Early and Late Extensive Chronic Graft-versus-Host Disease in Children Is Characterized by Different Th1/Th2 Cytokine Profiles: Findings of the Children's Oncology Group Study ASCT0031
Bibliographic record
Abstract
Numerous mechanisms underlie chronic graft-versus-host disease (cGVHD), including skewing of Th1/Th2 cytokine expression. There are biological differences between early-onset and late-onset cGVHD. To test whether different Th1/Th2 cytokines are associated with early- or late-onset cGVHD, peripheral blood was collected from 63 children enrolled on the Children's Oncology Group Phase III trial ASCT0031 evaluating hydroxychloroquine therapy for newly diagnosed extensive cGVHD. mRNA expression of interferon (IFN)-γ and interleukin (IL)-2, -4, and -10 from stimulated peripheral blood mononuclear cells was evaluated by quantitative polymerase chain reaction. Early-onset cGVHD (n = 33) was characterized by decreased expression of IFN-γ and IL-2 mRNA after nonspecific phorbol 12-myristate 13-acetate-ionomycin stimulation. In contrast, late-onset cGVHD (n = 11) was characterized by decreased expression of IL-4 and IL-2 mRNA after anti-CD3 stimulation of T cells. Receiver-operating characteristic curve analysis revealed that IFN-γ expression was correlated with the absence of early cGVHD (area under the curve [AUC] = 0.77) and that IL-4 (AUC = 0.89) and IL-2 (AUC = 0.84) expression was correlated with the absence of late cGVHD. There was no correlation between cytokine expression and a specific immune cell subset. Increased expression of Foxp3 mRNA was seen in early-onset cGVHD and late controls. The different time-dependent cytokine profiles in patients with newly diagnosed cGVHD suggests that the mechanisms underlying cGVHD are temporally regulated. Although larger validation studies are needed, our data suggest that cytokine profiles have a potential use as biomarkers for the diagnosis of cGVHD.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".