Association of lower urinary tract symptoms and geriatric nutritional risk index in men: a cross-sectional study based on NHANES.

Background: Despite previous literature exploring the factors influencing lower urinary tract symptoms (LUTS), few studies have examined the relationship between nutritional status and LUTS. Objectives: The objective of this research was to evaluate the relationship between LUTS and Geriatric Nutritional Risk Index (GNRI) in middle-aged and older men. Methods: We included 2,607 men in the NHANES 2005-2006 and 2007-2008 cycles for cross-sectional analysis. We screened for LUTS based on four specific questions on the relevant questionnaire. We calculated GNRI according to the relevant calculation formula and included other covariates. Multivariate logistic analysis using GNRI as the principal independent variable and adjusting for other covariates were used to determine the association with LUTS, nocturia, and daytime LUTS. Results: According to the responses to the questionnaire, out of 2,607 eligible participants, 471 had LUTS, 906 had nocturia, and 819 had daytime LUTS. In the unadjusted regression model, LUTS (OR = 0.93, 95% CI = 0.91-0.96, p < 0.001), nocturia (OR = 0.90, 95% CI = 0.88-0.93, p < 0.001), and daytime LUTS (OR = 0.96, 95% CI = 0.94-0.99, p = 0.002) were significantly negatively associated with GNRI. After adjustment by adding covariates, LUTS (OR = 0.97,95% CI =0.94-0.99, p = 0.026) and nocturia (OR = 0.94, 95% CI =0.91-0.93, p < 0.001) were significantly negatively associated with GNRI. Conclusion: Low GNRI was associated with the development of LUTS. In the prevention and treatment of LUTS, urologists should consider the impact of nutritional status on LUTS, and interventions for nutritional status may prevent and improve LUTS.

Cognitive fusion-targeted biopsy versus transrectal ultrasonography-guided systematic biopsy: comparison and analysis of the risk of Gleason score upgrading.

PURPOSE: The aim of this study is to assess the precision of the Gleason score (GS) obtained through cognitive fusion-targeted biopsy (COG-TB) in comparison to transrectal ultrasonography-guided systematic biopsy (TRUS-SB), and to identify factors that can predict Gleason score upgrading (GSU) in a cohort of Chinese patients. METHODS: A final enrollment of 245 patients was recorded. Between 2020 and 2022, 132 patients underwent TRUS-SB, and 113 patients underwent COG-TB. The Chi-square test was performed to analyze the variation in downgrading, concordance, and upgrading between TRUS-SB and COG-TB. Multivariable analyses were performed to seek factors predicting Gleason score upgrading. Finally, a model which utilizes multivariable logistic regression was developed to predict the likelihood of GSU. RESULTS: The concordance for TRUS-SB and COG-TB were 42.4% and 65.5%, respectively. TRUS-SB and COG-TB exhibited notable disparities in downgrading, concordance, and upgrading. Age, prostate volume, body mass index (BMI), and the biopsy modality were significant predictive factors. CONCLUSION: COG-TB can significantly increase concordance with final histopathology. Age, prostate volume, BMI, and the biopsy modality were predictive factors of GSU.

Comparing histology between prostate cognitive fusion targeted biopsy and radical prostatectomy: exploring risk factors of Gleason score upgrading in Chinese patients.

PURPOSE: To explore and identify the relevant clinical and pathological predictors leading to biopsy Gleason score upgrading (GSU) in cognitive fusion targeted biopsy (COG-TB) in Chinese patients. METHODS: Clinical and pathological information of 496 patients who underwent COG-TB and radical prostatectomy (RP) in our hospital from January 2020 to September 2023 were retrospectively compiled and analyzed. In this study, we screened valuable predictors through univariable and multivariable logistic regression analyses and then constructed predictive models. We draw nomograms to visualize the predictive models. In addition, the discriminatory power of the model was assessed using receiver operating characteristic (ROC) curves. Finally, calibration curves and decision curve analysis (DCA) were used to evaluate the predictive power of the model and the net benefits it could deliver. RESULTS: Out of the 496 patients eligible for the study, 279 had a consistent Gleason score (GS) on biopsy and postoperative GS, 191 experienced GSU, and 26 experienced downgrading. Significant associations for GSU were identified for five risk factors through multivariable logistic regression analyses, which included age, prostate volume, BMI, tumor percentage in biopsy tissue, and tumor location. Our model had excellent discriminatory power through ROC analysis. Calibration curves and DCA showed that our model was well calibrated and provided certain benefits for patient treatment decisions. CONCLUSION: Age, prostate volume, BMI, tumor percentage in biopsy tissue, and tumor location are risk indicators for predicting GSU in COG-TB. Our prediction model is more suitable for Chinese patients and can assist in accurately evaluating biopsy GS and developing effective treatment plans.