Toward a Better Understanding of the Atypical Features of Chronic Graft-Versus-Host Disease: A Report from the 2020 National Institutes of Health Consensus Project Task Force
Bibliographic record
Abstract
Alloreactive and autoimmune responses after allogeneic hematopoietic cell transplantation can occur in nonclassical chronic graft-versus-host disease (chronic GVHD) tissues and organ systems or manifest in atypical ways in classical organs commonly affected by chronic GVHD. The National Institutes of Health (NIH) consensus projects were developed to improve understanding and classification of the clinical features and diagnostic criteria for chronic GVHD. Although still speculative whether atypical manifestations are entirely due to chronic GVHD, these manifestations remain poorly captured by the current NIH consensus project criteria. Examples include chronic GVHD impacting the hematopoietic system as immune mediated cytopenias, endothelial dysfunction, or as atypical features in the musculoskeletal system, central and peripheral nervous system, kidneys, and serous membranes. These purported chronic GVHD features may contribute significantly to patient morbidity and mortality. Most of the atypical chronic GVHD features have received little study, particularly within multi-institutional and prospective studies, limiting our understanding of their frequency, pathogenesis, and relation to chronic GVHD. This NIH consensus project task force report provides an update on what is known and not known about the atypical manifestations of chronic GVHD while outlining a research framework for future studies to be undertaken within the next 3 to 7 years. We also provide provisional diagnostic criteria for each atypical manifestation, along with practical investigation strategies for clinicians managing patients with atypical chronic GVHD features.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".