Tianyi Huang, Jing Chen, Lu Zhang, Rui Wang, Yiheng Liu, Cuihua Lu
{"title":"Diagnostic performance of microRNAs for predicting response to transarterial chemoembolization in hepatocellular carcinoma: a meta-analysis.","authors":"Tianyi Huang, Jing Chen, Lu Zhang, Rui Wang, Yiheng Liu, Cuihua Lu","doi":"10.3389/fonc.2024.1483196","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To provide a detailed pooled analysis of the diagnostic accuracy of microRNAs (miRNAs) in predicting the response to transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC).</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across PubMed, Embase, Cochrane Library, and Web of Science to identify studies assessing the diagnostic performance of miRNAs in predicting TACE response in HCC. Two independent reviewers performed quality assessment and data extraction using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression were performed to explore potential sources of heterogeneity, including sample size, response criteria, specimen source, response evaluation methods, TACE efficacy interval window, and geographical location.</p><p><strong>Results: </strong>Seven studies, comprising 320 HCC responders and 187 non-responders, were included in this meta-analysis. The miRNAs studied included miR-373, miR-210, miR-4492, miR-1271, miR-214, miR-133b, and miR-335. The pooled sensitivity of miRNAs in predicting recurrence after TACE was 0.79 [95% CI: 0.72-0.84], and the pooled specificity was 0.82 [95% CI: 0.74-0.88]. The DOR was 17 [95% CI: 9-33], and the pooled area under the SROC curve (AUC) was 0.85 [95% CI: 0.81-0.88], indicating excellent diagnostic accuracy. Subgroup analyses revealed significant differences in diagnostic performance based on response criteria and geographical location. Meta-regression did not identify any significant sources of interstudy heterogeneity.</p><p><strong>Conclusion: </strong>MiRNAs show promise as diagnostic tools for predicting TACE response in HCC patients. However, their clinical application requires further validation in larger cohorts. Future research should focus on standardizing RNA extraction methods, selecting consistent endogenous controls, and adopting uniform response evaluation criteria to improve reliability and reduce variability.</p>","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":"14 ","pages":"1483196"},"PeriodicalIF":3.5000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773618/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fonc.2024.1483196","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: To provide a detailed pooled analysis of the diagnostic accuracy of microRNAs (miRNAs) in predicting the response to transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC).
Methods: A comprehensive literature search was conducted across PubMed, Embase, Cochrane Library, and Web of Science to identify studies assessing the diagnostic performance of miRNAs in predicting TACE response in HCC. Two independent reviewers performed quality assessment and data extraction using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression were performed to explore potential sources of heterogeneity, including sample size, response criteria, specimen source, response evaluation methods, TACE efficacy interval window, and geographical location.
Results: Seven studies, comprising 320 HCC responders and 187 non-responders, were included in this meta-analysis. The miRNAs studied included miR-373, miR-210, miR-4492, miR-1271, miR-214, miR-133b, and miR-335. The pooled sensitivity of miRNAs in predicting recurrence after TACE was 0.79 [95% CI: 0.72-0.84], and the pooled specificity was 0.82 [95% CI: 0.74-0.88]. The DOR was 17 [95% CI: 9-33], and the pooled area under the SROC curve (AUC) was 0.85 [95% CI: 0.81-0.88], indicating excellent diagnostic accuracy. Subgroup analyses revealed significant differences in diagnostic performance based on response criteria and geographical location. Meta-regression did not identify any significant sources of interstudy heterogeneity.
Conclusion: MiRNAs show promise as diagnostic tools for predicting TACE response in HCC patients. However, their clinical application requires further validation in larger cohorts. Future research should focus on standardizing RNA extraction methods, selecting consistent endogenous controls, and adopting uniform response evaluation criteria to improve reliability and reduce variability.
期刊介绍:
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.