Native kidney small renal masses in patients with kidney transplants: Does chronic immunosuppression affect tumor biology?
Bibliographic record
Abstract
INTRODUCTION: We compared clinicopathological characteristics and outcomes of radical nephrectomy (RN) for small renal masses (SRM) in patients with end-stage renal disease (ESRD) before or after transplant at a high-volume urologic and transplant center. METHODS: We performed a retrospective review of patients with ESRD (glomerular filtration rate [GFR] <15 mL/min) who underwent RN for suspected malignant SRM from 2000-2018. Group 1 consisted of patients who underwent RN after transplant; group 2 underwent RN prior to transplant, and group 3 underwent RN without subsequent transplant. Dominant tumor size and histopathological characteristics, recurrence, and survival outcomes were compared between groups. Chi-squared and Mann-Whitney U tests were used to compare categorical and continuous baseline and histopathologic characteristics, respectively. Univariate analysis and log rank test were used to compare RCC recurrence rates. RESULTS: We identified 34 nephrectomies in group 1, 27 nephrectomies in group 2, and 70 nephrectomies in group 3. Median time from transplant to SRM radiological diagnosis in group 1 was 87 months, and three months from diagnosis to nephrectomy for all groups. There were no statistically significant differences between pathological dominant mass size, histological subtype breakdown, grade, or stage between the groups. Rates of benign histology were similar between the groups. Univariate analysis did not reveal a statistically significant difference in recurrence-free survival between the groups (p=0.9). CONCLUSIONS: Patients undergoing nephrectomy before or after transplant for SRM have similar indolent clinicopathological characteristics and low recurrence rates. Our results suggest that chronic immunosuppression does not adversely affect SRM biology.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".