Papillary thyroid carcinoma (PTC) is the most common form of thyroid cancer. Several studies have proposed serum microRNAs (miRNAs) as novel biomarkers for diagnosing PTC. In this study, we conducted a meta-analysis aiming to investigate the overall diagnostic accuracy of serum miRNAs in PTC detection. Three online databases including PubMed, EMBASE and Cochrane Library were searched up to 1 May 2021. We systematically reviewed studies evaluating the value of serum miRNAs in diagnosing PTC, and then summarized the area under receiver operating characteristics curve (AUROC), sensitivity, specificity, and diagnostic odds ratio to assess the accuracy of serum miRNAs for the discrimination between patients with PTC and patients with benign thyroid nodules and healthy controls. We included 32 studies from 6 articles. Overall, there were 463 PTC patients, 334 patients with benign thyroid nodules, and 104 healthy controls. The results showed that the summary sensitivity and specificity were 76% (95% confidence interval [CI]: 68%‒83%) and 86% (95% CI: 80%‒91%), respectively, and that the summary AUROC was 0.89 (95% CI: 0.86‒0.91), when serum miRNAs were used for discriminating between PTC patients and those with benign nodules. On the other hand, the summary sensitivity and specificity of serum miRNAs for discriminating between PTC patients and healthy controls were 82% (95% CI: 77%‒86%) and 84% (95% CI: 76%‒90%), respectively, and the summary AUROC was 0.89 (95% CI: 0.86‒0.92). We found that serum miRNAs have good diagnostic performance for the discrimination between patients with PTC and patients with benign nodules and healthy controls, and thus have considerable potential as novel minimally invasive tools for detecting PTC.

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BackgroundDiabetic peripheral neuropathy (DPN) is the most common diabetes-associated complication and imposes a significant burden to healthcare systems. Thus, early diagnosis of DPN is extremely critical for management and outcome of diabetic patients. Supersonic Shear Wave Imaging (SSI) enables the noninvasive measurement of nerve stiffness. However, previous studies on SSI in the diagnosis of DPN were limited in sample sizes and reported various results. In this meta-analysis, we aimed to obtain comprehensive evidence on the value of tibial nerve stiffness measurement by SSI in the diagnosis of DPN.MethodsA comprehensive literature search in English and Chinese electronic database was conducted for studies (published until January 25, 2022) that investigated the diagnostic performance of tibial nerve stiffness measurement by SSI for detecting DPN. Summary receiver operating characteristics (SROC) modelling was constructed to conduct the meta-analysis of diagnostic accuracy of SSI for detecting DPN.ResultsFinally, a total of 12 eligible studies with 1325 subjects were included for evaluation, and a meta-analysis was conducted to evaluate the diagnostic performance of tibial nerve stiffness measurement by SSI for detecting DPN. For tibial nerve stiffness measurement by SSI, the summary sensitivity and specificity for the diagnosis of DPN were 80% (95% confidence interval [CI]: 73%–86%) and 86% (95% CI: 82%–89%), respectively. The summary area under the ROC curve (AUROC) value of the SROC was 0.90 (95% CI: 0.87–0.92), for diagnosing DPN. A subgroup analysis of 11 SSI studies from China revealed similar diagnostic performance, with a summary sensitivity of 79% (95% CI: 72%–85%), specificity of 86% (95% CI: 82%–89%) and summary AUROC value of the SROC of 0.90 (95% CI: 0.87–0.92) for diagnosing DPN.ConclusionsOur meta-analysis suggests that a tibial nerve stiffness measurement by SSI shows good performance in diagnosing DPN and has considerable potential as a noninvasive tool for detecting DPN.