Modified Risk of Ovarian Malignancy Algorithm and Risk of Malignancy Index in Predicting Epithelial Ovarian Cancer in Indonesian Population: A Single-centered Validation Study
Hariyono Winarto, Indira T Ongkowidjaja, Fitriyadi Kusuma, Andi D Putra, Tofan W Utami, Bismarck J Laihad, Maya Dorothea, Gatot Purwoto
Epithelial ovarian cancer, Risk of malignancy index, Risk of ovarian malignancy algorithm
Citation Information :
Winarto H, Ongkowidjaja IT, Kusuma F, Putra AD, Utami TW, Laihad BJ, Dorothea M, Purwoto G. Modified Risk of Ovarian Malignancy Algorithm and Risk of Malignancy Index in Predicting Epithelial Ovarian Cancer in Indonesian Population: A Single-centered Validation Study. J South Asian Feder Obs Gynae 2022; 14 (3):283-286.
Background: Risk of ovarian malignancy algorithm (ROMA) and risk of malignancy index (RMI) are two scoring systems that are commonly used to predict ovarian tumor malignancy. Literature shows different cutoff points for a different population.
Objective: This study aims to validate and compare the performance of ROMA and RMI and also validate the cutoff points for Indonesian population.
Methods: This is a retrospective study conducted at Dr Cipto Mangunkusumo Hospital (CMH). Medical records of patients with epithelial ovarian cancer who underwent surgery in our institution during 2010–2014 were collected. The diagnostic values of ROMA and RMI were calculated.
Results: From the analysis of 213 subjects included in this study, ROMA was statistically better than RMI [AUC (area under the curve) in all groups: 87.00% > 81.30%, p ≤0.001; postmenopausal group: AUC 91.47% > 88.97%, p ≤0.001]. RMI had values of sensitivity: 85.3%, specificity: 66.3%, positive predictive value (PPV): 79.7%, negative predictive value (NPV): 74.3%, positive likelihood ratio (LR): 2.53, negative LR: 0.22, and accuracy: 0.77. ROMA had values of sensitivity: 95.4%, specificity: 32.5%, PPV: 68.9%, NPV: 81.8%, positive LR: 1.41, negative LR: 0.14, and accuracy: 0.71. At the ideal cutoff point (RMI 330, premenopausal ROMA 30.4, and postmenopausal ROMA 53.1), ROMA showed better sensitivity and specificity than RMI (sensitivity of 82.31 vs 74.62%; specificity of 78.31 vs 75.9%).
Conclusion: ROMA is better than RMI in predicting epithelial ovarian cancer in Indonesian population. Using the modified cutoff, the specificities of both ROMA and RMI were better than the standard cutoff points.
Abuidris DO, Weng HY, Elhaj AM, et al. Incidence and survival rates of ovarian cancer in low-income women in Sudan. Mol Clin Oncol 2016;5(6):823–828. DOI: 10.3892/mco.2016.1068.
Montagnana M, Danese E, Ruzzenente O, et al. The ROMA (Risk of Ovarian Malignancy Algorithm) for estimating the risk of epithelial ovarian cancer in women presenting with pelvic mass: is it really useful? Clin Chem Lab Med 2011;49(3):521. DOI: 10.1515/CCLM.2011.075.
Arab M, Khayamzadeh M, Tehranian A, et al. Incidence rate of ovarian cancer in Iran in comparison with developed countries. Indian J Cancer 2010;47(3):322. DOI: 10.4103/0019-509X.64721.
Razi S, Ghoncheh M, Mohammadian-Hafshejani A, et al. The incidence and mortality of ovarian cancer and their relationship. ecancermedicalscience 2016;10:628. DOI: 10.3332/ecancer.2016.628.
Bailey J, Tailor A, Monaghan J. Risk of malignancy index for referral of ovarian cancer cases to a tertiary center: does it identify the correct cases? Int J Gynecol Cancer 2006;16(Suppl. 1):1–5. DOI: 10.1111/j.1525-1438.2006.00468.x.
