Assessing the accuracy and applicability of the risk of malignancy index in predicting histopathological diagnoses of ovarian malignancy among patients at Saint Paul’s Hospital Millennium Medical College in Addis Ababa, Ethiopia, in 2024

Q: What is the Risk of Malignancy Index (RMI) used for in this study?

RMI is assessed for its ability to predict histopathologic diagnoses of ovarian malignancy, with histopathology used as the gold standard.

Q: How was the study conducted and what data were used?

An institution-based two-year retrospective cohort study (2022–2023) was conducted, and data were collected from March to April 2024, including 230 cases using census sampling.

Q: What factors were significantly associated with the accuracy of RMI?

Premenopausal stage, serum CA125 level ≤ 35, and absence of a solid area on ultrasound were significantly associated with RMI diagnostic accuracy.

Sep 22, 2026

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Ovarian cancer remains a major global health challenge, driven by high mortality and restricted options for early detection. Accurate malignancy-risk estimation is essential to support evidence-based treatment decisions. This study evaluates how well the Risk of Malignancy Index (RMI) predicts histopathologic diagnoses of ovarian malignancy using histopathology as the gold standard, and examines associated factors influencing RMI diagnostic accuracy.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

Background

Objective

Method

Results

Conclusion & recommendation

Keywords

Jagema etal. BMC Cancer (2026) 26:810 BMC Cancer [https://doi.org/10.1186/s12885-026-16122-y](https://doi.org/10.1186/s12885-026-16122-y) RESEARCH Open Access Assessing the accuracy and applicability of the risk of malignancy index in predicting histopathological diagnoses of ovarian malignancy among patients at Saint Paul’s Hospital Millennium Medical College in Addis Ababa, Ethiopia, in 2024 Tilahun Jagema1, Temesgen Arusi2,4,5, Malede Birara1, Yohanna Hailu3,4,5, Tayech Arusi6, Meseret Jeldu1 and Temesgen Arusi2,4,5* Abstract Background Ovarian cancer is a significant global health concern, with high mortality rates and limited early detection methods. Accurate assessment of the risk of malignancy in ovarian tumors is crucial for guiding treatment decisions. Objective To assess the accuracy and applicability of the Risk of Malignancy Index (RMI) in predicting histopathologic diagnoses of ovarian malignancy among patients at Saint Paul’s Hospital Millennium Medical College in Addis Ababa, Ethiopia, 2024. Method An institution based a two-year retrospective cohort study (2022–2023) was conducted Data were collected from March to April 2024, including 230 cases through census sampling. Sensitivity and specificity analyses assessed the diagnostic performance of the Risk of Malignancy Index (RMI) against histopathology as the gold standard. Correlation analysis was done to evaluate the risk of malignancy with histopathology of ovarian tumor. Multivariate analysis used to evaluate the associated factors with Risk of malignancy index with significance set at p < 0.05. Result The risk of malignancy index has strong correlation (r = 0 . 701) with histopathology of ovarian tumour. The sensitivity, specificity, PPV, NPV and accuracy of risk of malignancy index in the current study were 86 .4%, 78%, 76%, 87. 6% and 81 . 7% respectively. Being at premenopausal stage [AOR = 0 . 05; 95%CI (0 .002–0. 98), serum CA125 ≤ 35 [AOR = 0 . 002; 95%CI (0 .00-0. 02)] and absence of solid area are in Ultrasound [AOR = 0 . 03; 95%CI (0 .005–0. 16)] were also significantly associated with accuracy of risk of malignancy index. *Correspondence: Temesgen Arusi[tematantu405@gmail.com](tematantu405@gmail.com) Full list of author information is available at the end of the article © The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/licenses/by-nc-nd/4.0/](vecommons.org/licenses/by-nc-nd/4.0/.)[.](vecommons.org/licenses/by-nc-nd/4.0/.) Jagema et al. BMC Cancer (2026) 26:810 Page 2 of 9 Conclusion & recommendation The correlation between RMI and histopathology of ovarian tumors is found tobe strong. The accuracy of RMI is 81. 7% and reasonably good. The menopausal status, serum level of CA-125 and presence of solid echotexture during ultrasound examination are factors significantly associated with the accuracy of risk of malignancy index. Physicians shall better use the risk of malignancy index for diagnosing the ovarian tumors. Keywords Ovarian, Cancer, Ultrasoun

FAQs

What is the Risk of Malignancy Index (RMI) used for in this study?

RMI is assessed for its ability to predict histopathologic diagnoses of ovarian malignancy, with histopathology used as the gold standard.

How was the study conducted and what data were used?

An institution-based two-year retrospective cohort study (2022–2023) was conducted, and data were collected from March to April 2024, including 230 cases using census sampling.

What factors were significantly associated with the accuracy of RMI?

Premenopausal stage, serum CA125 level ≤ 35, and absence of a solid area on ultrasound were significantly associated with RMI diagnostic accuracy.

Sep 22, 2026

Upload by Ben