A 25-Year Prospective Study of Plasma Adiponectin and Leptin Concentrations and Prostate Cancer Risk and Survival

Abstract Background: Adipocytokines may mediate the association between adiposity and lethal prostate cancer outcomes. Methods: In the Physicians’ Health Study, we prospectively examined the association of prediagnostic plasma concentrations of adiponectin and leptin with risk of developing incident prostate cancer (654 cases diagnosed 1982–2000 and 644 age-matched controls) and, among cases, risk of dying from prostate cancer by 2007. Results: Adiponectin concentrations were not associated with risk of overall prostate cancer. However, men with higher adiponectin concentrations had lower risk of developing high-grade or lethal cancer (metastatic or fatal disease). The relative risk (95% CI) comparing the highest quintile to the lowest (Q5 vs Q1) was 0.25 (95% CI 0.07–0.87; Ptrend = 0.02) for lethal cancer. Among all the cases, higher adiponectin concentrations predicted lower prostate cancer–specific mortality [hazard ratio (HR)Q5 vs Q1= 0.39; 95% CI 0.17–0.85; Ptrend = 0.02], independent of body mass index (BMI), plasma C-peptide (a marker of insulin secretion), leptin, clinical stage, and tumor grade. This inverse association was apparent mainly among men with a BMI ≥25 kg/m2 (HRQ5 vs Q1= 0.10; 95% CI 0.01–0.78; Ptrend = 0.02), but not among men of normal weight (Ptrend = 0.51). Although the correlation of leptin concentrations with BMI (r = 0.58, P < 0.001) was stronger than that of adiponectin (r = −0.17, P < 0.001), leptin was unrelated to prostate cancer risk or mortality. Conclusions: Higher prediagnostic adiponectin (but not leptin) concentrations predispose men to a lower risk of developing high-grade prostate cancer and a lower risk of subsequently dying from the cancer, suggesting a mechanistic link between obesity and poor prostate cancer outcome.

Download Full-text

456: Genetic Polymorphisms in CYP17, CYPJA4, CYP19 and SRD5A2 and Prostate Cancer Risk in African American Men: the Flint Men's Health Study

The Journal of Urology ◽

10.1016/s0022-5347(18)30709-2 ◽

2007 ◽

Vol 177 (4S) ◽

pp. 153-153

Author(s):

Aruna V. Sarma ◽

Leslie Lange ◽

Anna Ray ◽

Ethan Lange ◽

Rodney L. Dunn ◽

...

Keyword(s):

Prostate Cancer ◽

African American ◽

Cancer Risk ◽

Genetic Polymorphisms ◽

African American Men ◽

Prostate Cancer Risk ◽

Men’S Health ◽

Health Study ◽

Men's Health

Download Full-text

The Association of Nighttime Fasting Duration and Prostate Cancer Risk: Results from the Multicase-Control (MCC) Study in Spain

Nutrients ◽

10.3390/nu13082662 ◽

2021 ◽

Vol 13 (8) ◽

pp. 2662

Author(s):

Anna Palomar-Cros ◽

Ana Espinosa ◽

Kurt Straif ◽

Beatriz Pérez-Gómez ◽

Kyriaki Papantoniou ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Risk ◽

Lower Risk ◽

Night Shift ◽

Prostate Cancer Risk ◽

Meal Timing ◽

Risk Of Cancer ◽

Fasting Duration ◽

Population Controls ◽

Reduced Risk

Nighttime fasting has been inconclusively associated with a reduced risk of cancer. The purpose of this study was to investigate this association in relation to prostate cancer risk. We examined data from 607 prostate cancer cases and 848 population controls who had never worked in night shift work from the Spanish multicase-control (MCC) study, 2008–2013. Through an interview, we collected circadian information on meal timing at mid-age. We estimated odds ratios (OR) and 95% confidence intervals (CI) with unconditional logistic regression. After controlling for time of breakfast, fasting for more than 11 h overnight (the median duration among controls) was associated with a reduced risk of prostate cancer compared to those fasting for 11 h or less (OR = 0.77, 95% 0.54–1.07). Combining a long nighttime fasting and an early breakfast was associated with a lower risk of prostate cancer compared to a short nighttime fasting and a late breakfast (OR = 0.54, 95% CI 0.27–1.04). This study suggests that a prolonged nighttime fasting duration and an early breakfast may be associated with a lower risk of prostate cancer. Findings should be interpreted cautiously and add to growing evidence on the importance of chrononutrition in relation to cancer risk.

Download Full-text

Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools

BMC Medical Research Methodology ◽

10.1186/s12874-019-0839-0 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Johanna Tolksdorf ◽

Michael W. Kattan ◽

Stephen A. Boorjian ◽

Stephen J. Freedland ◽

Karim Saba ◽

...

Keyword(s):

Prostate Cancer ◽

Risk Factors ◽

Family History ◽

Cancer Risk ◽

Risk Prediction ◽

Prostate Biopsy ◽

Prostate Cancer Risk ◽

High Grade ◽

Prediction Tools ◽

History Of

Abstract Background Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for building such tools with application to the Prostate Biopsy Collaborative Group prostate cancer risk prediction tool. Methods We created models for high-grade prostate cancer risk using six established risk factors. The data comprised 8492 prostate biopsies collected from ten institutions, 2 in Europe and 8 across North America. We calculated area under the receiver operating characteristic curve (AUC) for discrimination, the Hosmer-Lemeshow test statistic (HLS) for calibration and the clinical net benefit at risk threshold 15%. We implemented several internal cross-validation schemes to assess the influence of modeling method and individual cohort on validation performance. Results High-grade disease prevalence ranged from 18% in Zurich (1863 biopsies) to 39% in UT Health San Antonio (899 biopsies). Visualization revealed outliers in terms of risk factors, including San Juan VA (51% abnormal digital rectal exam), Durham VA (63% African American), and Zurich (2.8% family history). Exclusion of any cohort did not significantly affect the AUC or HLS, nor did the choice of prediction model (pooled, random-effects, meta-analysis). Excluding the lowest-prevalence Zurich cohort from training sets did not statistically significantly change the validation metrics for any of the individual cohorts, except for Sunnybrook, where the effect on the AUC was minimal. Therefore the final multivariable logistic model was built by pooling the data from all cohorts using logistic regression. Higher prostate-specific antigen and age, abnormal digital rectal exam, African ancestry and a family history of prostate cancer increased risk of high-grade prostate cancer, while a history of a prior negative prostate biopsy decreased risk (all p-values < 0.004). Conclusions We have outlined a multi-cohort model-building internal validation strategy for developing globally accessible and scalable risk prediction tools.

Download Full-text