Prognostic Significance of Body Mass Index in Asian Patients With Localized Renal Cell Carcinoma
Bibliographic record
Abstract
We investigated the prognostic value of BMI (body mass index) in Asian patients with RCC (renal cell carcinoma). We evaluated 170 Asian patients who underwent surgery for localized RCC (pathologic T1-4 tumors in the absence of nodal or distant metastases) between 1996 and 2004 at our institution. Patients were stratified by BMI: 22 or less vs. greater than 22. Overall, CSS (cancer-specific survival) and RFS (recurrence-free survival) was estimated using the Kaplan-Meier method. Multivariate analysis was performed with the Cox regression model. The mean age and BMI of all patients was 62.4 ± 11.4 yr and 23.1 ± 3.2 kg/m(2), respectively. Patients' population consisted of 114 (67.1%) men and 56 (32.9%) women. The median follow-up was 50 mo. The BMI was less than 22 in 83 (49%) patients and greater than 22 in 87 (51%). There was a trend toward worse Eastern Cooperative Oncology Group (ECOG) performance status, less likely to have an incidentaloma, higher pathological stage, and more frequent microvascular invasion with lower BMI. Only the correlations between BMI and ECOG performance status (P = 0.003) and pathological stage (P = 0.015) were statistically significant. Of other relevant factors including gender, mode of presentation, ECOG performance status, C-reactive protein, histological type, Fuhrman nuclear grade, microvascular invasion, pathological stage, and adjuvant cytokine therapy, smaller BMI remained an independent predictor for worse CSS (44.5 mo vs. 56.0 mo, P = 0.041, HR = 10.99) and RFS (43.0 mo vs. 55.0 mo, P = 0.03, HR = 2.653), but not for OS (overall survival) (46.0 mo vs. 55.5 mo, P = 0.13, HR = 2.217) on multivariate analysis. Our findings identify increasing BMI in the Asian population as an independent predictor for favorable CSS and RFS in patients with RCC treated by surgery. Further studies, including a multiinstitutional, prospective Asian cohort, are required to confirm these findings.
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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 | 0.000 | 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".