Gastric metastases from primary breast cancers: rare causes of common gastrointestinal disorders
Bibliographic record
Abstract
We report two cases of gastric metastases from primary breast cancers. In case 1, a 31-year-old woman with right-sided ductal breast carcinoma presented with nausea, vomiting and frank haematemesis, 8 months after mastectomy and adjuvant chemotherapy. An esophagogastroduodenoscopy (EGD) revealed multiple ulcerated gastric lesions secondary to metastatic adenocarcinoma from primary breast tumour. In case 2, an 84-year-old woman with a history of left lobular carcinoma presented with early satiety, 17 years after initial mastectomy and adjuvant endocrine therapy. An EGD revealed unspecific gastric mucosa with thickened and erythematous folds and biopsies revealed adenocarcinoma from primary breast carcinoma. Our cases demonstrate how gastric metastases have variable, non-specific clinical and endoscopic presentations. Symptoms may include nausea, vomiting, early satiety and gastrointestinal (GI) bleeding. Endoscopic appearance may range from thickened gastric folds to ulcerating lesions. Our cases demonstrate that gastric metastases should be considered in patients with breast cancer history presenting with GI symptoms.
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 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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".