Organ Changes Associated with Provider-Assessed Responses in Patients with Chronic Graft-versus-Host Disease
Bibliographic record
Abstract
Assessments of overall improvement and worsening of chronic graft-versus-host disease (GVHD) manifestations by the algorithm recommended by National Institutes of Health (NIH) response criteria do not align closely with those reported by providers, particularly when patients have mixed responses with improvement in some manifestations but worsening in others. To elucidate the changes that influence provider assessment of response, we used logistic regression to generate an overall change index based on specific manifestations of chronic GVHD measured at baseline and 6 months later. We hypothesized that this overall change index would correlate strongly with overall improvement as determined by providers. The analysis included 488 patients from 2 prospective observational studies who were randomly assigned in a 3:2 ratio to discovery and replication cohorts. Changes in bilirubin and scores of the lower gastrointestinal tract, mouth, joint/fascia, lung, and skin were correlated with provider-assessed improvement, suggesting that the main NIH response measures capture relevant information. Conversely, changes in the eye, esophagus, and upper gastrointestinal tract did not correlate with provider-assessed response, suggesting that these scales could be modified or dropped from the NIH response assessment. The area under the receiver operator characteristic curve in the replication cohort was 0.72, indicating that the scoring algorithm for overall change based on NIH response measures is not well calibrated with provider-assessed response.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".