Adverse events in second- and third-line treatments for acute and chronic graft- <i>versus</i> -host disease: systematic review
Bibliographic record
Abstract
Background: Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is associated with an increased risk of graft- versus-host disease (GvHD), a strong prognostic predictor of early mortality within the first 2 years following allo-HSCT. The objective of this study was to describe the harm outcomes reported among patients receiving second- and third-line treatment as part of the management for GvHD via a systematic literature review. Methods: A total of 34 studies met the systematic review inclusion criteria, reporting adverse events (AEs) across 12 different second- and third-line therapies. Results: A total of 14 studies reported AEs across nine different therapies used in the treatment of acute GvHD (aGvHD), 17 studies reported AEs of eight different treatments for chronic GvHD (cGvHD) and 3 reported a mixed population. Infections were the AE reported most widely, followed by haematologic events and laboratory abnormalities. Reported infections per patient were lower under extracorporeal photopheresis (ECP) for aGvHD (0.267 infections per patient over 6 months) relative to any of the therapies studied (ranging from 0.853 infections per patient per 6 months under etanercept up to 1.998 infections per patient on inolimomab). Conclusion: The reported incidence of infectious AEs in aGvHD and grade 3–5 AEs in cGvHD was lower on ECP compared with pharmaceutical management.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".