Huang Xiaotong, Wang Ziwei, Zhang Meiqin, Luo Hong
Department of Ultrasound, West China Second University Hospital, Sichuan University, Chengdu, China.
Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Chengdu, China.
Front Oncol. 2021 Jun 17;11:684257. doi: 10.3389/fonc.2021.684257. eCollection 2021.
To evaluate the diagnostic accuracy of the ADNEX model for ovarian cancer at the 15% cut-off value.
Studies on the identified diagnosis of the ADNEX model for ovarian cancer published in PubMed, Embase, the Cochrane Library and Web of Science databases from January 1st, 2014 to February 20th, 2021 were searched. Two researchers independently screened the retrieved studies and extracted the basic features and parameter data. The quality of the eligible studies was evaluated by Quality Assessment of Diagnostic Accuracy Studies-2, and the result was summarized by Review Manager 5.3. Meta-Disc 1.4 and STATA 16.0 were used in statistical analysis. Heterogeneity of this meta-analysis was calculated. Meta-regression was performed to investigate the potential sources of heterogeneity. Sensitivity analysis and Deek's funnel plot analysis were conducted to evaluate the stability and publication bias, respectively.
280 studies were initially retrieved through the search strategy, and 10 eligible studies were ultimately included. The random-effects model was selected for data synthesis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and the area under the summary receiver operating characteristic curve were 0.92 (95% CI: 0.89-0.94), 0.82 (95% CI: 0.78-0.86), 5.2 (95% CI: 4.1-6.4), 0.10 (95% CI: 0.07-0.13), 54.0 (95% CI: 37.0-77.0) and 0.95 (95% CI: 0.91-0.95). Meta-regression based on study design, country, enrollment and blind method was not statistically significant. This meta-analysis was stable with no obvious publication bias.
The ADNEX model at the 15% cut-off had high diagnostic accuracy in identifying ovarian cancer.
评估ADNEX模型在15%截断值时对卵巢癌的诊断准确性。
检索2014年1月1日至2021年2月20日在PubMed、Embase、Cochrane图书馆和Web of Science数据库中发表的关于ADNEX模型对卵巢癌诊断的研究。两名研究人员独立筛选检索到的研究，并提取基本特征和参数数据。采用诊断准确性研究质量评估-2对纳入研究的质量进行评估，结果用Review Manager 5.3进行汇总。统计分析使用Meta-Disc 1.4和STATA 16.0。计算该Meta分析的异质性。进行Meta回归以探究异质性的潜在来源。分别进行敏感性分析和Deek漏斗图分析以评估稳定性和发表偏倚。
通过检索策略初步检索到280项研究，最终纳入10项符合条件的研究。选择随机效应模型进行数据合成。合并敏感度、特异度、阳性似然比、阴性似然比、诊断比值比和综合受试者工作特征曲线下面积分别为0.92（95%CI：0.89 - 0.94）、0.82（95%CI：0.78 - 0.86）、5.2（95%CI：4.1 - 6.4）、0.10（95%CI：0.07 - 0.13）、54.0（95%CI：37.0 - 77.0）和0.95（95%CI：0.91 - 0.95）。基于研究设计、国家、纳入人数和盲法进行的Meta回归无统计学意义。该Meta分析稳定，无明显发表偏倚。
ADNEX模型在15%截断值时对卵巢癌具有较高的诊断准确性。
