The impact of renal cell carcinoma histopathological subtype on disease prognosis: A Canadian multi-institutional analysis.
Bibliographic record
Abstract
480 Background: Renal cell carcinoma (RCC) is divided into several histopathological subtypes, each with significantly different clinical features. However, current data regarding the prognostic value of histological subtype is limited and conflicted. We examined the impact of RCC histology on disease prognosis in a large, multi-institutional Canadian analysis. Methods: The Canadian Kidney Cancer Information System (CKCis), a prospective database from 14 Canadian institutions, was utilized for the study. 1284 patients with non-metastatic RCC, who underwent surgical intervention with curative intent, were included in the study. Patients were stratified according to their primary histology and the Chi-squared test was used to determine associations between histopathology and clinical features. The impact of histology of disease-free survival (DFS) was determined with a multivariate analysis adjusted for age, gender, tumor size, tumor grade, and pathological stage. Results: Clear cell RCC was the most prevalent histological subtype found in 80.5% of patients. Histopathology was significantly associated with patient age, tumor grade, and pathological stage. Advanced stage disease (>T3) was associated with clear cell and papillary type II RCC (p<0.05). 90.7%, 86.7%, 78.5%, and 78.8% of patients with chromophobe, papillary type I, papillary type II, and clear cell RCC respectively, were free of disease after a median follow-up of 1.2 years. On multivariate analysis, histological subtype was a significant predictor of disease-free survival (DFS). When compared to clear cell histology, chromophobe RCC had a significantly higher DFS (HR=0.38, 95% CI 0.15-0.95, p<0.05), and papillary type I RCC had a trend towards a lower rate of disease progression (HR=0.31, 95% CI 0.08-1.28, p=0.05). Conclusions: This study demonstrates that histological subtype impacts disease progression. Histological subtype was independently associated with DFS in surgically treated RCC, specifically chromophobe RCC was shown to have the highest DFS. This may be used to help individualize patient treatment and follow-up based on primary tumor histology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".