Upper Gastrointestinal Bleeding as a Metastatic Manifestation of Breast Cancer: A Case Report and Review of the Literature
Bibliographic record
Abstract
CASE PRESENTATION: A 64-year-old woman with known metastatic lobular breast cancer presented with fever, epigastric pain, hematemesis, and melena. A bleeding, ulcerated gastric metastasis was found and was treated with endoscopic therapy, omeprazole, and hormonal therapy. The patient was alive and well 13 months later. The bleeding was probably precipitated by necrosis of the lesion during chemotherapy. DISCUSSION: Gastrointestinal tract metastases from primary breast carcinoma are present in 14% to 35% of cases in autopsy series, with gastric involvement in 6% to 18% of cases. Recognized much less commonly during life than in autopsy studies, they can occur anywhere in the gut and can mimic virtually any gastrointestinal disorder. Endoscopy and barium studies facilitate diagnosis. Gastric lesions that have been noted include "linitis plastica", nodules, polyps, and ulcers. They are usually due to lobular breast carcinoma and resemble primary gastric carcinoma on microscopy. Reported cases of bleeding gastric metastases have been treated successfully with various local and systemic modalities. The median survival time of reviewed cases was four months from presentation (with a range of zero to 24 months). CONCLUSIONS: Gastrointestinal metastasis is an underdiagnosed complication of breast cancer. Gastrointestinal bleeding from metastatic breast cancer is an uncommon presentation that is readily diagnosed and that can be treated successfully by endoscopic hemostatic therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".