Diagnostic utility of Risk of Malignancy Index in differentiation of benign from malignant ovarian masses

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DOI:

https://doi.org/10.3126/ajms.v14i9.54859

Keywords:

Ovarian tumor; Histopathology; Ultrasonography

Abstract

Background: Women with adnexal masses still pose a diagnostic dilemma and require efficient triaging. The Risk of Malignancy Index (RMI) is an algorithm used for differentiation of malignant from benign ovarian masses.

Aims and Objectives: The present study aimed to evaluate the four indices RMI 1, RMI 2, RMI 3, and RMI 4 to discriminate a malignant ovarian tumor from a benign one.

Materials and Methods: This cross-sectional study was carried out at a tertiary care hospital of Eastern Uttar Pradesh, India, in 312 patients with ovarian masses. RMI scores were calculated based on pre-operative cancer antigen-125 levels, ultrasonography, and menopausal status followed by post-operative histopathology, taken as gold standard. Using cutoff points of RMI indices, the sensitivity, specificity, positive predictive value, and negative predictive value of RMI were assessed.

Results: Out of total 312 patients, 68 (21.8%) had malignant disease and 244 (78.2%) had benign pathology. All indices presented a significantly better performance in detecting malignancy than the use of a single parameter. Each of the RMIs had a different optimal threshold; however, using a threshold of 250, RMI 1, RMI 2, RMI 3, and RMI 4 had a sensitivity and specificity of 64.7%, 70.5%, 64.7%, and 65.2% and 93.4%, 83.6%, 90.2%, and 91.4%, respectively.

Conclusion: The RMI is a simple, composite tool that at lower values can reliably predict benign nature of adnexal tumors. However, at values above the cutoff points, it is helpful for appropriate surgical planning and averts radical surgeries in women of reproductive age group.

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Published

2023-09-01

How to Cite

Ankita Kumari, Vani Aditya, Shaila Mitra, & Harish Chandra Tiwari. (2023). Diagnostic utility of Risk of Malignancy Index in differentiation of benign from malignant ovarian masses. Asian Journal of Medical Sciences, 14(9), 200–207. https://doi.org/10.3126/ajms.v14i9.54859

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Section

Original Articles