Renal Metastasis of Small Cell Lung Cancer With Urothelial Carcinoma of the Bladder Misdiagnosed as Renal Cell Carcinoma
Bibliographic record
Abstract
Metastases to the kidney from lung cancer are very rare and are usually therefore recognized at autopsy. A 71-year-old man visited the urology department due to symptoms of worsening hematuria. An abdominal computed tomography scan showed a right renal mass. After a nephrectomy, he was diagnosed with small cell lung carcinoma, and further investigation showed small cell lung cancer in the central area of the left upper lobe with hepatic, bone and brain metastases. But his hematuria was unchanged. Therefore, we additionally diagnosed urothelial cell carcinoma in the bladder by transurethral resection of the bladder tumor. He was treated with etoposide and cisplatin chemotherapy. This is a unique antemortem case report in the literature of small cell lung cancer metastasizing to the contralateral kidney, liver, bone and brain diagnosed concurrently with urothelial cell carcinoma in the bladder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".