Incidence, Risk Factors, and Long-Term Outcomes of Sclerotic Graft-versus-Host Disease after Allogeneic Hematopoietic Cell Transplantation
Bibliographic record
Abstract
Sclerotic chronic graft-versus-host disease (sclGVHD) is associated with significant morbidity and a poor quality of life. We reviewed 502 patients diagnosed with chronic GVHD and analyzed the incidence and risk factors of sclGVHD and long-term outcomes and immunosuppressive therapy (IST) cessation in patients with sclGVHD. With a median onset at 18 months the cumulative incidence of sclGVHD was estimated at 22.6% at 5 years (95% confidence interval, 18.6% to 26.8%). Univariate and multivariate analysis identified 2 risk factors for sclGVHD: non-T cell depletion (hazard ratio [HR] 9.09, P < .001) and peripheral blood stem cell (HR 3.87, P < .001). Overall survival (OS) at 5 years was significantly better in the sclGVHD group (88.1%) compared with the non-sclGVHD group (62.7%; P < .001), as were nonrelapse mortality (7.3% versus 21.5% at 5 years) and relapse rates (9.1% versus 19.3% at 5 years). There was no difference in the rate of IST cessation at 5 years (44.8% versus 49.9%, P = .312), but there was a trend of longer IST duration in the sclGVHD group compared with the non-sclGVHD group (median 71.6 months versus 62.9 months). In conclusion, T cell depletion and graft source affect the risk of sclGVHD. SclGVHD did not adversely affect long-term outcomes or IST duration.
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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 | 0.001 | 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".