Breast Cancer and Dermatomyositis: A Case Study and Literature Review
Bibliographic record
Abstract
A 49-year-old woman presents with an extensive violaceous rash, rapidly progressive proximal muscle weakness, and dysphagia to solids, consistent with a diagnosis of dermatomyositis. Two weeks later, she palpates a mass in her left breast and is diagnosed with her2-positive metastatic invasive ductal carcinoma of the breast. There is a well-established association between dermatomyositis and malignancy. However, the specific association between breast cancer and dermatomyositis has not been well characterized. No guideline for oncologists managing these patients has been established. Recently, 3 cases of breast cancer and dermatomyositis were diagnosed at our institution. A review of the literature was pursued to characterize the association between breast cancer and dermatomyositis. A review of 178 papers identified 22 cases of breast cancer with dermatomyositis. Most patients (71%) presented with stage iii or iv breast cancer. The median time between the diagnosis of breast cancer and the onset of dermatomyositis symptoms was 1 month. Three quarters of the patients were steroid-responsive and able to taper. Half the women with follow-up data experienced a documented cancer relapse associated with a new flare of cutaneous symptoms. The presence of dermatomyositis appears to be associated with more-advanced breast cancer stage and is most commonly associated with invasive ductal carcinoma. In our review, treatment of cancer alone is insufficient to adequately control the cutaneous and myopathic manifestations of dermatomyositis, which can significantly affect quality of life. A multidisciplinary approach, including close collaboration with rheumatologists and dermatologists, is therefore important in the diagnosis and management of oncology patients with dermatomyositis.
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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) | 0.000 | 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 | 0.000 | 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".