Predictors for Treatment Success and Expression of Glucocorticoid Receptor in Giant Cell Arteritis and Polymyalgia Rheumatica
Bibliographic record
Abstract
OBJECTIVE: Giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) generally respond well to treatment with glucocorticoids (GC). We sought to determine the value of clinical, histopathologic, immunohistochemical, and genetic findings and the expression of the glucocorticoid receptor (GR) for discriminating between patients who achieve complete remission, or partial remission, or who do not improve with glucocorticoid treatment. METHODS: We examined biopsies of the temporal artery from 60 patients, of whom 27 had GCA, 13 PMR, and 20 arteriosclerosis. RESULTS: Of the clinical variables evaluated, jaw claudication was correlated with the histologic classification of the biopsies (p < 0.0001). Erythrocyte sedimentation rate was significantly higher in patients with PMR and GCA than in patients with arteriosclerosis (p < 0.0001). There were significant differences between patients with GCA versus PMR in the numbers of CD3-, CD8-, and CD4-positive T cells, in CD68-positive monocytes (p < 0.0001), and antigen-presenting cells (p < 0.0001). CD138-positive and CD20-positive cells were absent in patients with PMR but present in patients with GCA (p < 0.0001). In GCA and chronic inflammation most monocytes and lymphocytes expressed GR (88.9%). The number of CD68-positive cells and the extent of GR-staining in chronic inflammation reflected the success of treatment in logistic regression analysis (p < 0.05). GR polymorphism showed that more than 90% of patients had the wild-type (homozygote) of the R23K or N363S polymorphism. There was no evidence that this polymorphism influenced response to treatment with GC (Fisher's exact test 1.0). CONCLUSION: Expression of GR and the presence of CD20-, CD3-, CD4-, CD8-, CD68-, CD138-positive cells and antigen-presenting cells differ between GCA and PMR. The presence of CD68-positive cells and the extent of GR-staining in chronic inflammation are suitable to predict complete remission in GCA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".