Overlap chronic GVHD is associated with adverse survival outcomes compared to classic chronic GVHD
Bibliographic record
Abstract
Abstract Background Chronic graft-versus-host-disease (cGVHD) is divided into two subtypes: classic (absence of acute GVHD features) and overlap cGVHD (‘ocGVHD’), in which both chronic and acute GVHD clinical features are present simultaneously. While worse outcomes with ocGVHD have been reported, there are few recent analyses. Methods We performed a secondary analysis of data from the ABA2 trial, in which detailed GVHD data were collected prospectively and systematically adjudicated. Analyses included cumulative incidence of classic versus ocGVHD, their specific organ manifestations, global disease severity scores, non-relapse mortality (NRM), disease-free survival (DFS) and overall survival (OS) in these two cGVHD subtypes. Results The 1-year cumulative incidence, organ involvement, and global severity of classic and ocGVHD were similar between ABA2 patients receiving CNI/MTX + placebo and CNI/MTX + abatacept; thus, cohorts were combined for ocGVHD evaluation. This analysis identified ocGVHD as having significantly higher severity at presentation and at maximum global severity compared to classic cGVHD. OS and DFS were significantly lower for ocGVHD versus classic cGVHD. Conclusion ocGVHD is associated with increased cGVHD severity scores, both at presentation and at maximum disease severity. OcGVHD was also associated with decreased OS and DFS compared to classic cGVHD, underscoring the high risks with this cGVHD subtype.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".