Parotid Gland Mass as the First Manifestation of Recurrent Metastatic Breast Carcinoma: Diagnostic Pitfalls and Therapeutic Considerations in Oral-Maxillofacial Care
Bibliographic record
Abstract
Breast cancer rarely metastasizes to the parotid gland. Early recognition in patients with a history of malignancy is critical for timely diagnosis and treatment. We report the case of a 60-year-old female who presented with a two-month history of a left periauricular mass, 18 months after completing treatment for breast carcinoma. Despite the patient's oncologic history, initial evaluation by our maxillofacial surgery service showed no evidence of distant metastasis, and we initially ruled out metastatic disease. Clinical evaluation, contrast-enhanced computed tomography (CT), fine-needle aspiration cytology (FNAC), PET-CT, and histopathological analysis were performed. Given the persistent and progressive nature of the mass, surgical excision was undertaken to obtain a definitive diagnosis and provide local control. Immunohistochemical analysis of the resected mass and adjacent node confirmed metastatic breast carcinoma infiltrating the parotid parenchyma and an intra-parotid lymph node, with strong positivity for progesterone receptor (PR) and carcinoembryonic antigen (CEA). Unfortunately, several months later, the patient developed pulmonary metastases and subsequently died.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".