Abstract 901: Prediagnostic body mass index (BMI), plasma C-peptide levels, and cigarette smoking predict prostate cancer-specific and overall mortality: A 27-year survival analysis in men with PCa
Bibliographic record
Abstract
Abstract Background: Widespread PSA screening significantly increased prostate cancer (PCa) detection but has limited ability to predict PCa and overall mortality. A major challenge is thus to identify risk factors that can predict the cases that will progress to fatal outcomes. Elevated BMI, hyperinsulinemia, and smoking status have been linked to fatal (but not incident) PCa but their roles in predicting overall and PCa-specific mortality in men with PCa has not yet been fully and simultaneously evaluated. Methods: BMI (kg/m2) and smoking status were available at baseline (1982) in the Physicians’ Health Study participants without prior diagnosis of cardiovascular disease (CVD) or cancer. Between 1982 and 2009, 2,715 men were diagnosed with PCa; baseline C-peptide levels in plasma were available for 827 of them. We used proportional hazard ratios (HR) to estimate risk of overall and cause-specific mortality (PCa, CVD, and other causes). Results: During the 27-year follow-up, 882 (33%) men with PCa died: 11% of PCa, 6% of CVD and 16% of other causes. In the multivariate model including both BMI and smoking status controlling for age at diagnosis, time between baseline and PC diagnosis, and competing risk, the HRs (95% confidence interval, CI) associated with a 5 kg/m2 increment in baseline BMI were 1.52 (1.23-1.89; Ptrend=0.0001) for PCa mortality, 1.35 (0.98-1.86; Ptrend=0.07) for CVD mortality, and 1.24 (1.08-1.41; Ptrend=0.002) for overall mortality. Compared to never smokers, current smokers at baseline had significantly higher risk of PCa mortality (HR=1.67; 1.15-2.44), CVD mortality (HR= 2.39; 1.46-3.91), and overall mortality (HR=2.08; 1.68-2.59). Further controlling for clinical stage and Gleason grade slightly attenuated the associations, but most, except smoking and PCa mortality, remained statistically significant. Elevated C-peptide levels were significantly associated with higher risk of fatal outcomes; the HRs for each increment in C-peptide were 1.18 (1.02-1.37; Ptrend=0.03) for PCa mortality and 1.12 (1.03-1.22; Ptrend=0.006) for total mortality, independent of BMI, smoking, clinical stage, and Gleason grade. After excluding current smokers, the associations of BMI and C-peptide became stronger for PCa mortality. Conclusions: This study in US physicians diagnosed with PCa showed that only a third of the deaths were due to PCa. Prediagnostic BMI, hyperinsulinemia, and smoking are significant and independent predictors for progression to fatal PCa and overall mortality among men with PCa. These findings underscore the importance of identifying and preventing these risk factors in men with PCa to reduce fatal outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 901.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".