| 朱爱红,吴 云,钱 娟,余晶晶,吕晓宁.ADNEX模型联合ROMA指数、CA199鉴别卵巢肿瘤良恶性的临床价值及卵巢恶性肿瘤的影响因素分析[J].,2022,(19):3670-3675 |
| ADNEX模型联合ROMA指数、CA199鉴别卵巢肿瘤良恶性的临床价值及卵巢恶性肿瘤的影响因素分析 |
| Clinical Value of ADNEX Model Combined with ROMA Index and CA199 in Differentiating Benign and Malignant Ovarian Tumors and Analysis of Influencing Factors of Ovarian Malignant Tumors |
| 投稿时间：2022-03-07 修订日期：2022-04-04 |
| DOI：10.13241/j.cnki.pmb.2022.19.013 |
| 中文关键词: 卵巢肿瘤 良恶性 ADNEX模型 卵巢恶性肿瘤风险预测模型 糖类抗原199 影响因素 |
| 英文关键词: Ovarian tumor Benign and malignant ADNEX model Ovarian malignant tumors risk prediction model Carbohydrate antigen 199 Influencing factors |
| 基金项目:江苏省妇幼健康科研项目（F201758） |
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| 中文摘要: |
| 摘要 目的：探讨ADNEX模型联合ROMA指数、糖类抗原199（CA199）鉴别卵巢肿瘤良恶性的临床价值，并分析卵巢恶性肿瘤的影响因素。方法：选取2019年4月～2021年4月我院收治的150例卵巢肿瘤患者，以病理结果为金标准，其中良性肿瘤111例（良性组），恶性肿瘤39例（恶性组）。所有患者均进行ADNEX模型分析，开展卵巢恶性肿瘤风险预测模型（ROMA）指数分析，并检测血清CA199水平。通过受试者工作特征（ROC）曲线分析ADNEX模型联合ROMA指数、CA199鉴别诊断卵巢肿瘤良恶性的效能。此外，以单因素、多因素Logistic回归分析卵巢恶性肿瘤的影响因素。结果：ROC曲线分析结果显示：ADNEX模型联合ROMA指数、CA199鉴别诊断卵巢肿瘤良恶性的曲线下面积为0.974，明显高于三项单独应用时的0.845、0.772、0.763。单因素分析结果显示：恶性组年龄、病灶最大径大于良性组，流产次数多于良性组，CA199、人附睾蛋白4（HE4）、糖类抗原125（CA125）水平以及腹水、乳头数＞4个比例高于良性组，差异均有统计学意义（P＜0.05）。多因素Logistic回归分析结果显示：年龄、病灶最大径较大，CA199水平较高以及乳头数＞4个是卵巢恶性肿瘤的危险因素（P＜0.05）。结论：ADNEX模型联合ROMA指数、CA199鉴别卵巢肿瘤良恶性的临床价值较高，年龄、CA199水平、病灶最大径以及乳头数是卵巢恶性肿瘤的影响因素。 |
| 英文摘要: |
| ABSTRACT Objective: To investigate the clinical value of ADNEX model combined with ROMA index and carbohydrate antigen 199 (CA199) in differentiating benign and malignant ovarian tumors, and to analyze the influencing factors of ovarian malignant tumors. Methods: 150 patients with ovarian tumors who were treated in our hospital from April 2019 to April 2021 were selected. Taking the pathological results as the gold standard, there were 111 cases of benign tumors (benign group) and 39 cases of malignant tumors (malignant group). All patients underwent ADNEX model analysis, ovarian cancer risk prediction model (ROMA) index analysis was carried out, and serum CA199 level was detected. The efficacy of ADNEX model combined with ROMA index and CA199 in differential diagnosis of benign and malignant ovarian tumors was analyzed by receiver operating characteristic (ROC) curve. In addition, the influencing factors of ovarian malignant tumors were analyzed by univariate and multivariate Logistic regression. Results: ROC curve analysis showed that the area under curve of ADNEX model combined with ROMA index and CA199 in differential diagnosis of benign and malignant ovarian tumors was 0.974, which was significantly higher than 0.845, 0.772 and 0.763 when the three items were used alone. The results of univariate analysis showed that the age and maximum diameter of lesions in the malignant group were greater than those in the benign group, the number of abortions was more than that in the benign group, and the CA199, human epididymal protein 4 (HE4) and carbohydrate antigen 125(CA125) levels, ascites and number of nipples > 4 proportion were higher than those in the benign group, the differences were statistically significant(P＜0.05). Multivariate Logistic regression analysis showed that age, the largest maximum diameter of lesions, the high CA199 level and the number of nipples > 4 were the risk factors of ovarian malignant tumors (P＜0.05). Conclusion: ADNEX model combined with ROMA index and CA199 has high clinical value in differentiating benign and malignant ovarian tumors. Age, CA199 level, maximum diameter of lesions and number of nipples are the influencing factors of ovarian malignant tumors. |
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