Literature DB >> 35645149

Diagnostic performance of clusterin in hepatocellular carcinoma: A meta-analysis.

Ge Gao1, Xuke Luan2.   

Abstract

INTRODUCTION: Clusterin (CLU) is a pleiotropic protein with numerous functions. It has recently attracted considerable attention owing to its association with cancer progression and metastasis. However, its role in hepatocellular carcinoma (HCC) has not been investigated. This meta-analysis is the first evaluation of the diagnostic performance of CLU in HCC.
METHODS: Articles published in PubMed, EMBASE, Web of Science, Wanfang Data Knowledge Service Platform, and China Science and Technology Journal Database until January 2022 were searched. Studies that reported the usefulness of CLU for the differentiation of HCC and non-HCC (e.g., liver cirrhosis, chronic hepatitis, and other benign liver disease) patients were selected. Alpha-fetoprotein (AFP) was used as a positive control in this study. The sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were compared between CLU and AFP.
RESULTS: Eight articles including 811 participants were included. The pooled sensitivity (95% confidence interval (CI)), specificity (95% CI), DOR (95% CI), and AUC (95% CI) were: 0.86 (0.78-0.91), 0.85 (0.75-0.91), 35 (13-94), and 0.92 (0.89-0.94) for CLU; 0.74 (0.67-0.81), 0.89 (0.79-0.94), 22 (8-61), and 0.87 (0.84-0.90) for AFP; 0.93 (0.88-0.96), 0.85 (0.68-0.94), 75 (21-262), and 0.95 (0.92-0.96) for CLU + AFP, respectively. Compared with AFP, CLU showed higher sensitivity, DOR, and AUC, as well as similar specificity. The combination of CLU and AFP resulted in higher sensitivity, DOR, and AUC.
CONCLUSIONS: Serum CLU is a better biomarker versus AFP for the diagnosis of HCC. The combination of CLU and AFP improved diagnostic performance.

Entities:  

Keywords:  clusterin; diagnosis; hepatocellular carcinoma; meta-analysis; tumor marker

Year:  2022        PMID: 35645149     DOI: 10.1177/03936155221101206

Source DB:  PubMed          Journal:  Int J Biol Markers        ISSN: 0393-6155            Impact factor:   2.659


  1 in total

1.  Construction of a Colorectal Cancer Prognostic Risk Model and Screening of Prognostic Risk Genes Using Machine-Learning Algorithms.

Authors:  Xuezhi Du; Han Qi; Wenbin Ji; Peiyuan Li; Run Hua; Wenliang Hu; Feng Qi
Journal:  Comput Math Methods Med       Date:  2022-10-11       Impact factor: 2.809

  1 in total

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