Background: In recent years, triglyceride-glucose index (TyG) was a new indicator of insulin resistance, and it has been widely reported that it may be associated with serum prostate-specific antigen (PSA) concentrations.
Aims: We intended to investigate the possible connection between serum PSA concentration and the TyG index.
Methods: This is a cross-sectional study of adults with complete data on TyG and serum PSA concentrations (ng/ml) from the NHANES, 2003-2010. The TyG index is obtained by the formula below: TyG = Ln [triglycerides (mg/dL) × fasting glucose(mg/dL)/2]. Multivariate regression analysis and subgroup analysis were used to examine the connection between the TyG index and serum PSA levels.
Results: Multiple regression analysis of the weighted linear model showed that individuals with a higher TyG index had lower PSA levels. Subgroup analyses and interaction tests showed no apparent dependence on age, race/ethnicity, BMI, household income ratio, education level, and marital status on this negative association (all interactions p > 0.05).
Conclusions: TyG index is related to lower serum PSA concentrations in adult men from the USA. Further comprehensive prospective studies are needed to confirm our findings.
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http://dx.doi.org/10.1007/s11845-023-03431-5 | DOI Listing |
Prostate Int
September 2024
Erciyes University, Department of Urology, Devision of UroOncology, Kayseri, Turkey.
Background: It has been more than a decade since fusion prostate biopsy (FPB) has been used in the diagnosis of prostate cancer (PCa). Therefore, patients with a previous history of negative FPB and ongoing suspicion of PCa are beginning to emerge. This study investigated whether the first biopsy type (standard or fusion) should be effective in deciding on a second biopsy.
View Article and Find Full Text PDFRMD Open
January 2025
Department of Rheumatology, UZ Leuven, Leuven, Belgium.
Objectives: To investigate serum lipid profile in early, treatment-naïve psoriatic arthritis (PsA) and to determine whether changes in classical lipids or apolipoproteins are specific to PsA.
Methods: Total cholesterol, non-high-density lipoprotein cholesterol (non-HDL-c), low-density lipoprotein cholesterol (LDL-c), HDL-c, triglycerides, apolipoprotein B (ApoB) and apolipoprotein A1 (ApoA1) were compared in newly diagnosed untreated PsA patients (n=75) to sex- and age-matched controls (healthy control (HC)) (n=61) and early untreated rheumatoid arthritis (RA) patients (n=50).
Results: Among classical lipid measurements, HDL-c levels were lower in PsA than in HC and RA (df 2, χ10, p=0.
Ther Adv Musculoskelet Dis
January 2025
The First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1 Iseigaoka, Yahata-nishi, Kitakyushu 807-8555, Japan.
Int Urol Nephrol
January 2025
Department of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.
Objective: A prostate ultrasound (US) imaging omics model was established to assess its effectiveness in diagnosing prostate cancer (PCa), predicting Gleason score (GS), and determining the likelihood of distant metastasis.
Methods: US images of patients with prostate pathology confirmed by biopsy or surgery at our hospital were retrospectively analyzed. Regions of interest (ROI) segmentation, feature extraction, feature screening, and the construction and training of the radiomics model were performed.
Cancers (Basel)
December 2024
Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA.
: Prostate cancer treatment has been revolutionized by targeted therapies, including PARP inhibitors, checkpoint immunotherapies, and PSMA-targeted radiotherapies. Despite such advancements, accurate patient stratification remains a challenge, with current methods relying on genomic markers, tissue staining, and imaging. Extracellular vesicle (EV)-derived proteins offer a novel non-invasive alternative for biomarker discovery, holding promise for improving treatment precision.
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