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Record W2085471026 · doi:10.1158/1538-7445.am10-901

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

2010· article· en· W2085471026 on OpenAlexaff
Jing Ma, Jorge E. Chavarro, Weiliang Qiu, Bernard Rosner, Lorelei A. Mucci, Howard D. Sesso, Michaël Pollak, Meir J. Stampfer

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineBody mass indexHazard ratioProstate cancerInternal medicineProportional hazards modelCancerConfidence intervalHyperinsulinemiaMultivariate analysisOncologyObesityInsulin resistance

Abstract

fetched live from OpenAlex

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.331
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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