Improvement in Dermatomyositis Rash Associated With the Use of Antiestrogen Medication
Bibliographic record
Abstract
BACKGROUND: Dermatomyositis (DM) is an autoimmune disorder that occurs more often in women than men and causes highly symptomatic and inflammatory cutaneous and proximal muscle disease. Corticosteroids have been the treatment of choice for myositis in DM, and antimalarial agents for the skin disease of DM, with methotrexate sodium, azathioprine, mycophenolate mofetil, cyclosporine, and intravenous immunoglobulin used as steroid-sparing agents. Recently, reports supporting a role for anti-tumor necrosis factor alpha (TNF-alpha) therapy in the treatment of DM have emerged. OBSERVATIONS: We describe 2 women who experienced an improvement in their DM-associated skin eruptions while taking antiestrogen medication. The first patient was taking tamoxifen, a selective estrogen receptor modulator that has been found to have anti-TNF-alpha properties. The second was taking anastrozole, an aromatase inhibitor. When tamoxifen therapy was discontinued after 4 years of use in the first patient, her DM rash worsened and remained difficult to control with conventional immunosuppressant medication. CONCLUSIONS: With the limited number of therapies available to manage DM skin eruptions, the discovery of novel agents effective in treating this disease is vital. Using antiestrogen medication in women with DM may result in a significant improvement in their rash, possibly via the inhibition of TNF-alpha production by immune or other cells. Further investigation into the use of antiestrogen therapy in DM is merited to evaluate long-term risks and benefits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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".