手术切除及保守治疗中对附件良恶性肿瘤的准确预测:基于CEUS、HE4、O-RADS US v2022评估的诊断模型构建及外部验证

IF 3.8 3区 医学 Q1 REPRODUCTIVE BIOLOGY
Chun Liu, Yi Zhu, Keju Dai, Bo Tan, Hao Dong, Jing Lin, Rong He, Man Lu, Yuan Li
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引用次数: 0

摘要

目的:建立对比增强超声(CEUS)、人附睾蛋白4 (HE4)、卵巢附件报告与数据系统(O-RADS) US v2022联合诊断模型,验证其诊断效果,并与主观评价进行比较。方法:前瞻性连续收集2018年1月至2021年8月(试验组)和2021年9月至2022年9月(验证组)进行附件超声检查的O-RADS US v2022 2 ~ 5类患者的资料。实验组采用单因素和多因素分析,探讨年龄、体重指数(BMI)、病变最大直径、绝经状态、HE4、癌抗原125 (CA125)、超声造影特征与恶性病变的关系。选取独立影响因素构建诊断模型,在外部验证组进行验证,并与主观评价进行比较。结果:试验组纳入563例患者,平均年龄48.7±13.2岁;验证组纳入246例患者,平均年龄47.6±12.9岁。单因素和多因素分析显示,增强时间、增强强度、动态变化和HE4是预测附件恶性肿瘤的独立影响因素。验证组O-RADS US v2022、O-RADS US v2022 + CEUS、O-RADS US v2022 + CEUS + HE4、主观评价的敏感性和特异性分别为88.89%和70.69%、94.44%和79.31%、91.67%和92.53%、93.09%和89.66%。O-RADS US v2022、CEUS和HE4联合诊断的诊断性能(AUC = 0.980)高于O-RADS US v2022单独诊断的诊断性能(AUC = 0.876, P)结论:O-RADS US v2022、CEUS和HE4联合诊断模型在不牺牲敏感性的前提下提高了附件超声诊断的特异性,具有较高的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accurate prediction of benign and malignant adnexal tumors in surgical resection and conservative treatment: construction and external validation of a diagnostic model based on CEUS, HE4, and O-RADS US v2022 evaluation.

Purpose: To establish a diagnostic model combining contrast-enhanced ultrasound (CEUS), human epididymis protein 4 (HE4), and Ovarian-Adnexal Reporting and Data Systems (O-RADS) US v2022, verify its diagnostic efficacy, and compare it with subjective evaluation.

Methods: From January 2018 to August 2021 (the test group) and from September 2021 to September 2022 (the validation group), the data of patients classified as O-RADS US v2022 categories 2 to 5 who underwent adnexal ultrasound examinations were prospectively and continuously collected. In the test group, univariate and multivariate analyses were used to explore the relationship between age, body mass index (BMI), maximum diameter of the lesion, menopausal status, HE4, cancer antigen 125 (CA125), and the characteristics of CEUS and malignant lesions. Selecting independent influencing factors to construct diagnostic model, which was validated in the external validation group and compared with subjective evaluation.

Results: The test group included 563 patients (mean age, 48.7 ± 13.2), and the validation group included 246 patients (mean age, 47.6 ± 12.9). Univariate and multivariate analyses showed that enhancement time, enhancement intensity, dynamic changes, and HE4 were independent influencing factors for predicting adnexal malignant tumors. In the validation group, the sensitivities and specificities of O-RADS US v2022, O-RADS US v2022 + CEUS, O-RADS US v2022 + CEUS + HE4, and subjective assessment were 88.89% and 70.69%, 94.44% and 79.31%, 91.67% and 92.53%, and 93.09% and 89.66% respectively. In addition, the combined diagnostic performance of O-RADS US v2022, CEUS and HE4 (AUC = 0.980) was higher than that of O-RADS US v2022 alone (AUC = 0.876, P < 0.001) and the combination of O-RADS US v2022 + CEUS (AUC = 0.908, P < 0.001), and was comparable to the subjective evaluation (AUC = 0.963, P = 0.192).

Conclusions: The combined diagnostic model of O-RADS US v2022, CEUS and HE4 can improve the specificity of adnexal ultrasound diagnosis without sacrificing sensitivity, and it has high reliability.

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来源期刊
Journal of Ovarian Research
Journal of Ovarian Research REPRODUCTIVE BIOLOGY-
CiteScore
6.20
自引率
2.50%
发文量
125
审稿时长
>12 weeks
期刊介绍: Journal of Ovarian Research is an open access, peer reviewed, online journal that aims to provide a forum for high-quality basic and clinical research on ovarian function, abnormalities, and cancer. The journal focuses on research that provides new insights into ovarian functions as well as prevention and treatment of diseases afflicting the organ. Topical areas include, but are not restricted to: Ovary development, hormone secretion and regulation Follicle growth and ovulation Infertility and Polycystic ovarian syndrome Regulation of pituitary and other biological functions by ovarian hormones Ovarian cancer, its prevention, diagnosis and treatment Drug development and screening Role of stem cells in ovary development and function.
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