A Progesterone-Receptor-Positive Huge Retroperitoneal Tumour Mimics Metastasis in a Breast Cancer Patient: Sarcomatoid Renal Cell Carcinoma
Bibliographic record
Abstract
We report a rare case of breast cancer concomitant with progesterone-receptor-positive renal cell carcinoma. A 48-year-old woman was diagnosed as having infiltrating ductal carcinoma of the breast and underwent modified radical mastectomy. A synchronous retroperitoneal tumour was detected by sonography of the abdomen in a routine cancer staging. Initially, the tumour was diagnosed as a synchronous retroperitoneal metastasis by needle biopsy; further tests revealed that it was progesterone receptor-positive. The retroperitoneal tumour showed poor response to full courses of adjuvant chemotherapy for breast cancer. Subsequently, the patient underwent a radical operation that included nephrectomy. The final pathology confirmed a sarcomatoid renal cell carcinoma. The post-operative course was uneventful. The patient had no recurrence at the 1-year follow-up. In this report, accurate diagnosis and adequate treatment were discussed. An intra-abdominal tumour with progesterone receptor- (PR) positive features is usually considered to be metastatic in breast cancer patients. For breast cancer patients with a PR-positive retroperitoneal tumour, renal cell carcinoma should be differentiated from a metastatic lesion of breast cancer, even if PR-expression is rare in renal cell carcinoma. To the best of our knowledge, this is the first case of PR-positive expression in breast cancer concomitant with renal carcinoma. In clinical settings, it is challenging for the surgeon to make an accurate diagnosis and to provide prompt treatment in such cases.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".