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SUMMARYDespite complex interactions between obesity, dyslipidemia, hyperinsulinaemia, and the reproductive axis, the impact of metabolic syndrome on human male reproductive function has not been analysed comprehensively. Complete demographic, clinical, and laboratory data from 1337 consecutive primary infertile men were analysed. Health-significant comorbidities were scored with the Charlson Comorbidity Index (categorised 0 vs. 1 vs. 2 or higher). NCEP-ATPIII criteria were used to define metabolic syndrome. Semen analysis values were assessed based on the 2010 World Health Organisation (WHO) reference criteria. Descriptive statistics and logistic regression models tested the association between semen parameters and clinical characteristics and metabolic syndrome. Metabolic syndrome was found in 128 (9.6%) of 1337 men. Patients with metabolic syndrome were older (p < 0.001) and had a greater Charlson Comorbidity Index of 1 or higher (chi-square: 15.6; p < 0.001) compared with those without metabolic syndrome. Metabolic syndrome patients had lower levels of total testosterone (p < 0.001), sex hormone-binding globulin (p = 0.004), inhibin B (p = 0.03), and anti-M€ ullerian hormone (p = 0.009), and they were hypogonadal at a higher rate (chi-square: 32.0; p < 0.001) than patients without metabolic syndrome. Conversely, the two groups did not differ significantly in further hormonal levels, semen parameters, and rate of either obstructive or non-obstructive azoospermia. At multivariate logistic regression analysis, testicular volume (OR: 0.90; p = 0.002) achieved independent predictor status for WHO pathological semen concentration; conversely, age, Charlson Comorbidity Index scores, metabolic syndrome, and inhibin B values did not. No parameters predicted normal sperm morphology and total progressive motility. Metabolic syndrome accounts for roughly 9% of men presenting for primary couple's infertility. Although metabolic syndrome patients have a lower general male health status, semen analysis values seem independent of the presence of metabolic syndrome.

Obesity is associated with an increased risk of a number of serious medical conditions, including cancer. As far as prostate cancer is concerned, obesity is associated with an increased risk of high-grade tumors, which is possibly related to lower androgen levels. Diet may also affect prostate cancer risk since countries with a higher dietary fat intake also present higher prostate cancer mortality rates. Interestingly, prostate cancer is associated with a number of metabolic alterations that may provide valuable diagnostic and therapeutic targets. This review explores the available clinical as well as biological evidence supporting the relationship between obesity, diet, alteration in metabolic pathways and prostate cancer.

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Background: Several biochemical and clinical markers have been proposed for selecting patients for active surveillance (AS). However, some of these are expensive and not easily accessible. Moreover, currently about 30% of patients on AS harbor aggressive disease. Hence, there is an urgent need for other tools to accurately identify patients with low-risk prostate cancer (PCa). Patients: We retrospectively reviewed the medical records of 260 patients who underwent radical prostatectomy and were eligible for AS according to the following criteria: clinical stage T2a or less, prostate-specific antigen level < 10 ng/mL, 2 or fewer cores involved with cancer, Gleason score (GS) ≤6 grade, and prostate-specific antigen density < 0.2 ng/mL/cc. Methods: Univariate and multivariate analyses were performed to evaluate the association of patient and tumor characteristics with reclassification, defined as upstaged (pathological stage >pT2) and upgraded (GS ≥7) disease. A base model (age, prostate-specific antigen, prostate volume, and clinical stage) was compared with models considering neutrophil to lymphocyte ratio (NLR) or platelets to lymphocyte ratio (PLR), monocyte to lymphocyte (MLR), and eosinophil to lymphocyte ratio (ELR). OR and 95% CI were calculated. Finally, a decision curve analysis was performed. Results: Univariate and multivariate analyses showed that NLR, PLR, and ELR upgrading were significantly associated with upgrading (ORs ranging from 2.13 to 4.13), but not with upstaging except for MLR in multivariate analysis, showing a protective effect. Conclusion: Our results showed that NLR, PLR, and ELR are predictors of Gleason upgrading. Therefore, these inexpensive and easily available tests might be useful in the assessment of low-risk PCa, when considering patients for AS.