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用于附件包块分类的卵巢附件报告数据系统(O-RADS):一项系统评价和Meta分析

Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis.

作者信息

Vara Julio, Manzour Nabil, Chacón Enrique, López-Picazo Ana, Linares Marta, Pascual Maria Ángela, Guerriero Stefano, Alcázar Juan Luis

机构信息

Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.

Department of Obstetrics and Gynecology, Universitiy Hospital Puerta del Mar, 11009 Cadiz, Spain.

出版信息

Cancers (Basel). 2022 Jun 27;14(13):3151. doi: 10.3390/cancers14133151.

DOI:10.3390/cancers14133151
PMID:35804924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9264796/
Abstract

In this systematic review and meta-analysis, we aimed to assess the pooled diagnostic performance of the so-called Ovarian Adnexal Report Data System (O-RADS) for classifying adnexal masses using transvaginal ultrasound, a classification system that was introduced in 2020. We performed a search for studies reporting the use of the O-RADS system for classifying adnexal masses from January 2020 to April 2022 in several databases (Medline (PubMed), Google Scholar, Scopus, Cochrane, and Web of Science). We selected prospective and retrospective cohort studies using the O-RADS system for classifying adnexal masses with histologic diagnosis or conservative management demonstrating spontaneous resolution or persistence in cases of benign appearing masses after follow-up scan as the reference standard. We excluded studies not related to the topic under review, studies not addressing O-RADS classification, studies addressing MRI O-RADS classification, letters to the editor, commentaries, narrative reviews, consensus documents, and studies where data were not available for constructing a 2 × 2 table. The pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated. The quality of the studies was evaluated using QUADAS-2. A total of 502 citations were identified. Ultimately, 11 studies comprising 4634 masses were included. The mean prevalence of ovarian malignancy was 32%. The risk of bias was high in eight studies for the "patient selection" domain. The risk of bias was low for the "index test" and "reference test" domains for all studies. Overall, the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and DOR of the O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%-98%), 77% (95% CI = 68%-84%), 4.2 (95% CI = 2.9-6.0), 0.04 (95% CI = 0.03-0.07), and 96 (95% CI = 50-185), respectively. Heterogeneity was moderate for sensitivity and high for specificity. In conclusion, the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses.

摘要

在这项系统评价和荟萃分析中,我们旨在评估所谓的卵巢附件报告数据系统(O-RADS)在使用经阴道超声对附件包块进行分类时的综合诊断性能,该分类系统于2020年推出。我们在多个数据库(Medline(PubMed)、谷歌学术、Scopus、Cochrane和科学网)中检索了2020年1月至2022年4月期间报告使用O-RADS系统对附件包块进行分类的研究。我们选择前瞻性和回顾性队列研究,这些研究使用O-RADS系统对附件包块进行分类,并以组织学诊断或保守治疗作为参考标准,对于表现为良性的包块,通过随访扫描显示自发消退或持续存在。我们排除了与所审查主题无关的研究、未涉及O-RADS分类的研究、涉及MRI O-RADS分类的研究、给编辑的信、评论、叙述性综述、共识文件以及无法获取数据以构建2×2表格的研究。计算了合并敏感性、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。共识别出502篇引文。最终,纳入了11项研究,共4634个包块。卵巢恶性肿瘤的平均患病率为32%。八项研究在“患者选择”领域的偏倚风险较高。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,O-RADS系统对附件包块进行分类的合并估计敏感性、特异性、阳性似然比、阴性似然比和DOR分别为97%(95%置信区间(CI)=94%-98%)、77%(95%CI=68%-84%)、4.2(95%CI=2.9-6.0)、0.04(95%CI=0.03-0.07)和96(95%CI=50-185)。敏感性的异质性为中等,特异性的异质性较高。总之,O-RADS系统在对附件包块进行分类时具有良好的敏感性和中等的特异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/b725afb935b3/cancers-14-03151-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/030667419dbe/cancers-14-03151-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/7de65566ad4f/cancers-14-03151-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/ab724acb17f1/cancers-14-03151-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/95313ec85a94/cancers-14-03151-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/b725afb935b3/cancers-14-03151-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/030667419dbe/cancers-14-03151-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/7de65566ad4f/cancers-14-03151-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/ab724acb17f1/cancers-14-03151-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/95313ec85a94/cancers-14-03151-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2908/9264796/b725afb935b3/cancers-14-03151-g005.jpg

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