Department of Obstetrics and Gynecology, Skåne University Hospital Malmö, Lund University, Lund, Sweden.
Ultrasound Obstet Gynecol. 2013 May;41(5):570-81. doi: 10.1002/uog.12294. Epub 2013 Apr 8.
To develop a logistic regression model for discrimination between benign and malignant unilocular solid cysts with papillary projections but no other solid components, and to compare its diagnostic performance with that of subjective evaluation of ultrasound findings (subjective assessment), CA 125 and the risk of malignancy index (RMI).
Among the 3511 adnexal masses in the International Ovarian Tumor Analysis (IOTA) database there were 252 (7%) unilocular solid cysts with papillary projections but no other solid components ('unilocular cysts with papillations'). All had been examined with transvaginal ultrasound using the IOTA standardized research protocol. The ultrasound examiner had also classified each mass as certainly or probably benign, unclassifiable, or certainly or probably malignant. A logistic regression model to discriminate between benignity and malignancy was developed for all unilocular cysts with papillations (175 tumors in the training set and 77 in the test set) and for unilocular cysts with papillations for which the ultrasound examiner was not certain about benignity/malignancy (113 tumors in the training set and 53 in the test set). The gold standard was the histological diagnosis of the surgically removed adnexal mass.
A model containing six variables was developed for all unilocular cysts with papillations. The model had an area under the receiver-operating characteristics curve (AUC) on the test set of 0.83 (95% CI, 0.74-0.93). The optimal risk cut-off, as defined on the training set (0.35), resulted in sensitivity 69% (20/29), specificity 79% (38/48), positive likelihood ratio (LR +) 3.31 and negative likelihood ratio (LR-) 0.39 on the test set. The corresponding values for subjective assessment when using the ultrasound examiner's dichotomous classification of the mass as benign or malignant were 97% (28/29), 79% (38/48), 4.63 and 0.04. A model containing four variables was developed for unilocular cysts with papillations for which the ultrasound examiner was not certain about benignity/malignancy. The model had an AUC of 0.74 (95% CI, 0.60-0.88) on the test set. The optimal risk cut-off of the model, as defined on the training set (0.30), resulted in sensitivity 57% (12/21), specificity 78% (25/32), LR + 2.61 and LR- 0.55 on the test set. The corresponding values for subjective assessment were 95% (20/21), 78% (25/32), 4.35 and 0.06. CA 125 and RMI had virtually no diagnostic ability.
Even though logistic regression models to predict malignancy in unilocular cysts with papillations can be developed, they have at most moderate performance and are not superior to subjective assessment for discrimination between benignity and malignancy.
建立一个用于鉴别具有乳头状突起但无其他实性成分的良性和恶性单侧实性囊肿的逻辑回归模型，并将其诊断性能与超声发现的主观评估、CA125 和风险恶性指数（RMI）进行比较。
在国际卵巢肿瘤分析（IOTA）数据库的 3511 个附件肿块中，有 252 个（7%）单侧实性囊肿伴乳头状突起但无其他实性成分（“单侧伴有突起的实性囊肿”）。所有病例均经阴道超声检查，采用 IOTA 标准化研究方案。超声检查者还将每个肿块分类为肯定良性、可能良性、无法分类、肯定恶性或可能恶性。为所有单侧伴有突起的实性囊肿（训练集 175 个肿瘤，测试集 77 个肿瘤）以及超声检查者对良性/恶性不确定的单侧伴有突起的实性囊肿（训练集 113 个肿瘤，测试集 53 个肿瘤）建立了鉴别良恶性的逻辑回归模型。金标准是手术切除的附件肿块的组织学诊断。
为所有单侧伴有突起的实性囊肿建立了一个包含 6 个变量的模型。该模型在测试集中的受试者工作特征曲线（ROC）下面积为 0.83（95%CI，0.74-0.93）。在训练集上定义的最佳风险截止值（0.35）在测试集上产生了 69%（20/29）的敏感性、79%（38/48）的特异性、3.31 的阳性似然比（LR+）和 0.39 的阴性似然比（LR-）。当使用超声检查者对肿块的良性或恶性的二分法分类时，主观评估的相应值为 97%（28/29）、79%（38/48）、4.63 和 0.04。为超声检查者对良性/恶性不确定的单侧伴有突起的实性囊肿建立了一个包含 4 个变量的模型。该模型在测试集中的 AUC 为 0.74（95%CI，0.60-0.88）。在训练集上定义的模型的最佳风险截止值（0.30）在测试集上产生了 57%（12/21）的敏感性、78%（25/32）的特异性、2.61 的阳性似然比（LR+）和 0.55 的阴性似然比（LR-）。主观评估的相应值为 95%（20/21）、78%（25/32）、4.35 和 0.06。CA125 和 RMI 几乎没有诊断能力。
尽管可以建立用于预测单侧伴有突起的实性囊肿恶性的逻辑回归模型，但它们的性能最多只是中等，并且在鉴别良恶性方面并不优于主观评估。
