Objective: To investigate the diagnostic performance of the ADNEX model in the International Ovarian Tumor Analysis diagnostic models for ovarian tumors and further explore its application value in the staging of ovarian tumors.
Methods: A total of 224 patients who underwent ultrasound for evaluation of adnexal masses and were treated surgically owing to adnexal masses from January 2018 to June 2020 in our hospital were selected for research on the diagnostic accuracy of the ADNEX model. The clinical information and ultrasonographic findings of the patients were collected, and the pathological diagnosis was taken as the gold standard. According to the ADNEX model, the ovarian tumors were divided into five subtypes: benign and borderline, stage I, stage II–IV, and metastatic cancer. The sensitivity, specificity, positive predictive value, negative predictive value, diagnostic odds ratio, and area under the receiver operating characteristics curve (AUC) of the ADNEX model were calculated.
Results: Of the 224 patients, 119 (53.1%) developed benign tumors and 105 (46.9%) had malignant tumors. When the cut-off value for malignancy risk was 10%, the ADNEX model including CA 125 achieved a sensitivity of 94.3% (95% CI: 88.0– 97.9%), specificity of 74.0% (95% CI: 65.1– 81.6%), positive predictive value of 76.2% (95% CI: 70.2– 81.3%), negative predictive value of 93.6% (95% CI: 87.0– 97.0%), diagnostic odds ratio of 45.25, and an AUC of 0.94 (95% CI: 0.90– 0.97) for differentiating between benign and malignant ovarian tumors. The AUC in the model excluding CA 125 was 0.93 (95% CI: 0.89– 0.96), but the difference was not statistically significant (P=0.20). The accuracy of the ADNEX model for the diagnosis of ovarian tumors of all subtypes exceeds 80% when CA 125 measurements were included in the application, but the sensitivity for diagnosing borderline, stage I, and metastatic ovarian tumors was only 60.0% (95% CI:36.1– 80.9%), 28.6% (95% CI:8.4– 58.1%) and 45.5% (95% CI:16.7– 76.6%).
Conclusion: The ADNEX model shows good diagnostic performance in differentiating between benign and malignant ovarian tumors. The model has a certain clinical value in the diagnosis of all subtypes of ovarian tumors, but the sensitivity is unsatisfactory for the diagnosis of borderline, stage I, and metastatic ovarian tumors and needs to be verified.

Keywords: IOTA, ADNEX model, ovarian tumors, ultrasound


中文翻译：

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超声 ADNEX 模型对卵巢良恶性肿瘤诊断价值的评价

目的：探讨ADNEX模型在国际卵巢肿瘤分析诊断模型中对卵巢肿瘤的诊断性能，进一步探讨其在卵巢肿瘤分期中的应用价值。
方法：选取2018年1月至2020年6月在我院接受超声评估附件包块并因附件包块接受手术治疗的224例患者进行ADNEX模型诊断准确性研究。收集患者的临床资料和超声检查结果，以病理诊断为金标准。根据 ADNEX 模型，卵巢肿瘤分为 5 种亚型：良性和交界性、I 期、II-IV 期和转移癌。计算ADNEX模型的敏感性、特异性、阳性预测值、阴性预测值、诊断优势比和受试者工作特征曲线下面积（AUC）。
结果：224例患者中，良性肿瘤119例（53.1%），恶性肿瘤105例（46.9%）。当恶性肿瘤风险的临界值为 10% 时，包含 CA 125 的 ADNEX 模型的敏感性为 94.3%（95% CI：88.0-97.9%），特异性为 74.0%（95% CI：65.1-81.6%） ，阳性预测值为 76.2%（95% CI：70.2–81.3%），阴性预测值为 93.6%（95% CI：87.0–97.0%），诊断优势比为 45.25，AUC 为 0.94（95% CI : 0.90– 0.97) 用于区分良性和恶性卵巢肿瘤。不包括 CA 125 的模型中的 AUC 为 0.93（95% CI：0.89-0.96），但差异无统计学意义（P=0.20）。当应用中包含 CA 125 测量时，ADNEX 模型诊断所有亚型卵巢肿瘤的准确性超过 80%，
结论： ADNEX模型在鉴别卵巢良恶性肿瘤方面表现出良好的诊断性能。该模型对卵巢肿瘤所有亚型的诊断具有一定的临床价值，但对卵巢交界性、Ⅰ期和转移性卵巢肿瘤的诊断敏感性不理想，有待验证。

关键词： IOTA，ADNEX模型，卵巢肿瘤，超声