Abdalla Nabil, Winiarek Joanna, Bachanek Michał, Cendrowski Krzysztof, Sawicki Włodzimierz
Medical University of Warsaw.
Ginekol Pol. 2016;87(12):824-829. doi: 10.5603/GP.2016.0096.
The choice of management for patients with adnexal tumors requires careful pre-surgical assessment. In case of adnexal masses, the diagnostic difficulties arise from the heterogenic nature of the adnexal diseases, presence of multiple functional changes, and lack of early symptoms of malignancy. A reliable pre-surgical differentiation cannot be performed using clinical features, ultrasound examination, or tumor markers alone. New diagnostic techniques and novel markers are under investigations, however no single test can be used to conclusively differentiate between malignant and non-malignant adnexal masses. Mathematical models and scoring systems based on different clinical, ultrasonographic and laboratory parameters alone or together may facilitate the diagnosis. Selected mathematical models and scoring systems are presented in this article. Models using only ultrasound features include simple rules, regression models, Gynecologic Imaging Report and Data System, and various morphologic scores. Some logistic regression models are based on multiple clinical and ultrasound data. The OVA1 test is based on five tumor markers without using other data. The Risk of Malignancy Algorithm uses two tumor markers with one clinical parameter. i.e. the menopausal status. Some models used clinical, ultrasound and tumor marker data together. This group of models includes risk of malignancy indices, artificial neural networks, and the ADNEX model. Although some of these models have been compared in the literature, more prospective studies are needed to select the most effective model, to develop the existing models, or to create new more effective models of oncological assessment of the adnexal tumors.
附件肿瘤患者的治疗方案选择需要进行仔细的术前评估。对于附件包块，诊断困难源于附件疾病的异质性、多种功能变化的存在以及恶性肿瘤早期症状的缺乏。仅依靠临床特征、超声检查或肿瘤标志物无法进行可靠的术前鉴别。新的诊断技术和新型标志物正在研究中，然而没有单一的检测方法可用于明确区分恶性和非恶性附件包块。基于不同临床、超声和实验室参数单独或联合使用的数学模型和评分系统可能有助于诊断。本文介绍了一些选定的数学模型和评分系统。仅使用超声特征的模型包括简单规则、回归模型、妇科影像报告和数据系统以及各种形态学评分。一些逻辑回归模型基于多种临床和超声数据。OVA1检测基于五种肿瘤标志物，不使用其他数据。恶性风险算法使用两种肿瘤标志物和一个临床参数，即绝经状态。一些模型同时使用临床、超声和肿瘤标志物数据。这组模型包括恶性风险指数、人工神经网络和ADNEX模型。尽管这些模型中的一些已在文献中进行了比较，但仍需要更多的前瞻性研究来选择最有效的模型、改进现有模型或创建更有效的附件肿瘤肿瘤学评估新模型。
