Abstract 4501: Energetic risk and prostate cancer-specific and all-cause mortality in two large cohorts of men with localized prostate cancer
Bibliographic record
Abstract
Abstract Objective: To examine whether high energetic risk predisposes men with localized prostate cancer (PC) to higher risk of PC-specific mortality or all-cause mortality. Methods: Among men with localized PC, prediagnostic body mass index (BMI) and plasma C-peptide (a marker of insulin production) were available for 691 men (301 overall deaths, 78 PC deaths) in the Physicians’ Health Study (discovery set) and 1111 men (262 overall deaths, 56 PC deaths) in the Health Professionals Follow-up Study (validation set). High energetic risk was defined as BMI 25-29.9 kg/m2 and C-peptide in the highest quartile or BMIα30 kg/m2. We used the Cox-regression model to estimate risk, adjusting for age, smoking, diabetes, and D'Amico risk defined by stage, Gleason grade and prostate-specific antigen (PSA). Results: Results were similar in both cohorts; the combined hazard ratio (HR)s (95% confidence interval, CI) associated with high energetic risk (25% of study population) were 2.2 (1.5-3.3) for PC-specific mortality and 1.4 (1.1-1.7) for all-cause mortality. The risk of PC-specific mortality according to low- intermediate-, or high-D'Amico risk were 1.0 (reference), 2.6, 6.4 for low energetic risk, and 5.0, 6.1, 9.4 for high energetic risk. The corresponding HRs for all-cause mortality were 1.0 (reference), 1.3, 2.1, 2.1, 2.1, and 2.3. Compared to D'Amico risk alone, incorporating energetic risk significantly improved the predictability of PC-specific mortality (C-statistic from 0.72 to 0.78, P<0.001). Conclusion: Adding energetic risk to D'Amico risk groups significantly improved prediction of PC-specific and all-cause mortality, and identifies 20% D'Amico “low-risk” patients who may be poor candidates for active surveillance. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4501. doi:1538-7445.AM2012-4501
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".