对比观察ADNEX模型、简单规则风险估计模型及恶性风险指数诊断卵巢良恶性肿瘤
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摘要
目的比较ADNEX模型、简单规则风险估计模型及恶性风险指数(RMI)对卵巢良恶性肿瘤的诊断价值。方法回顾性分析286例卵巢肿瘤患者的术前超声检查图像,分别以ADNEX模型、简单规则风险估计模型及RMI评估卵巢肿瘤的良恶性。以病理结果为金标准,计算并比较3种方法的敏感度、特异度,绘制ROC曲线,获得曲线下面积。结果286例卵巢肿瘤患者中,良性肿瘤142例,恶性肿瘤144例。ADNEX模型、简单规则风险估计模型、RMI诊断卵巢良恶性肿瘤的敏感度分别为83.33%(120/144)、80.56%(116/144)、65.97%(95/144),特异度分别为89.44%(127/142)、92.96%(132/142)、90.14%(128/142)。ADNEX模型与简单规则风险估计模型间敏感度及特异度差异均无统计学意义(χ~2=0.352、1.784,P=0.554、0.182),ADNEX模型及简单规则风险估计模型的敏感度均高于RMI(χ~2=16.691、7.533,P均<0.001),而特异度与RMI间差异均无统计学意义(χ~2=0、0.561,P=1.000、0.454)。ADNEX模型、简单规则风险估计模型及RMI鉴别卵巢肿瘤良恶性的AUC分别为0.864、0.868和0.788(P均<0.001)。结论 ADNEX模型及简单规则风险估计模型鉴别卵巢肿瘤良恶性的效能在一定程度上优于RMI。
Objective To compare the value of ADNEX model,simple rules risk model and the risk of malignancy index(RMI)in diagnosis of benign and malignant ovarian tumors.Methods The preoperative ultrasonic images of 286 patients with ovarian tumors were retrospectively analyzed.ADNEX model,simple rules risk model and RMI were used to differentiate benign and malignant ovarian tumors.Taken histopathological results after surgery as golden standards,the sensitivity and specificity were calculated and compared among 3 methods.ROC curve was used to obtain the area under the curves.Results Among 286 ovarian tumors,142 were benign and 144 were malignant.The sensitivity of ADNEX model,simple rules risk model and RMI was 83.33%(120/144),80.56%(116/144)and 65.97%(95/144),respectively,while the specificity was 89.44%(127/142),92.96%(132/142)and 90.14%(128/142),respectively.There was no statistical difference of sensitivity nor specificity between ADNEX model and simple rules risk model(χ~2=0.352,1.784,P=0.554,0.182).The sensitivity of ADNEX model and simple rules risk model was higher than that of RMI(χ~2=16.691,7.533,respectively,both P<0.001),while there was no statistical difference of specificity(χ~2=0,0.561,P=1,0.454).The AUC of ADNEX model,simple rules risk model and RMI was 0.864,0.868 and 0.788,respectively(all P<0.001).Conclusion ADNEX model and simple rules risk model are better than RMI in differentiating benign and malignant ovarian tumors.
Objective To compare the value of ADNEX model,simple rules risk model and the risk of malignancy index(RMI)in diagnosis of benign and malignant ovarian tumors.Methods The preoperative ultrasonic images of 286 patients with ovarian tumors were retrospectively analyzed.ADNEX model,simple rules risk model and RMI were used to differentiate benign and malignant ovarian tumors.Taken histopathological results after surgery as golden standards,the sensitivity and specificity were calculated and compared among 3 methods.ROC curve was used to obtain the area under the curves.Results Among 286 ovarian tumors,142 were benign and 144 were malignant.The sensitivity of ADNEX model,simple rules risk model and RMI was 83.33%(120/144),80.56%(116/144)and 65.97%(95/144),respectively,while the specificity was 89.44%(127/142),92.96%(132/142)and 90.14%(128/142),respectively.There was no statistical difference of sensitivity nor specificity between ADNEX model and simple rules risk model(χ~2=0.352,1.784,P=0.554,0.182).The sensitivity of ADNEX model and simple rules risk model was higher than that of RMI(χ~2=16.691,7.533,respectively,both P<0.001),while there was no statistical difference of specificity(χ~2=0,0.561,P=1,0.454).The AUC of ADNEX model,simple rules risk model and RMI was 0.864,0.868 and 0.788,respectively(all P<0.001).Conclusion ADNEX model and simple rules risk model are better than RMI in differentiating benign and malignant ovarian tumors.
引文
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[3]Van Calster B,Van Hoorde K,Valentin L,et al.Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign,borderline,early and advanced stage invasive,and secondary metastatic tumours:Prospective multicentre diagnostic study.BMJ,2014,349:g5920.
