Risk of malignancy index for referral of ovarian cancer cases to a tertiary center: does it identify the correct cases?

Abstract

Characterization of adnexal masses to identify patients with malignant ovarian tumors preoperatively for referral to a cancer center for treatment has been extensively studied. A simple algorithm called "risk of malignancy index" (RMI) reported by Jacobs incorporated the serum CA125 level, menopausal status, and ultrasound morphologic features. This algorithm has subsequently been tested on retrospective and prospective data with encouraging results. However, these studies did not include cases that had had both their serum CA125 measurements and ultrasound examinations from a diverse range of laboratories and sonographers. The purpose of this study was to determine the effectiveness of the RMI algorithm for identifying cases of ovarian malignancy presenting at cancer units for subsequent referral to a cancer center. All cases of suspected ovarian malignancy referred to the Northern Gynaecological Oncology Centre (NGOC) during an 18-month period were identified from the NGOC database. A case note review was performed, and the following data were extracted: patient demographics, the referring physician and the operating surgeon, ultrasound morphology, serum CA125 levels, and menopausal status. All patients had their ultrasound performed by sonographers at the peripheral unit according to local protocols. A total of 182 patients with a pelvic mass were referred to the center for surgery. A total of 24% patients had benign tumors, 6% had tumors of borderline malignancy, and 70% had invasive tumors. A total of 145 cases had an RMI >200; 125 of these had ovarian or peritoneal cancers. An RMI >200 had a sensitivity of 88.5% for diagnosing invasive lesions. The overall sensitivity of this algorithm for diagnosing all borderline, invasive ovarian, or primary peritoneal lesions was 87.4%, and the positive predictive value was 86.8%. Our data confirm the effectiveness of the RMI algorithm in clinical practice for the identification and subsequent referral to cancer centers of cases of potential ovarian malignancy. We therefore recommend its continued use.

Predictive Value of Malignancy Risk Indices for Ovarian Masses in Premenopausal and Postmenopausal Women

“…In all stages, RMI 3 had 87.4% sensitivity. (Bailey et al, 2006). In our study, the RMI 3 in a general population (cut off:200, kappa: 0.609) yielded a sensitivity of 76.1% and specificity of 90.6%.…”

Should Cut-Off Values of the Risk of Malignancy Index be Changed for Evaluation of Adnexal Masses in Asian and Pacific Populations?

“…On the other hand, according to the report by van den Akker et al from Holland, a cut-off value of 200 for RMI-3 and 450 for RMI-4 showed the best performance and yielded success rates similar to that reported by the original investigators (Tingulstad et al, 1999;Yamamoto et al, 2009;van den Akker et al, 2011). In England, Bailey et al (2006) reported 88.5% sensitivity for RMI with a cut-off value of 200. This finding was similar to that was found in other European studies (Jacobs et al, 1990;Tingulstad et al, 1996;1999).…”

Four risk of malignancy indices in evaluation of pelvic masses

“…Yamamoto et al [12], who created their own model of a malignancy risk index, added the parameter of tumor size (S) to the RMI, and have termed it RMI 4. Retrospective and prospective validation of the four versions of the RMI have been conducted in different clinical studies [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], where a cutoff value of 200 for RMI 1-3 and 450 for RMI 4 showed the best discrimination between benign and malignant pelvic masses, with high levels of sensitivity and specificity (sensitivity 51%-90%, specificity 51%-97%). The main advantage of four RMIs is that it is a simple scoring system that can be applied directly into clinical practice without the introduction of expensive or complicated methods (such as computed tomography scan, magnetic resonance imaging, and wholebody positron emission tomography).…”