Tofacitinib therapy in refractory inflammatory myositis: a retrospective cohort study of 41 patients
Bibliographic record
Abstract
OBJECTIVES: To evaluate the efficacy and safety of tofacitinib in treatment-refractory inflammatory myositis in a real-world clinical setting. METHODS: All patients with refractory inflammatory myositis treated with tofacitinib from a single urban centre in Vancouver, British Columbia, Canada, were included from June 2016 to December 2022. The medical records of these patients were retrospectively reviewed. RESULTS: A total of 41 patients were included, 23 with classic DM, 12 with amyopathic DM (ADM) and six with PM phenotype. The patients failed an average of four to five non-steroidal immunosuppressants before initiation of tofacitinib. In the classic DM and ADM group, tofacitinib offered clinically and statistically significant cutaneous improvement. In all myositis patients including the PM phenotype, no meaningful muscle strength response to tofacitinib was observed. 53.7% of the patients discontinued tofacitinib due to lack of benefit or death. Of the 19 patients who remained on tofacitinib at the conclusion of this study, tofacitinib demonstrated clinically and statistically significant improvement in cutaneous disease activity. CONCLUSION: Tofacitinib appears to be highly effective in targeting cutaneous manifestations in classic DM and ADM; however, minimal benefit in muscle strength in the DM or PM phenotype were observed.
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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 | 0.000 | 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 | 0.000 |
| 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".