Real-world Canadian data on belumosudil therapy in heavily pretreated patients with steroid-refractory chronic graft-versus-host disease: treatment outcomes and risk factor analysis for failure-free survival
Bibliographic record
Abstract
Chronic graft-versus-host disease (cGvHD) remains one of the common causes of morbidity and mortality after allogeneic hematopoietic stem cell transplantation. Belumosudil (BEL), a selective ROCK2 inhibitor, has immunomodulatory and anti-fibrotic properties, offering a new therapeutic option. Real-world data (RWD) in heavily pretreated patients remain limited, particularly for combination of BEL with ruxolitinib (RUX). We conducted a multicenter, real-world study in 46 patients treated for refractory cGvHD with BEL under a Canadian compassionate program. Treatment outcomes were assessed using the NIH consensus response criteria for overall response rate (ORR), failure-free (FFS), overall survival (OS), and safety. Forty-six patients were included with a median follow-up of 11.4 months; the best ORR was 52% (n = 20/38). The FFS and OS rates at 12 months were 64.3% and 91.1%, respectively. Steroids were discontinued in 73% at 12 months. BEL combination therapy with RUX exhibited equivalent treatment outcomes to BEL monotherapy, although patients treated with drug combination presented with more advanced form of GvHD and mostly failed RUX therapy. A prognostic risk model based on prior acute GvHD and involvement of ≥ 4 organs effectively stratified FFS at 12 months: 100% with no risk factors, 75.8% with one, and 30% with two risk factors (HR 3.91, 95% CI 1.58-9.67, p = 0.003). BEL demonstrated durable efficacy and acceptable safety in heavily pretreated cGvHD. BEL treatment was associated with a high probability of corticosteroid withdrawal. Risk stratification by disease burden and prior aGvHD identified distinct prognostic groups, informing patient selection and future therapeutic strategies.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".