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妇科影像学及报告数据系统用于附件包块分类。

Gynecologic Imaging and Reporting Data System for classifying adnexal masses.

机构信息

Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, Pamplona, Spain -

Panoramic Ultrasonic Ultrasound Center, Santiago, Chile.

出版信息

Minerva Obstet Gynecol. 2023 Feb;75(1):69-79. doi: 10.23736/S2724-606X.22.05122-3.

Abstract

INTRODUCTION

To perform a systematic review and meta-analysis of the diagnostic performance of the so-called Gynecologic Imaging and Report Data System (GI-RADS) for classifying adnexal masses.

EVIDENCE ACQUISITION

A search for studies reporting about the use of GI-RADS system for classifying adnexal masses from January 2009 to December 2021 was performed in Medline (Pubmed), Google Scholar, Scopus, Cochrane, and Web of Science databases. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odd ratio (DOR) were calculated. Studies' quality was evaluated using QUADAS-2.

EVIDENCE SYNTHESIS

We identified 510 citations. Ultimately, 26 studies comprising 7350 masses were included. Mean prevalence of ovarian malignancy was 26%. The risk of bias was high in eight studies for domain "patient selection" and low for "index test," "reference test" domains for all studies. Overall, pooled estimated sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and DOR of GI-RADS system for classifying adnexal masses were 94% (95% confidence interval [CI]=91-96%), 90% (95% CI=87-92%), 9.1 (95% CI=7.0-11.9), and 0.07 (95% CI=0.05-0.11), and 132 (95% CI=78-221), respectively. Heterogeneity was high for both sensitivity and specificity. Meta-regression showed that multiple observers and study's design explained this heterogeneity among studies.

CONCLUSIONS

GI-RADS system has a good diagnostic performance for classifying adnexal masses.

摘要

简介

对所谓的妇科影像学和报告数据系统(GI-RADS)用于分类附件肿块的诊断性能进行系统评价和荟萃分析。

证据获取

在 Medline(Pubmed)、Google Scholar、Scopus、Cochrane 和 Web of Science 数据库中,对 2009 年 1 月至 2021 年 12 月期间报告使用 GI-RADS 系统分类附件肿块的研究进行了检索。计算了汇总的敏感性、特异性、阳性和阴性似然比以及诊断比值比(DOR)。使用 QUADAS-2 评估研究质量。

证据综合

我们确定了 510 条引文。最终,纳入了 26 项研究,共 7350 个肿块。卵巢恶性肿瘤的平均患病率为 26%。8 项研究在“患者选择”领域存在高偏倚风险,所有研究在“索引测试”和“参考测试”领域的偏倚风险较低。总体而言,GI-RADS 系统用于分类附件肿块的汇总估计敏感性、特异性、阳性似然比、阴性似然比和 DOR 分别为 94%(95%置信区间[CI]=91-96%)、90%(95% CI=87-92%)、9.1(95% CI=7.0-11.9)、0.07(95% CI=0.05-0.11)和 132(95% CI=78-221)。敏感性和特异性的异质性均较高。Meta 回归表明,多个观察者和研究设计解释了研究之间的这种异质性。

结论

GI-RADS 系统对分类附件肿块具有良好的诊断性能。

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