Eccrine Carcinoma Mimicking Breast Cancer: Diagnostic Challenges and Hormone Therapy as an Emerging Treatment
Bibliographic record
Abstract
Eccrine carcinoma is an exceedingly rare malignancy originating from the eccrine sweat glands, representing less than 0.01% of all cutaneous malignancies. The diagnosis of eccrine carcinoma is challenging due to its rarity. Its morphological similarities with other common tumors, especially breast cancer, further complicate assessment. It is crucial to differentiate eccrine carcinoma from metastatic breast cancer. In addition, the standard treatment is also not well established. We present the case of a 66-year-old female with a lesion on her left lip. Initially identified in 2017, the lesion recurred in 2020 and 2023. Surgeries in 2017 and 2020 achieved R0 resections, while the 2023 recurrence was an R2 resection with lymph node metastasis. Pathology suggested a possible primary breast ductal carcinoma. Immunostains were positive for estrogen receptor (ER) and progesterone receptor (PR). However, positron emission tomography/computed tomography (PET/CT) did not reveal any primary breast lesion, and there was no accessory breast tissue involvement, leading to a diagnosis of primary eccrine carcinoma. The patient declined chemotherapy and radiation therapy, opting instead for treatment with letrozole and ribociclib. Six-month follow-up imaging showed reduced lymph node size, suggesting a favorable response to therapy. This case highlights the diagnostic challenges of eccrine carcinoma, given that it mimics malignancies like breast cancer. Hormone therapy may be a potential option for hormone receptor-positive cases. Further research is essential to develop clearer diagnostic tools and standardized treatment protocols for this rare malignancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".