Risk factors for acute GVHD and survival after hematopoietic cell transplantation
Bibliographic record
Abstract
Risk factors for acute GVHD (AGVHD), overall survival, and transplant-related mortality were evaluated in adults receiving allogeneic hematopoietic cell transplants (1999-2005) from HLA-identical sibling donors (SDs; n = 3191) or unrelated donors (URDs; n = 2370) and reported to the Center for International Blood and Marrow Transplant Research, Minneapolis, MN. To understand the impact of transplant regimen on AGVHD risk, 6 treatment categories were evaluated: (1) myeloablative conditioning (MA) with total body irradiation (TBI) + PBSCs, (2) MA + TBI + BM, (3) MA + nonTBI + PBSCs, (4) MA + nonTBI + BM, (5) reduced intensity conditioning (RIC) + PBSCs, and (6) RIC + BM. The cumulative incidences of grades B-D AGVHD were 39% (95% confidence interval [CI], 37%-41%) in the SD cohort and 59% (95% CI, 57%-61%) in the URD cohort. Patients receiving SD transplants with MA + nonTBI + BM and RIC + PBSCs had significantly lower risks of grades B-D AGVHD than patients in other treatment categories. Those receiving URD transplants with MA + TBI + BM, MA + nonTBI + BM, RIC + BM, or RIC + PBSCs had lower risks of grades B-D AGVHD than those in other treatment categories. The 5-year probabilities of survival were 46% (95% CI, 44%-49%) with SD transplants and 33% (95% CI, 31%-35%) with URD transplants. Conditioning intensity, TBI and graft source have a combined effect on risk of AGVHD that must be considered in deciding on a treatment strategy for individual patients.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".