Pathology Department of the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Ultrasound Department of the First Affiliated Hospital of Dalian Medical University, Dalian, China.
PLoS One. 2022 Aug 5;17(8):e0272149. doi: 10.1371/journal.pone.0272149. eCollection 2022.
In this meta-analysis study, the main objective was to determine the accuracy of S-detect in effectively distinguishing malignant thyroid nodules from benign thyroid nodules.
We searched the PubMed, Cochrane Library, and CBM databases from inception to August 1, 2021. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 softwares. We calculated summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR+/LR-), diagnostic odds ratio(DOR), and receiver operating characteristic (SROC) curves. Cochran's Q-statistic and I2 test were used to evaluate potential heterogeneity between studies. A sensitivity analysis was performed to evaluate the influence of single studies on the overall estimate. We also performed meta-regression analyses to investigate the potential sources of heterogeneity.
In this study, a total of 17 studies meeting the requirements of the standard were used. The number of benign and malignant nodules analyzed and evaluated in this paper was 1595 and 1118 respectively. This paper mainly completes the required histological confirmation through s-detect. The pooled Sen and pooled Spe were 0.87 and 0.74, respectively, (95%CI = 0.84-0.89) and (95%CI = 0.66-0.81). Furthermore, the pooled LR+ and negative LR- were determined to be 3.37 (95%CI = 2.53-4.50) and 0.18 (95%CI = 0.15-0.21), respectively. The experimental results showed that the pooled DOR of thyroid nodules was 18.83 (95% CI = 13.21-26.84). In addition, area under SROC curve was determined to be 0.89 (SE = 0.0124). It should be pointed out that there is no evidence of bias (i.e. t = 0.25, P = 0.80).
Through this meta-analysis, it can be seen that the accuracy of s-detect is relatively high for the effective distinction between malignant thyroid nodules and benign thyroid nodules.
在这项荟萃分析研究中,主要目的是确定 S-detect 在有效区分恶性甲状腺结节与良性甲状腺结节方面的准确性。
我们检索了 PubMed、Cochrane 图书馆和 CBM 数据库,检索时间截至 2021 年 8 月 1 日。使用 STATA 版本 14.0 和 Meta-Disc 版本 1.4 软件进行荟萃分析。我们计算了敏感性(Sen)、特异性(Spe)、阳性和阴性似然比(LR+/LR-)、诊断比值比(DOR)和受试者工作特征(SROC)曲线的汇总统计数据。使用 Cochran's Q 统计量和 I2 检验评估研究间潜在的异质性。进行敏感性分析以评估单个研究对总体估计的影响。我们还进行了荟萃回归分析,以探讨异质性的潜在来源。
本研究共纳入 17 项符合标准的研究。本文分析和评估的良性和恶性结节数量分别为 1595 个和 1118 个。本文主要通过 S-detect 完成所需的组织学确认。汇总的 Sen 和 Spe 分别为 0.87 和 0.74,(95%CI = 0.84-0.89)和(95%CI = 0.66-0.81)。此外,汇总的 LR+和负 LR-分别为 3.37(95%CI = 2.53-4.50)和 0.18(95%CI = 0.15-0.21)。实验结果表明,甲状腺结节的汇总 DOR 为 18.83(95%CI = 13.21-26.84)。此外,SROC 曲线下面积为 0.89(SE = 0.0124)。需要指出的是,没有偏倚的证据(即 t = 0.25,P = 0.80)。
通过这项荟萃分析,可以看出 S-detect 在有效区分恶性甲状腺结节与良性甲状腺结节方面的准确性相对较高。