Circulating Angiogenic Factors Associated with Response and Survival in Patients with Acute Graft-versus-Host Disease: Results from Blood and Marrow Transplant Clinical Trials Network 0302 and 0802
Bibliographic record
Abstract
Circulating angiogenic factors (AF) reflect tissue healing capacity, although some AF can also contribute to inflammation and are indicative of endothelial dysfunction. The AF milieu in acute graft-versus-host disease (aGVHD) has not been broadly characterized. We hypothesized that patients with abundant AF involved in repair/regeneration versus those mediating damage/inflammation would have improved outcomes. Circulating AF known predominantly for repair/regeneration (epidermal growth factor [EGF], fibroblast growth factor-1 and -2, heparin binding-EGF-like growth factor, and vascular endothelial growth factor-A [VEGF-A], -C, and -D) and for damage/inflammation (angiopoietin-2, endothelin-1, soluble endoglin [sEng], follistatin [FS], leptin, and placental growth factor [PlGF]) were measured in a discovery set of hematopoietic cell recipients with grade III and IV aGVHD and compared with controls, then validated in 2 aGVHD cohorts enrolled in Blood and Marrow Transplant Clinical Trials Network (BMT CTN) trials 0302 (n = 105, serum) and 0802 (n = 158, plasma) versus controls without aGVHD (n = 53, serum). Levels of EGF and VEGF-A were lower than in controls at the onset of aGVHD in both trials and higher with complete response to first-line aGVHD therapy in CTN 0802. FS and PlGF were elevated in aGVHD measured in either serum or plasma. At day 28 after initial aGVHD therapy, elevated FS was an independent negative prognostic factor for survival in both cohorts (hazard ratio, 9.3 in CTN 0302; 2.8 in CTN 0802). These data suggest that circulating AF are associated with clinical outcomes after aGVHD and, thus, may contribute to both pathogenesis and recovery.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".