Abstract | PURPOSE: METHODS: Our cross-sectional, case-only study consisted of 1,058 White Americans and 991 Black Americans from the North Carolina-Louisiana Prostate Cancer ( PCaP) project. Diabetes status was determined by self-report. Obesity was determined using body mass index and calculated based on anthropometric measurements. High aggressive prostate cancer was defined as Gleason sum ≥8, or prostate-specific antigen >20 ng/ml, or Gleason sum = 7 and clinical stage cT3-cT4. The association between diabetes and obesity with high aggressive prostate cancer at diagnosis was evaluated using multivariable logistic regression and adjusted for potential confounders. RESULTS: Diabetes was not associated with high aggressive prostate cancer in the overall sample (OR 1.04; 95% CI 0.79, 1.37), White Americans (OR 1.00; 95% CI 0.65, 1.57) or Black Americans (OR 1.07; 95% CI 0.75, 1.53). Obesity, independent of diabetes, was positively associated with high aggressive prostate cancer in White Americans (OR 1.98; 95% CI 1.14, 3.43), but not in the overall sample (OR 1.37; 95% CI 0.99, 1.92) or Black Americans (OR 1.09; 95% CI 0.71, 1.67). CONCLUSIONS:
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Authors | Saira Khan, Jianwen Cai, Matthew E Nielsen, Melissa A Troester, James L Mohler, Elizabeth T H Fontham, Laura H Hendrix, Laura Farnan, Andrew F Olshan, Jeannette T Bensen |
Journal | Cancer causes & control : CCC
(Cancer Causes Control)
Vol. 27
Issue 12
Pg. 1475-1485
(Dec 2016)
ISSN: 1573-7225 [Electronic] Netherlands |
PMID | 27830399
(Publication Type: Journal Article)
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Chemical References |
- Prostate-Specific Antigen
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Topics |
- Black or African American
(statistics & numerical data)
- Aged
- Case-Control Studies
- Cross-Sectional Studies
- Diabetes Mellitus
(epidemiology, ethnology)
- Humans
- Louisiana
(epidemiology)
- Male
- Middle Aged
- Neoplasm Grading
- North Carolina
(epidemiology)
- Obesity
(epidemiology, ethnology)
- Prostate-Specific Antigen
(metabolism)
- Prostatic Neoplasms
(epidemiology, ethnology, metabolism)
- Self Report
- White People
(statistics & numerical data)
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