Moreira, Daniel M.

ObjectiveTo determine if cholesterol is a risk factor for the development of lower urinary tract symptoms in asymptomatic men.MethodsA post‐hoc analysis of the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) study was carried out in 2323 men with baseline International Prostate Symptom Score <8 and not taking benign prostatic hyperplasia or cholesterol medications. Cox proportion models were used to test the association between cholesterol, high‐density lipoprotein, low‐density lipoprotein and the cholesterol : high‐density lipoprotein ratio with incident lower urinary tract symptoms, defined as first report of medical treatment, surgery or two reports of an International Prostate Symptom Score >14.ResultsA total of 253 men (10.9%) developed incident lower urinary tract symptoms. On crude analysis, higher high‐density lipoprotein was associated with a decreased lower urinary tract symptoms risk (hazard ratio 0.89, P = 0.024), whereas total cholesterol and low‐density lipoprotein showed no association. After multivariable adjustment, the association between high‐density lipoprotein and incident lower urinary tract symptoms remained significant (hazard ratio 0.89, P = 0.044), whereas no association was observed for low‐density lipoprotein (P = 0.611). There was a trend for higher cholesterol to be linked with higher lower urinary tract symptoms risk, though this was not statistically significant (hazard ratio 1.04, P = 0.054). A higher cholesterol : high‐density lipoprotein ratio was associated with increased lower urinary tract symptoms risk on crude (hazard ratio 1.11, P = 0.016) and adjusted models (hazard ratio 1.12, P = 0.012).ConclusionsAmong asymptomatic men participating in the REDUCE study, higher cholesterol was associated with increased incident lower urinary tract symptoms risk, though the association was not significant. A higher cholesterol : high‐density lipoprotein ratio was associated with increased incident lower urinary tract symptoms, whereas higher high‐density lipoprotein was protective. These findings suggest dyslipidemia might play a role in lower urinary tract symptoms progression.

Objectives To evaluate the ability of clinical and radiographic features to predict lymph node (pN1) disease among patients with renal cell carcinoma undergoing radical nephrectomy (RN), and to develop a preoperative risk prediction model. Patients and Methods In all, 220 patients with preoperative computed tomography scans available for review underwent RN with lymph node dissection (LND) from 2000 to 2010. Radiographic features were assessed by one genitourinary radiologist blinded to pN status. Associations of features with pN1 disease were evaluated using logistic regression to develop predictive models. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results The median (interquartile range) lymph node yield was 10 (5–18). In all, 55 patients (25%) had pN1 disease at RN. On univariable analysis, the maximum lymph node (LN) short axis diameter [odds ratio (OR) 1.17; P < 0.001] predicted pN1 disease with an AUC of 0.84. Although several clinical and radiographic features were associated with pN1 disease, only two were retained in the multivariable model: maximum LN short axis diameter (OR 1.19; P <0.001) and radiographic perinephric/sinus fat invasion (OR 44.64; P = 0.01), with an AUC of 0.85. On decision curve analysis, the single variable and multivariable models showed similar net benefit. Conclusion Two radiographic features, maximum LN short axis diameter and perinephric/sinus fat invasion, outperformed traditional clinical variables in predicting pN1 disease. Maximum LN short axis diameter alone showed excellent predictive performance, and, if validated externally, would provide for a simple model to guide patient selection for LND.

Objectives To test the external validity of a previously developed risk table, designed to predict the probability of a positive bone scan among men with non‐metastatic (M0) castration‐resistant prostate cancer ( CRPC ), in a separate cohort. Patients and Methods We retrospectively analysed 429 bone scans of 281 patients with CRPC , with no known previous metastases, treated at three Veterans Affairs Medical Centers. We assessed the predictors of a positive scan using generalized estimating equations. Area under the curve ( AUC ), calibration plots and decision‐curve analysis were used to assess the performance of our previous model to predict a positive scan in the current data. Results A total of 113 scans (26%) were positive. On multivariable analysis, the only significant predictors of a positive scan were log‐transformed prostate‐specific antigen ( PSA ): hazard ratio ( HR ) 2.13; 95% confidence interval ( CI ) 1.71–2.66 ( P < 0.001) and log‐transformed PSA doubling time ( PSADT ): HR 0.53; 95% CI 0.41–0.68 ( P < 0.001). Among men with a PSA level <5 ng/ mL , the rate of positive scans was 5%. The previously developed risk table had an AUC of 0.735 to predict positive bone scan with excellent calibration, and provided additional net benefit in the decision‐curve analysis. Conclusion We have validated our previously developed table to predict the risk of a positive bone scan among men with M0/Mx CRPC . Use of this risk table may allow better tailoring of patients' scanning to identify metastases early, while minimizing over‐imaging. Regardless of PSADT , positive bone scans were rare in men with a PSA <5 ng/ mL .

Abstract The role of metformin in prostate cancer chemoprevention remains unclear. REDUCE, which followed biopsy-negative men with protocol-dictated PSA-independent biopsies at 2- and 4-years, provides an opportunity to evaluate the link between metformin use and prostate cancer diagnosis with minimal confounding from screening biases. In diabetic men from REDUCE, we tested the association between metformin use, use of other antidiabetic medications, versus no antidiabetic medication use, and prostate cancer diagnosis as well as prostate cancer grade (low-grade Gleason 4–6 and high-grade Gleason 7–10) using logistic regression. Of the 540 diabetic men with complete data, 205 (38%) did not report use of any antidiabetic medications, 141 (26%) reported use of at least one antidiabetic medication other than metformin, and 194 (36%) reported use of metformin. During the 4-year study, 122 men (23%) were diagnosed with prostate cancer. After adjusting for various clinical and demographic characteristics, we found that metformin use was not significantly associated with total (OR, 1.19; P = 0.50), low- (OR, 1.01; P = 0.96), or high-grade (OR, 1.83; P = 0.19) prostate cancer diagnosis. Likewise, there was no significant association between the use of non-metformin antidiabetic medications and prostate cancer risk in both crude (OR, 1.02; P = 0.95) and multivariable analysis (OR, 0.85; P = 0.56). Furthermore, the interactions between antidiabetic medication use and BMI, geographic location, coronary artery disease, smoking, and treatment group were not significant (all P &gt; 0.05). Among diabetic men with a negative prestudy biopsy who all underwent biopsies largely independent of PSA, metformin use was not associated with reduced risk of prostate cancer diagnosis. Cancer Prev Res; 8(11); 1055–60. ©2015 AACR.