Real-world use of upadacitinib in refractory giant cell arteritis: a case report
Bibliographic record
Abstract
Giant cell arteritis (GCA) is an autoimmune disease that predominantly affects individuals over 50 years of age by causing inflammation typically in the temporal and cranial arteries. While glucocorticoids like prednisone are the first-line treatment for GCA, glucocorticoid monotherapy is often inadequate for preventing disease flares and is associated with significant side effects when long-term use is required, necessitating the exploration of alternative therapies. Tocilizumab (TCZ) has proven effective as a steroid-sparing agent; however, some patients may respond inadequately or develop adverse events. Treatment with the Janus kinase (JAK) inhibitor upadacitinib (UPA) has recently emerged as a potential alternative therapy for refractory GCA, and its phase III clinical trials successfully demonstrated its efficacy for GCA patients, with or without prior treatment with TCZ. It has also been recently approved by both the European Commission and the U.S. Food and Drug Administration for GCA. However, real-world data on the efficacy of UPA in GCA remain scarce. This case report describes an 82-year-old woman with GCA refractory to both prednisone and TCZ, who reported severe side effects and decreased quality of life from the latter medication. Treatment with UPA resulted in substantial improvements in symptoms, including headaches and fatigue, with minimal negative responses. This outcome demonstrates the potential of UPA as a promising treatment option for GCA patients who are unresponsive or intolerant to current standard therapies. Further real-world studies are warranted to validate UPA's long-term safety and efficacy in treating GCA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".