Renal angiosarcoma: a case report and literature review.
Bibliographic record
Abstract
PURPOSE: In adults renal cell carcinoma (RCC) accounts for over 85% of all diagnosed renal cancers. A much more rare and aggressive malignant tumor of the kidney is angiosarcoma (AS) with less than 25 cases described internationally. Both RCC and AS have similar radiological appearances and thus require histological evaluation for definitive diagnosis. We present a case of renal AS in a 63-year old male who was initially radiologically diagnosed as RCC, and review the current renal AS literature. METHODS: The current English literature from 1981 and onwards on renal AS was reviewed and compared to our current case. RESULTS: The median age and sex of patients with renal AS at presentation was 63 years old (mean 61 years) and common in males with a left kidney predominance. Symptoms included flank pain, palpable mass, and hematuria with imaging suggestive of RCC. Hematogenous metastatic spread often occurred with median survival time of 3.5 months from time of diagnosis (mean 5.8 months). Histologically, the tumors have classical features of angiosarcoma with numerous blood-filled vascular spaces lined by plump pleomorphic endothelial cells with CD31 and CD34 staining positivity. Overall treatment was radical nephrectomy with radiation therapy for local control and metastases. The use of chemotherapy was not consistent. CONCLUSION: Although RCC accounts for the majority of malignant renal tumors, the poor prognosis of AS and its similar radiological appearance to RCC imparts the importance of histological evaluation and the potential radiological mimicry of AS.
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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 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| 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".