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比较四种不同的恶性风险指数在鉴别卵巢良恶性肿块中的应用

Comparing Four Different Risk Malignancy Indices in Differentiating Benign and Malignant Ovarian Masses.

作者信息

Mundhra Rajlaxmi, Bahadur Anupama, Kashibhatla Jyotshna, Kishore Sanjeev, Chaturvedi Jaya

机构信息

Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.

Department of Pathology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.

出版信息

J Midlife Health. 2024 Apr-Jun;15(2):75-80. doi: 10.4103/jmh.jmh_192_23. Epub 2024 Jul 5.

Abstract

BACKGROUND

Accurate prediction of ovarian masses preoperatively is crucial for optimal management of ovarian cancers.

OBJECTIVE

The objective of this study was to identify the risk of malignancy index (RMI) incorporating menopausal status, serum carbohydrate antigen 125 levels, and imaging findings for presurgical differentiation of benign from malignant ovarian masses and to evaluate the diagnostic ability of four different RMIs.

MATERIALS AND METHODS

Women presenting with ovarian masses from August 2018 to January 2020 were evaluated preoperatively with detailed history, examination, imaging, and tumor markers. RMI 1-4 was calculated for all patients. Evaluation of the diagnostic utility of four different RMIs for preoperative identification of malignancy was based on the increment of the area under the receiver operating characteristic curve. Histopathological diagnosis was used as the gold standard test.

RESULTS

One hundred and twenty-one patients fulfilling the eligibility criteria were enrolled in this study. Benign tumors constituted 61 (50.4%) out of 121 cases, followed by malignant tumors and borderline tumors constituting 49 (40.49%) cases and 11 (9.09%) cases, respectively. The sensitivity of RMIs 1, 2, 3, and 4 was 77.0%, 63%, 77.0%, and 77.0%, respectively, and the specificity was 84%, 86%, 77%, and 71%, respectively. The RMI 2 had higher specificity at predicting malignancy than other RMIs while diagnostic accuracy was highest in RMI 1.

CONCLUSION

The RMI method is a simple and cost-effective technique in preoperative differentiation of ovarian masses.

摘要

背景

术前准确预测卵巢肿块对于卵巢癌的最佳治疗至关重要。

目的

本研究的目的是确定结合绝经状态、血清糖类抗原125水平和影像学表现的恶性风险指数(RMI),用于术前鉴别卵巢良性与恶性肿块,并评估四种不同RMI的诊断能力。

材料与方法

对2018年8月至2020年1月出现卵巢肿块的女性进行术前评估,包括详细的病史、检查、影像学和肿瘤标志物检查。为所有患者计算RMI 1-4。基于受试者操作特征曲线下面积的增加来评估四种不同RMI对术前恶性肿瘤识别的诊断效用。组织病理学诊断用作金标准测试。

结果

121名符合入选标准的患者纳入本研究。121例中良性肿瘤61例(50.4%),其次是恶性肿瘤49例(40.49%)和交界性肿瘤11例(9.09%)。RMI 1、2、3和4的敏感性分别为77.0%、63%、77.0%和77.0%,特异性分别为84%、86%、77%和71%。RMI 2在预测恶性肿瘤方面比其他RMI具有更高的特异性,而RMI 1的诊断准确性最高。

结论

RMI方法是术前鉴别卵巢肿块的一种简单且经济有效的技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b6f/11321511/3ef85a79a990/JMH-15-75-g001.jpg

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