Association between visceral and subcutaneous adiposity and clinicopathological outcomes in non-metastatic clear cell renal cell carcinoma
Bibliographic record
Abstract
INTRODUCTION: Visceral adiposity has been inconsistently associated with clinicopathologic features and outcomes of clear cell renal cell carcinoma (ccRCC); however, most studies were conducted in non-Western populations. We evaluated the associations between visceral and subcutaneous adiposity and clinicopathological characteristics of non-metastatic ccRCC patients in a Western population. METHODS: The medical records of 220 surgically treated ccRCC patients with documented preoperative body mass index (BMI) and computed tomography (CT) scans were retrospectively reviewed. Nineteen patients with stage IV disease were excluded. Visceral (VFA) and subcutaneous fat area (SFA) were computed from pre-operative CT scans. Correlations between obesity measures were assessed with Pearson correlation. Associations between obesity measures and pathologic features were evaluated using logistic regression models adjusted for sex. Overall survival (OS) probabilities were estimated using Cox regression analysis. The log-rank test was used for group comparisons. RESULTS: The study cohort comprised 150 men and 51 women. Women had higher SFA (p = 0.01) but lower VFA (p < 0.001) than men. BMI was highly correlated with SFA (r = 0.804) and moderately correlated with VFA (r = 0.542). SFA and VFA were weakly correlated (r = 0.367). An increased BMI was associated with a better OS (p = 0.028). When adjusting for sex, neither SFA nor VFA was significantly associated with tumour grade, stage, or OS. CONCLUSIONS: Consistent with prior reports, our study suggests that increased BMI is associated with a better OS for patient with nonmetastatic ccRCC. Despite the high correlation between SFA and BMI, neither SFA nor VFA were significantly associated with tumour stage, grade, or OS in the current study; however, further studies in larger cohorts are required to validate this finding.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".