Introduction: Ovarian cancer is considered the most lethal gynecologic malignancy because it is difficult to diagnose in its early stages. Ovarian malignancy prediction models may be useful in discriminating between benign and malignant masses, allowing for accurate and timely referral as well as proper therapeutic care Objective: To evaluate the diagnostic performance of the four ovarian prediction models: Risk of Malignancy Index‑4 (RMI‑4), Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH‑I), and International Ovarian Tumor Analysis (IOTA)‑Assessment of Different NEoplasias in the AdneXa (ADNEX) in identifying malignant and benign ovarian masses Materials and Methods: This was a retrospective, cross‑sectional, analytical diagnostic study in a tertiary hospital between January 2017 and December 2020. Receiver operating characteristic (ROC) curves, area under the curves (AUCs), sensitivities, specificities, positive and negative predictive values, and positive and negative likelihood ratios were used to assess the diagnostic performance of the prediction models. Results: We analyzed a total of 248 patients. One hundred and sixty‑one (65%) had benign tumors, 28 (11%) had borderline, and 59 (24%) had malignant tumors. The AUCs of all models were all above 90%, but when compared to the other models, CPH‑I had the best estimate. RMI‑4 had the highest sensitivity (98.3%) in diagnosing malignancy. For appropriately diagnosing benign disease, the IOTA‑ADNEX model exhibited the highest specificity (92.1%). Overall, RMI‑4 had the lowest diagnostic accuracy (74.6%), whereas IOTA‑ADNEX had the greatest (93.2%). Conclusion The four malignancy prediction models in this study were all useful tools in discriminating between benign and malignant ovarian tumors. IOTA‑ADNEX, CPH‑I, and ROMA all demonstrated overlapping diagnostic performances indicating that they are equal in that regard. In terms of sensitivity in predicting malignancy, RMI‑4 was the most sensitive. CPH‑I is the predictor with the best overall estimate. Lastly, IOTA‑ADNEX was the most specific, and displayed highest diagnostic accuracy among the four
Ovarian Neoplasms ; Roma ; Humans ; Female

OBJECTIVE: To estimate the incidence of falsely elevated risk of ovarian malignancy algorithm (ROMA) in a group of women with pathologically confirmed endometrioma and to investigate the associated factors. METHODS: One hundred premenopausal women surgically diagnosed with ovarian endometrioma were selected. Preoperative clinical, laboratory, and surgical characteristics were compared between the elevated-risk group (ROMA-premenopausal value, ≥7.4%) and normal-risk group (ROMA-premenopausal value, <7.4%). RESULTS: Elevated ROMA was observed in 15 women (false positive rate, 15%). Excluding one woman with known chronic renal failure, we compared the characteristics of 99 women between the elevated-risk group (n=14) and the normalrisk group (n=85). None of the clinical and surgical variables distinguished the two groups. Serum level of CA 125 >82.3 U/mL and serum level of human epididymis protein 4 (HE4) >46 pmol/L could predict an elevated ROMA test with a statistical significance. When serum level of HE4 ≤46 pmol/L, none of the women showed an elevated ROMA test, regardless of serum level of CA 125; however, 55.6% of the women showed an elevated ROMA test when serum level of HE4 >46 pmol/L and CA 125 ≤82.3 U/mL and all women showed an elevated ROMA test when serum level of HE4 >46 pmol/L and CA 125 >82.3 U/mL. CONCLUSION: The incidence of falsely elevated ROMA was 15% in the group of women with pathologically confirmed endometrioma. Interpretation of the ROMA results should be cautious when serum level of HE4 >46 pmol/L and CA 125 >82.3 U/mL in women with suspicious ovarian endometrioma.
Endometriosis* ; Epididymis ; Female ; Humans ; Incidence ; Kidney Failure, Chronic ; Male ; Roma

OBJECTIVE: To identify the power of tumor markers for predicting ovarian cancer according to menopausal status. METHODS: The medical records of 876 women with ovarian cysts were retrospectively reviewed. Cancer antigen 125 (CA 125), human epididymis protein 4 (HE4), and Risk of Ovarian Malignancy Algorithm (ROMA) were analyzed. Sensitivity, specificity, and the receiver operating characteristic (ROC) curve analyses of these tumor markers were evaluated. RESULTS: The sensitivity of ROMA was 66.7% and the specificity was 86.8% to detect ovarian malignancy. The patients were divided into 2 groups according to menopausal status: premenopause (n=532, 60.7%) and postmenopause (n=344, 39.3%). For diagnostic accuracy, ROMA was lower than HE4 in premenopausal women (82.7% vs. 91.4%) and lower than CA 125 in postmenopausal women (86.9% vs. 88.7%). The ROC curve analysis revealed that the power of ROMA was not significantly better than that of HE4 in premenopausal women (area under the curve [AUC], 0.731 vs. 0.732, p=0.832), and it was also not significantly better than that of CA 125 in postmenopausal women (AUC, 0.871 vs. 0.888, p=0.440). CONCLUSION: The discrimination power of tumor markers for ovarian cancer was different according to menopausal status. In predicting ovarian malignancy, ROMA was neither superior to HE4 in premenopausal women nor superior to CA 125 in postmenopausal women.
Biomarkers, Tumor ; CA-125 Antigen ; Discrimination (Psychology) ; Epididymis ; Female ; Humans ; Male ; Medical Records ; Menopause ; Ovarian Cysts ; Ovarian Neoplasms ; Postmenopause ; Premenopause ; Retrospective Studies ; ROC Curve ; Roma ; Sensitivity and Specificity