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恶性肿瘤风险指数在卵巢恶性肿瘤术前诊断中的应用
引用本文:马永静,张雪玉. 恶性肿瘤风险指数在卵巢恶性肿瘤术前诊断中的应用[J]. 宁夏医科大学学报, 2005, 27(1): 17-19
作者姓名:马永静  张雪玉
作者单位:宁夏医学院附属医院妇产科,银川,750004;宁夏医学院附属医院妇产科,银川,750004
摘    要:目的评价应用恶性肿瘤风险指数(riskofmalignancyindex,RMI,为血清CA125值、超声分数、绝经状态三种指标的综合)对卵巢肿物的良、恶性进行预测的价值,探讨卵巢恶性肿瘤的术前诊断方法。方法对176例卵巢肿瘤患者分别以其术前血清CA125水平、超声分数、绝经状态以及RMI对卵巢肿瘤良、恶性进行预测,比较上述指标的敏感性、特异性及阳性预测值。结果血清CA125>35U/mL时,对卵巢肿瘤预测的敏感性为724%,特异性为690%,阳性预测值为640%;超声评分≥2时上述指标分别为737%、680%和636%;绝经后状态的上述指标分别为447%、730%和557%。以RMI200为界值,其敏感性为776%,特异性为920%,阳性预测值为881%。结论提示RMI较其它单项指标对卵巢良、恶性肿瘤的预测更为准确,是一种简单、可靠、实用的卵巢肿瘤术前诊断方法。

关 键 词:恶性肿瘤风险指数  卵巢肿瘤  诊断
文章编号:1005-8486(2005)01-0017-03
修稿时间:2004-09-13

Application of a Risk of Malignancy Index in Pre-operative Diagnosis of Ovarian Cancer
MA Yong-jing,ZHANG Xue-yu. Application of a Risk of Malignancy Index in Pre-operative Diagnosis of Ovarian Cancer[J]. Journal of Ningxia Medical College, 2005, 27(1): 17-19
Authors:MA Yong-jing  ZHANG Xue-yu
Abstract:Objective To evaluate the actual value of a risk of malignancy index (RMI), based on a serum CA125 level, ultrasound findings and menopausal status, in discriminating a benign from a malignant ovarian neoplasm. Methods One hundred and seventy six women with a ovarian neoplasm, admitted between January 2003 and July 2004, we studied the sensitivity, specificity and positive predictive value of serum CA125 level, ultrasound findings and menopausal status separately and combined into the RMI, to diagnose ovarian cancer. Results It was found that the sensitivity, specificity and positive predictive value of serum CA125>35U/mL were 72.4%, 69.0% and 64.0% respectively; those of ultrasound score>2 were 73.7%,68.0% and 63.6% ;of menopausal status were 44.7%, 73.0% and 55.7%; and of RMI>200 were 77.6%, 92.0% and 88.1%. Results showed that RMI was more accurate than any individual criterion in diagnosing cancer. Conclusions RMI is a easy, reliable and applied method of preoperative diagnosis of ovarian cancer. It can be introduced easily into clinical practice.
Keywords:risk of malignancy index  ovarian neoplasms  diagnosis
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