A body shape index (ABSI) but not body mass index (BMI) is associated with prostate cancer-specific mortality: Evidence from the US NHANES database.

BACKGROUND: Prostate cancer (PCa) is a common malignancy in males and obesity may play a role in its development and progression. Associations between visceral obesity measured by a body shape index (ABSI) and PCa mortality have not been thoroughly investigated. This study assessed the associations between ABSI, body mass index (BMI), and long-term PCa-specific mortality using a nationally representative US database. METHODS: This population-based longitudinal study collected data of males aged ≥40 years diagnosed with PCa and who underwent surgery and/or radiation from the National Health and Nutrition Examination Survey database 2001-2010. All included participants were followed through the end of 2019 using the National Center for Health Statistics Linked Mortality File. Associations between PCa-specific mortality, BMI, and ABSI were determined using Cox proportional hazards regression and receiver operating characteristic (ROC) curve analysis. RESULTS: Data of 294 men (representing 1,393,857 US nationals) were analyzed. After adjusting for confounders, no significant associations were found between BMI (adjusted hazard ratio [aHR] = 1.06, 95% confidence interval [CI]: 0.97-1.16, p = 0.222), continuous ABSI (aHR = 1.29, 95% CI: 0.83-2.02, p = 0.253), or ABSI in category (Q4 vs. Q1-Q3: aHR = 1.52, 95% CI: 0.72-3.24, p = 0.265), and greater risk of PCa-specific mortality. However, among participants who had been diagnosed within 4 years, the highest ABSI quartile but not in BMI was significantly associated with greater risk for PCa-specific mortality (Q4 vs. Q1-Q3: aHR = 5.34, 95% CI: 2.26-12.62, p = 0.001). In ROC analysis for this subgroup, the area under the curve of ABSI alone for predicting PCa-specific mortality was 0.638 (95% CI: 0.448-0.828), reaching 0.729 (95% CI: 0.490-0.968 when combined with other covariates. CONCLUSIONS: In US males with PCa diagnosed within 4 years, high ABSI but not BMI is independently associated with increased PCa-specific mortality.

Validating the use of contrast-induced nephropathy prediction models in endovascular aneurysm repairs.

BACKGROUND: Existing risk prediction models for contrast-induced nephropathy (CIN) are based on studies for percutaneous coronary interventions, with none validated for use in vascular procedures. We aim to validate existing CIN prediction models in patients who underwent aortic endovascular aneurysm repair (EVAR). METHODS: A retrospective review of 216 patients who underwent EVAR between January 2008 and December 2015 was undertaken. Incidence of acute kidney injuries at 24, 48, and 72 hours and at follow-up were evaluated. Of 12 CIN prediction models within the literature, 8 were suitable for validation in patients who underwent EVAR and validation was performed with C-statistics. RESULTS: There were 216 EVARs performed within the study period. The mean patients age was 73 years and 162 (75%) were performed in an elective setting. Percentage of preoperative chronic kidney disease stages 1 to 5 were 16%, 42%, 31%, 6%, and 5%, respectively. The mean intraprocedure contrast volume used was 280 mL. Incidence of acute kidney injuries at 24, 48, and 72 hours and at follow-up were 8%, 12%, 11%, and 6%, respectively. Three percent of patients became dialysis dependent. Validation of the eight existing CIN predication models reveal area under curve C-statistics between 0.61 and 0.75 (P = .026 to P < .001). Five of the 8 had good discriminative ability (C-statistics of >0.70) and the CIN prediction models by Mehran and Tziakas had the highest C-statistics at 0.75 (P < .001). CONCLUSIONS: In our study population, 8 of 12 CIN prediction models within the literature were validated for use in patients undergoing EVAR and five are useful in identifying patients at risk for CIN.