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[5]Timmerman D,Van Calster B,Testa A,et al.Predicting the risk of malignancy in adnexal masses based on the simple rules from the International Ovarian Tumor Analysis group.Am JObstet Gynecol,2016,214(4):424-437.
[6]Davies AP,Jacobs I,Woolas R,et al.The adnexal mass:Benign or malignant?Evaluation of a risk of malignancy index.Br JObstet Gynaecol,1993,100(10):927-931.
[7]Baker VV.Treatment options for ovarian cancer.Clin Obstet Gynecol,2001,44(3):522-530.
[8]Hoo WL,Yazbek J,Holland T,et al.Expectant management of ultrasonically diagnosed ovarian dermoid cysts:Is it possible to predict outcome?Ultrasound Obstet Gynecol,2010,36(2):235-240.
[9]Timmerman D.The use of mathematical models to evaluate pelvic masses;can they beat an expert operator?Best Pract Res Clin Obstet Gynaecol,2004,18(1):91-104.
[10]Valentin L,Jurkovic D,Van Calster B,et al.Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses.Ultrasound Obstet Gynecol,2009,34(3):345-354.
[11]苏坤丽,吴大保,周颖,等.恶性肿瘤风险指数在卵巢恶性肿瘤诊断中的价值.中国临床保健杂志,2016,19(2):141-143.
[12]刘婧,陈秋月,吕国荣.超声国际卵巢肿瘤研究组简单法则与妇科影像报告与数据系统分类诊断卵巢肿瘤的比较.中国医学影像技术,2017,33(5):739-742.
[13]Araujo KG,Jales RM,Pereira PN,et al.Performance of the IOTA ADNEX model in preoperative discrimination of adnexal masses in a gynecological oncology center.Ultrasound Obstet Gynecol,2017,49(6):778-783.
[14]Meys EMJ,Jeelof LS,Achten NMJ,et al.Estimating risk of malignancy in adnexal masses:External validation of the ADNEX model and comparison with other frequently used ultrasound methods.Ultrasound Obstet Gynecol,2017,49(6):784-792.
[2]Alcázar JL,Guerriero S,Laparte C,et al.Contribution of power Doppler blood flow mapping to gray-scale ultrasound for predicting malignancy of adnexal masses in symptomatic and asymptomatic women.Eur J Obstet Gynecol Reprod Biol,2011,155(1):99-105.
[3]Van Calster B,Van Hoorde K,Valentin L,et al.Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign,borderline,early and advanced stage invasive,and secondary metastatic tumours:Prospective multicentre diagnostic study.BMJ,2014,349:g5920.
[4]Sayasneh A,Ferrara L,De Cock B,et al.Evaluating the risk of ovarian cancer before surgery using the ADNEX model:Amulticentre external validation study.Br J Cancer,2016,115(5):542-548.
[5]Timmerman D,Van Calster B,Testa A,et al.Predicting the risk of malignancy in adnexal masses based on the simple rules from the International Ovarian Tumor Analysis group.Am JObstet Gynecol,2016,214(4):424-437.
[6]Davies AP,Jacobs I,Woolas R,et al.The adnexal mass:Benign or malignant?Evaluation of a risk of malignancy index.Br JObstet Gynaecol,1993,100(10):927-931.
[7]Baker VV.Treatment options for ovarian cancer.Clin Obstet Gynecol,2001,44(3):522-530.
[8]Hoo WL,Yazbek J,Holland T,et al.Expectant management of ultrasonically diagnosed ovarian dermoid cysts:Is it possible to predict outcome?Ultrasound Obstet Gynecol,2010,36(2):235-240.
[9]Timmerman D.The use of mathematical models to evaluate pelvic masses;can they beat an expert operator?Best Pract Res Clin Obstet Gynaecol,2004,18(1):91-104.
[10]Valentin L,Jurkovic D,Van Calster B,et al.Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses.Ultrasound Obstet Gynecol,2009,34(3):345-354.
[11]苏坤丽,吴大保,周颖,等.恶性肿瘤风险指数在卵巢恶性肿瘤诊断中的价值.中国临床保健杂志,2016,19(2):141-143.
[12]刘婧,陈秋月,吕国荣.超声国际卵巢肿瘤研究组简单法则与妇科影像报告与数据系统分类诊断卵巢肿瘤的比较.中国医学影像技术,2017,33(5):739-742.
[13]Araujo KG,Jales RM,Pereira PN,et al.Performance of the IOTA ADNEX model in preoperative discrimination of adnexal masses in a gynecological oncology center.Ultrasound Obstet Gynecol,2017,49(6):778-783.
[14]Meys EMJ,Jeelof LS,Achten NMJ,et al.Estimating risk of malignancy in adnexal masses:External validation of the ADNEX model and comparison with other frequently used ultrasound methods.Ultrasound Obstet Gynecol,2017,49(6):784-792.