Department of Obstetrics and Gynecology, the Affiliated Hospital of Medical College of Qingdao University, Qingdao, Shandong 266003, China.
Chin Med J (Engl). 2012 Feb;125(3):533-5.
With the advent of color Doppler flow imaging (CDFI) and technological development of detection of serum tumor markers, new opportunities are presented to the improved risk of malignancy index (RMI) based on Jacobs' research for predicting ovarian malignancy in patients with adnexal masses.
One hundred and eighty women with an adnexal mass admitted for primary laparotomy were studied. Tumor specific growth factor (TSGF) adjusted ultrasound scores and the results of Doppler blood flow analysis were obtained before the operation. Based on the parameters which had been studied in Jacobs' research, TSGF levels and the findings of color Doppler flow imaging, the risk of malignancy model was redesigned using a binary Logistic regression model. The diagnostic efficacy of the improved risk of malignancy index (improved RMI) was compared with the Jacobs' model RMI by receiver operator characteristic (ROC) curve.
The ROC curve showed a higher sensitivity (Mcnamer's test, P < 0.05) in the discrimination between benign and malignant adnexal masses for the improved RMI than the RMI. Compared with the RMI, the improved RMI had an advantage in prediction of ovarian germ cell tumors and granular cell tumor (28.57% vs.71.43%, P < 0.05) and the early stage tumors and borderline tumors (33.33% vs. 66.67%, P < 0.05).
The predictability of the improved RMI is better than the classic Jacobs' model, especially in diagnosis of the ovarian germ cell tumors and granular cell tumor and other early stage adnexal tumors.
随着彩色多谱勒血流成像（CDFI）的出现和检测血清肿瘤标志物技术的发展，为基于 Jacobs 研究的改良恶性肿瘤风险指数（RMI）预测附件肿块患者的卵巢恶性肿瘤提供了新的机会。
对 180 名因附件肿块行初次剖腹术的女性进行研究。在手术前获得肿瘤特异性生长因子（TSGF）调整的超声评分和多普勒血流分析结果。根据 Jacobs 研究中研究的参数、TSGF 水平和彩色多谱勒血流成像的结果，使用二元 Logistic 回归模型重新设计了恶性风险模型。通过受试者工作特征（ROC）曲线比较改良恶性风险指数（改良 RMI）与 Jacobs 模型 RMI 的诊断效能。
ROC 曲线显示，改良 RMI 对鉴别附件良恶性肿块的敏感性更高（Mcnamer 检验，P<0.05）。与 RMI 相比，改良 RMI 预测卵巢生殖细胞肿瘤和颗粒细胞瘤（28.57%比 71.43%，P<0.05）和早期肿瘤和交界性肿瘤（33.33%比 66.67%，P<0.05）有优势。
改良 RMI 的预测能力优于经典 Jacobs 模型，特别是在诊断卵巢生殖细胞肿瘤和颗粒细胞瘤以及其他早期附件肿瘤方面。
