Design and Patient Characteristics of the Chronic Graft-versus-Host Disease Response Measures Validation Study
Bibliographic record
Abstract
In 2014, the National Institutes of Health sponsored the second Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-versus-Host Disease (GVHD). The purpose was to update recommendations about key elements of chronic GVHD research, including definitions for diagnosis, severity scoring, and response measures, based on empirical data published since the first 2005 Consensus Conference. The most significant modifications were to the response assessments, based on studies demonstrating difficulty with the first consensus definitions. The Response Measures Validation Study is a multicenter, prospective cohort study of patients who are starting initial or subsequent treatments for chronic GVHD. The aim of the study is to evaluate the performance of the 2014 response measures and determine whether any other combination of assessments is superior. Clinical data, clinician assessments, patient-reported outcomes, and research samples are collected at enrollment and 3, 6, and 18 months later, and whenever another chronic GVHD systemic treatment is added. The target enrollment of 368 evaluable patients from 12 transplantation centers has been reached. This report describes the rationale, design, and methods of the Chronic GVHD Response Measures Validation Study, and invites other investigators to collaborate with the Consortium to analyze data or specimens.
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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 | 0.033 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".