Statin-induced anti-HMGCR myopathy: successful therapeutic strategies for corticosteroid-free remission in 55 patients
Bibliographic record
Abstract
OBJECTIVE: To describe successful therapeutic strategies in statin-induced anti-HMGCR myopathy. METHODS: Retrospective data from a cohort of 55 patients with statin-induced anti-HMGCR myopathy, sequentially stratified by the presence of proximal weakness, early remission, and corticosteroid and IVIG use at treatment induction, were analyzed for optimal successful induction and maintenance of remission strategies. RESULTS: A total of 14 patients achieved remission with a corticosteroid-free induction strategy (25%). In 41 patients treated with corticosteroids, only 4 patients (10%) failed an initial triple steroid/IVIG/steroid-sparing immunosuppressant (SSI) induction strategy. Delay in treatment initiation was independently associated with lower odds of successful maintenance with immunosuppressant monotherapy (OR 0.92, 95% CI 0.85 to 0.97, P = 0.015). While 22 patients (40%) presented with normal strength, only 9 had normal strength at initiation of treatment. CONCLUSION: While corticosteroid-free treatment of anti-HMGCR myopathy is now a safe option in selected cases, initial triple steroid/IVIG/SSI was very efficacious in induction. Delays in treatment initiation and, as a corollary, delays in achieving remission decrease the odds of achieving successful maintenance with an SSI alone. Avoiding such delays, most notably in patients with normal strength, may reset the natural history of anti-HMGCR myopathy from a refractory entity to a treatable disease.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".