Jacobs I, Oram D, Fairbanks J, et al. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. BJOG Int J Obstet Gynaecol 1990;97(10):922–929. DOI: 10.1111/j.1471-0528.1990.tb02448.x.
Holcomb K, Vucetic Z, Miller MC, et al. Human epididymis protein 4 offers superior specificity in the differentiation of benign and malignant adnexal masses in premenopausal women. Am J Obstet Gynecol 2011;205(4):358.e1–358.e6. DOI: 10.1016/j.ajog.2011.05.017.
Chang X, Ye X, Dong L, et al. Human epididymis protein 4 (HE4) as a serum tumor biomarker in patients with ovarian carcinoma. Int J Gynecol Cancer 2011;21(5):852–858. DOI: 10.1097/IGC.0b013e31821a3726.
Moore RG, Brown AK, Miller MC, et al. The use of multiple novel tumor biomarkers for the detection of ovarian carcinoma in patients with a pelvic mass. Gynecol Oncol 2008;108(2):402–408. DOI: 10.1016/j.ygyno.2007.10.017.
van den Akker PAJ, Aalders AL, Snijders MPLM, et al. Evaluation of the risk of malignancy index in daily clinical management of adnexal masses. Gynecol Oncol 2010;116(3):384–388. DOI: 10.1016/j.ygyno.2009.11.014.
Moore RG, Jabre-Raughley M, Brown AK, et al. Comparison of a novel multiple marker assay vs the risk of malignancy index for the prediction of epithelial ovarian cancer in patients with a pelvic mass. Am J Obstet Gynecol 2010;203(3):228.e1–228.e6. DOI: 10.1016/j.ajog.2010.03.043.
Huy NVQ, Van Khoa V, Tam LM, et al. Standard and optimal cut-off values of serum ca-125, HE4 and ROMA in preoperative prediction of ovarian cancer in Vietnam. Gynecol Oncol Rep 2018;25:110–114. DOI: 10.1016/j.gore.2018.07.002.
Anton C, Carvalho F, Oliveira E, et al. A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses. Clinics 2012;67(5): 437–441. DOI: 10.6061/clinics/2012(05)06.
Winarto H, Laihad BJ, Nuranna L. Modification of cutoff values for HE4, CA125, the risk of malignancy index, and the risk of malignancy algorithm for ovarian cancer detection in Jakarta, Indonesia. Asian Pac J Cancer Prev 2014;15(5):1949–1953. DOI: 10.7314/APJCP.2014.15.5.1949.
Tanamas G, Iskandar J, Utami TW, et al. Risk of malignancy index is not accurate as a triage tool for ovarian cancer. Indones J Obstet Gynecol 2014;2(1):50–54. DOI: 10.32771/inajog.v2i1.380.
Van Gorp T, Cadron I, Despierre E, et al. HE4 and CA125 as a diagnostic test in ovarian cancer: prospective validation of the risk of ovarian malignancy algorithm. Br J Cancer 2011;104(5):863–870. DOI: 10.1038/sj.bjc.6606092.
Zheng G, Yu H, Kannerva A, et al. Familial risks of ovarian cancer by age at diagnosis, proband type and histology. PLoS One 2018;13(10):e0205000. DOI: 10.1371/journal.pone.0205000.
Chen WT, Gao X, Han XD, et al. HE4 as a serum biomarker for ROMA prediction and prognosis of epithelial ovarian cancer. Asian Pac J Cancer Prev 2014;15(1):101–105. DOI: 10.7314/APJCP.2014.15.1.101.
Park Y, Kim Y, Lee EY, et al. Reference ranges for HE4 and CA125 in a large Asian population by automated assays and diagnostic performances for ovarian cancer. Int J Cancer 2012;130(5):1136–1144. DOI: 10.1002/ijc.26129.
Simmons AR, Baggerly K, Bast RC Jr. The emerging role of HE4 in the evaluation of advanced epithelial ovarian and endometrial carcinomas. Oncology (Williston Park) 2013;27(6):548–556. PMID: 23909069.