Department of Gynecological Surgery and Gynecological Oncology of Adults and Adolescents, Pomeranian Medical University, Szczecin, Poland.
Clin Chim Acta. 2015 Feb 2;440:143-51. doi: 10.1016/j.cca.2014.11.015. Epub 2014 Nov 20.
Improvement of survival in ovarian cancer may be achieved through early diagnosis and modification of treatment. Although abnormalities in the adnexal region are frequently observed in transvaginal ultrasound, interpretation may be equivocal in some cases. If neoplastic tumor is suspected, a wide range of tests and algorithms may be applied. Risk of Malignancy Algorithm (ROMA), as first described by Moore in 2009, is one of the most popular approaches. The clinical utility of this regression model has been demonstrated in both pre- (75.6% sensitivity and 74.8% specificity) and post-menopausal (92.3% sensitivity and 74.7% specificity) women. These findings have been independently confirmed in a number of publications. The sensitivity and specificity of ROMA may, however, be improved with inclusion of supplemental data, such as age and ultrasound findings. Because of its simplicity, ROMA is a reliable tool characterized by high accuracy and reproducibility to stratify patients into a high or a low ovarian cancer risk.
通过早期诊断和治疗方式的改进，卵巢癌的生存率可能得到提高。尽管经阴道超声经常观察到附件区的异常，但在某些情况下，其解读可能存在争议。如果怀疑有肿瘤，可能会应用广泛的检查和算法。2009 年，Moore 首次描述了恶性风险算法（ROMA），这是最受欢迎的方法之一。该回归模型的临床实用性在绝经前（75.6%的敏感性和 74.8%的特异性）和绝经后（92.3%的敏感性和 74.7%的特异性）女性中均得到了证实。这一发现已经在许多出版物中得到了独立的证实。然而，通过纳入年龄和超声结果等补充数据，ROMA 的敏感性和特异性可能会提高。由于其简单性，ROMA 是一种可靠的工具，具有高精度和可重复性，可以将患者分为高风险或低风险卵巢癌。
