Myeloablative versus Reduced-Intensity Conditioning in Patients with Myeloid Malignancies: A Propensity Score-Matched Analysis
Bibliographic record
Abstract
Reduced-intensity conditioning (RIC) has been shown to have similar overall survival (OS) but higher relapse rates compared with myeloablative (MAC) regimens in patients with myeloid malignancies undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). Using propensity score matching (PSM) analysis, well-balanced pairs of different variables can be compared effectively. We retrospectively compared allo-HSCT recipients with acute myeloid leukemia or myelodysplasia receiving a RIC regimen (FBT200; fludarabine 30 mg/m 2 /day for 4 days, busulfan 3.2 mg/kg/day for 2 days, and total body irradiation [TBI] 200 cGy) or MAC regimen (FBT400; fludarabine 50 mg/m 2 /day for 4 days, busulfan 3.2 mg/kg/day for 4 days, and TBI 400 cGy). A total of 248 patients (121 in the RIC group and 127 in the MAC group) were included in the analysis. No statistically significant difference was observed in 2-year OS (RIC group, 45.2 ± 5.0%; MAC group, 51.7 ± 5.2%; P = .541), nonrelapse mortality (NRM; RIC group, 28.7 ± 2.8% MAC group, 34.7 ± 4.6%; P = .368), and acute graft-versus-host disease (GVHD) ( P = .171) or chronic GVHD ( P = .605) at 1 year. The cumulative incidence of relapse (CIR) at 2 years was statistically significantly different between the 2 groups, however (RIC, 26.1 ± 2.6%; MAC, 14.2 ± 3.5%; P = .033). When PSM was applied to the study population, 42 case-control pairs were evenly matched. PSM analysis confirmed no statistically significant difference in 2-year OS (RIC, 49.0 ± 9.1%; MAC, 54.9 ± 7.7%; P = .718), NRM (RIC, 22.2 ± 2.3%; MAC, 33.3 ± 2.8%; P = .238), or CIR (RIC, 25.7 ± 2.6%; MAC, 9.5 ± 1.1%; P = .315) in the PSM pairs. Our findings demonstrate that after applying PSM, FBT 200 RIC conditioning has comparable OS, NRM, and CIR to FBT 400 MAC conditioning before allo-HSCT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".