In this study, we performed a comprehensive estimation and assessment for the clinical value of prostate health index (PHI) in diagnosing prostate cancer. Using the bivariate mixed-effect model, we calculated the following parameters and their 95% confidence internals (CIs), including sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and symmetric receiver operator characteristic. Twenty eligible studies with a total number of 5543 subjects were included in the final analysis. The estimated sensitivity was 0.75 (95% CI: 0.70-0.79) and the specificity was 0.69 (95% CI: 0.58-0.83). The pooled area under the curve was 0.78 (95% CI: 0.74-0.81). The combined positive likelihood ratio was 2.45 (95% CI: 2.19-2.73) and the negative likelihood ratio was 0.36 (95% CI: 0.31-0.43). The diagnostic odds ratio was 6.73 (95% CI: 5.38-8.44). The posttest probability was 40% under the present positive likelihood ratio of 2.45. It seems there was no significant difference between Asian population and Caucasian population population in sensitivity and specificity. But the overlap of AUC 95% CI indicated that the diagnostic accuracy of PHI was slightly higher in the Asian population population setting than that in the Caucasian population population population (0.83 vs 0.76). Similarly, there was also overlap in AUC 95% CI, which suggested that sample size may be one of heterogeneity source. The PHI has a moderate diagnostic accuracy for detecting prostate cancer. The discrimination ability of PHI is slightly prior to free/total prostate-specific antigen. It seems that ethnicity has an influence on the clinical value of PHI in the diagnostic of prostate cancer.
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http://dx.doi.org/10.1002/cam4.2376 | DOI Listing |
Eur J Psychotraumatol
December 2025
Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
: Individuals impacted by adverse childhood experiences (ACEs) are at greater risk of developing obesity, however, few studies have prospectively measured ACEs and obesity during childhood. Associations with the adoption of obesogenic behaviours during childhood, which directly contribute to obesity are also understudied.: To examine associations between individual and cumulative ACEs, obesity, and obesogenic behaviours during childhood.
View Article and Find Full Text PDFDespite an increasing number of studies examining the effect of Single-Photon Emission Computed Tomography/ Computed Tomography (SPECT/CT) on improvement of diagnosis of aseptic loosening, there is still a great deal of uncertainty regarding its applicability in diagnostic algorithm. Therefore, in this meta-analysis, we aimed to investigate the diagnostic performance of SPECT/CT for identification of aseptic loosening in patients with persistent pain following the total knee arthroplasty (TKA) and total hip arthroplasty (THA). Electronic databases including Medline, Scopus, Web of Science, Cochrane library, and Embase were systematically searched for identifying relevant published studies from their inception to April 2023.
View Article and Find Full Text PDFOphthalmol Sci
November 2024
A2-Ai, Ann Arbor, Michigan.
Objective: To develop a population pharmacokinetic (PK) model to characterize serum pegcetacoplan concentration-time data after intravitreal administration in patients with geographic atrophy (GA) or neovascular age-related macular degeneration (nAMD).
Design: Pharmacokinetic modeling.
Participants: Two hundred sixty-one patients with GA or nAMD enrolled in 4 clinical studies of pegcetacoplan.
Front Cardiovasc Med
January 2025
Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, China.
Background: Depression is being increasingly acknowledged as an important risk factor contributing to coronary heart disease (CHD). Currently, there is no predictive model specifically designed to evaluate the risk of coronary heart disease among individuals with depression. We aim to develop a machine learning (ML) model that will analyze risk factors and forecast the probability of coronary heart disease in individuals suffering from depression.
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