36, 40 and 44 yrs; cytogenetics were missing/unknown in 26%, 12% and 17%; proportion with poor risk cytogenetics was 6%, 9% and 7%; and median follow-up of survivors was 82 (6–149), 60 (4–144), and 62 (1–139) mo., respectively. Outcomes were evaluated in univariate and by multivariate analyses using the pseudo-value technique. Results: 5 year transplant outcomes by univariate analysis are as follows: Allo BM Allo PB Auto PB Outcomes@5years N Prob (95%CI) N Prob (95%CI) N Prob (95%CI) P-value Relapse 473 20 (17–24) 425 26 (21–30) 227 45 (38–52) <0.001 TRM 473 19 (16–23) 425 20 (17–24) 227 8 (5–12) <0.001 LFS 473 61 (56–65) 425 54 (49–59) 227 47 (40–54) 0.13 Survival 475 64 (59–68) 428 59 (54–64) 230 54 (47–60) 0.19 All analyses showed that risks associated with alloBM and AlloPB were identical, hence relative risk (RR) was modeled for any allotransplant (alloBMT) vs autoPB. Multivariate analysis of alloBMT vs autoPB cohorts revealed that age >40 yrs was associated with increased RR for TRM, LFS and OS at 5yrs:1.39 (1.05–1.84;n=518;p=0.019);1.25(1.04– 1.51;n=521;p=0.015);1.28(1.05–1.56;n=521;p= 0.012), respectively. For relapse at 5 yrs, the presence of extramedullary disease was a poor prognostic factor: [RR: 1.60 (1.13– 2.27); for no n=1036; yes n=88]. Cytogenetics risk category was not a significant covariate for TRM (p=0.84), relapse (p=0.13), LFS (p=0.27) or OS (p=0.062) at 5 yrs. Conclusions: AutoPB may provide acceptable alternative post-remission therapy for AML CR1 in the absence of a matched sibling donor, and its role in this regard should be reinvestigated prospectively.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".