Renal Cell Carcinoma in the Native and Allograft Kidneys of Renal Transplant Recipients
Bibliographic record
Abstract
PURPOSE: Renal cell carcinoma develops in renal transplant recipients 30 or more times more commonly than in the general population. We assessed the prevalence, histology and outcome of renal cell carcinoma in a large, single center recipient population. MATERIALS AND METHODS: We examined outcomes in patients who underwent renal transplantation at our center to determine the prevalence, histology and outcome of those in whom renal cell carcinoma developed. RESULTS: A total of 3,568 patients received a renal allograft at our institution between 1966 and 2009. A total of 45 renal cell carcinomas were diagnosed in the native kidney of 39 patients (1.1%) and in 8 (0.2%) renal cell carcinoma developed in the allograft kidney. Mean age at diagnosis was 51.6 and 48.2 years in patients with native kidney and allograft tumors, respectively. The mean interval between transplantation and the native or allograft renal cell carcinoma diagnosis was 10.6 and 12.1 years, respectively. Clear cell renal cell carcinoma was the most common tumor histology in native kidneys, diagnosed in 21 cases, while papillary renal cell carcinoma was diagnosed in 20. Five allograft tumors were papillary renal cell carcinoma and 3 were clear cell renal cell carcinoma. Native kidney tumors were managed by radical nephrectomy in 44 or by observation after biopsy. Allograft tumors were managed by transplant nephrectomy in 3 cases, radio frequency ablation in 3 and partial nephrectomy in 2. At a mean 6.6-year followup 32 patients with native kidney renal cell carcinoma were alive while 7 with allograft tumors were alive at a mean 3.6-year followup. CONCLUSIONS: Renal cell carcinoma is more prevalent in patients with renal transplantation than the general population, although the subtype distribution differs. Excellent survival is seen at more than 6 years after treatment.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".