Clinico-pathological analysis of renal cell carcinoma demonstrates decreasing tumour grade over a 17-year period
Bibliographic record
Abstract
INTRODUCTION: Renal cell carcinoma (RCC) represents about 3% of adult malignancies in Ireland. Worldwide there is a reported increasing incidence and recent studies report a stage migration towards smaller tumours. We assess the clinico-pathological features and survival of patients with RCC in a surgically treated cohort. METHODS: A retrospective analysis of all nephrectomies carried out between 1995 and 2012 was carried out in an Irish tertiary referral university hospital. Data recorded included patient demographics, size of tumour, tumour-node-metastasis (TNM) classification, operative details and final pathology. The data were divided into 3 equal consecutive time periods for comparison purposes: Group 1 (1995-2000), Group 2 (2001-2006) and Group 3 (2007-2012). Survival data were verified with the National Cancer Registry of Ireland. RESULTS: In total, 507 patients underwent nephrectomies in the study period. The median tumour size was 5.8 cm (range: 1.2-20 cm) and there was no statistical reduction in size observed over time (p = 0.477). A total of 142 (28%) RCCs were classified as pT1a, 111 (21.9%) were pT1b, 67 (13.2%) were pT2, 103 (20.3%) were pT3a, 75 (14.8%) were pT3b and 9 (1.8%) were pT4. There was no statistical T-stage migration observed (p = 0.213). There was a significant grade reduction over time (p = 0.017). There was significant differences noted in overall survival between the T-stages (p < 0.001), nuclear grades (p < 0.001) and histological subtypes (p = 0.022). CONCLUSION: There was a rising incidence in the number of nephrectomies over the study period. Despite previous reports, a stage migration was not evident; however, a grade reduction was apparent in this Irish surgical series. We can demonstrate that tumour stage, nuclear grade and histological subtype are significant prognosticators of relative survival in RCC.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".