Comparison of Four Risk of Malignancy Indices for Preoperative Evaluation of Ovarian Masses: A Prospective Observational Study

  • Priyanka M
  • Panda J
  • Samantroy S
  • et al.
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Abstract

Ovarian cancer imposes a significant health burden worldwide. Although various tumor markers are available to diagnose ovarian cancer, low-resource countries like India require a humble marker or index. The Risk of Malignancy Index (RMI) has been found to be a simple yet promising tool that can be used for this purpose. In this study, we attempted to validate various RMIs with the help of menopausal status, ultrasonogram score, cancer antigen (CA) 125 value and compare all four RMIs, which would be useful to differentiate benign and malignant ovarian masses. This could be an essential tool, especially in low-resource settings. This prospective study was conducted at Kalinga Institute of Medical Sciences in Odisha, India, from September 2020 to September 2022 involving 191 patients with ovarian mass with histopathology, which was deemed the "gold standard" diagnostic tool. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RMI 1, 2, 3, and 4 were calculated and compared. Results: Out of 191 patients, 32 (16%) had malignancy and 159 (83.2%) had benign pathology. It was apparent that RMI 4 was a better tool for the initial assessment of patients with ovarian masses with a sensitivity of 80.6%, specificity of 96.2%, PPV of 81%, NPV of 96% at a cutoff of 334, and an area under the curve value of 0.939. RMI 4 followed by RMI 3 were relatively better indices than RMI 1 and RMI 2 for identifying benign and malignant ovarian masses. RMI 4 was a valuable and applicable method in diagnosing pelvic masses with a high risk of malignancy.

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APA

Priyanka, M. B., Panda, J., Samantroy, S., Panda, S. R., & Jena, P. (2023). Comparison of Four Risk of Malignancy Indices for Preoperative Evaluation of Ovarian Masses: A Prospective Observational Study. Cureus. https://doi.org/10.7759/cureus.41539

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