To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from Se...To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.展开更多
目的探讨卵巢-附件超声报告和数据风险分层系统(O-RADS US)结合卵巢恶性肿瘤风险算法(ROMA)鉴别卵巢-附件肿瘤良恶性的价值。方法回顾性分析2021年6月至2023年5月于青岛市市立医院妇产科住院治疗的卵巢-附件肿瘤患者89例的临床资料。采...目的探讨卵巢-附件超声报告和数据风险分层系统(O-RADS US)结合卵巢恶性肿瘤风险算法(ROMA)鉴别卵巢-附件肿瘤良恶性的价值。方法回顾性分析2021年6月至2023年5月于青岛市市立医院妇产科住院治疗的卵巢-附件肿瘤患者89例的临床资料。采用经阴道超声观察病灶的大小、回声、形态、内部分隔及血流分布等超声特征,按照O-RADS US对病灶进行分类,并通过糖类抗原125(CA125)和人附睾蛋白4(HE4)表达水平计算ROMA值。采用受试者操作特征(ROC)曲线分析O-RADS US、ROMA及其联合诊断卵巢癌的效能。结果本研究共收集到93个病灶,卵巢癌病灶的最大径及ROMA值均高于良性病灶,差异有统计学意义(P<0.05)。O-RADS US分类为2、3、4、5类的病灶分别占21.5%(20/93)、26.9%(25/93)、33.3%(31/93)和18.3%(17/93);联合ROMA对O-RADS US分类进行校正,则O-RADS US分类为2、3、4、5类的病灶分别占34.4%(32/93)、29.0%(27/93)、14.0%(13/93)、22.6%(21/93)。联合ROMA后,O-RADS US 2、3、4类卵巢-附件病灶分别有4、6、9个升级为O-RADS US 3、4、5类;同样,O-RADS US 5、4、3类卵巢-附件病灶分别有5、20、16个降级为O-RADS US 4、3、2类。O-RADS US诊断卵巢癌的敏感度、特异度、准确度、曲线下面积分别为80.0%、75.3%、76.3%、0.861。ROMA诊断绝经前和绝经后患者卵巢癌的敏感度、特异度、准确度及曲线下面积分别为85.0%、82.2%、82.8%、0.876及90.0%、89.0%、89.2%、0.904。O-RADS US联合ROMA诊断卵巢癌的敏感度、特异度、准确度及曲线下面积分别为95.0%、91.8%、92.5%、0.926。以O-RADS US联合ROMA诊断卵巢癌的曲线下面积最大,其次是ROMA,差异有统计学意义(P<0.05)。结论O-RADS US分类系统可以有效识别卵巢癌,与ROMA联合应用,能够克服单独应用的不足,提高卵巢癌诊断的性能,减少不必要的穿刺活检。展开更多
基金grants from Guangdong Science and Technology Department of China(No.2016A020215115)Science and Technology Bureau of Tianhe District,Guangzhou,Guangdong(No.201604KW010)Science and Technology Bureau of Huadu District,Guangzhou,Guangdong(No.HD15CXY006).
文摘To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.
基金Supported by Guangdong Science and Technology Department(2016A020215115)Huadu District Science and Technology Bureau(HD15CXY006)Tianhe District Science and Technology Bureau(201604KW010)~~
文摘目的探讨卵巢-附件超声报告和数据风险分层系统(O-RADS US)结合卵巢恶性肿瘤风险算法(ROMA)鉴别卵巢-附件肿瘤良恶性的价值。方法回顾性分析2021年6月至2023年5月于青岛市市立医院妇产科住院治疗的卵巢-附件肿瘤患者89例的临床资料。采用经阴道超声观察病灶的大小、回声、形态、内部分隔及血流分布等超声特征,按照O-RADS US对病灶进行分类,并通过糖类抗原125(CA125)和人附睾蛋白4(HE4)表达水平计算ROMA值。采用受试者操作特征(ROC)曲线分析O-RADS US、ROMA及其联合诊断卵巢癌的效能。结果本研究共收集到93个病灶,卵巢癌病灶的最大径及ROMA值均高于良性病灶,差异有统计学意义(P<0.05)。O-RADS US分类为2、3、4、5类的病灶分别占21.5%(20/93)、26.9%(25/93)、33.3%(31/93)和18.3%(17/93);联合ROMA对O-RADS US分类进行校正,则O-RADS US分类为2、3、4、5类的病灶分别占34.4%(32/93)、29.0%(27/93)、14.0%(13/93)、22.6%(21/93)。联合ROMA后,O-RADS US 2、3、4类卵巢-附件病灶分别有4、6、9个升级为O-RADS US 3、4、5类;同样,O-RADS US 5、4、3类卵巢-附件病灶分别有5、20、16个降级为O-RADS US 4、3、2类。O-RADS US诊断卵巢癌的敏感度、特异度、准确度、曲线下面积分别为80.0%、75.3%、76.3%、0.861。ROMA诊断绝经前和绝经后患者卵巢癌的敏感度、特异度、准确度及曲线下面积分别为85.0%、82.2%、82.8%、0.876及90.0%、89.0%、89.2%、0.904。O-RADS US联合ROMA诊断卵巢癌的敏感度、特异度、准确度及曲线下面积分别为95.0%、91.8%、92.5%、0.926。以O-RADS US联合ROMA诊断卵巢癌的曲线下面积最大,其次是ROMA,差异有统计学意义(P<0.05)。结论O-RADS US分类系统可以有效识别卵巢癌,与ROMA联合应用,能够克服单独应用的不足,提高卵巢癌诊断的性能,减少不必要的穿刺活检。
