ABSTRACT
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
Subject(s)
Humans , Female , Ovarian Neoplasms , RomeABSTRACT
OBJECTIVE@#To compare the performance of serum cancer antigen 125 (CA125), human epididymis protein 4 (HE4), Risk of Ovarian Malignancy Algorithm (ROMA) and Copenhagen index (CPH-I) for differential diagnosis of benign and malignant diseases in patients with ovarian mass.@*METHODS@#We retrospectively analyzed the data of 719 women with pelvic mass, and the performance of preoperative serum levels of CA125 and HE4, ROMA and CPH-I for differential diagnosis of the masses was compared.@*RESULTS@#Of the 710 women analyzed, 531 were diagnosed with benign ovarian lesions, 44 with borderline ovarian tumors (BOTs), 119 with epithelial ovarian cancers (EOCs), and 25 with non-EOCs. In differentiating ovarian cancer (OC) and BOT from benign lesions, the area under the receiver-operator characteristic (ROC) curve (AUC) was 0.854 for HE4, 0.856 for ROMA, 0.854 for CPH-I, and 0.792 for CA125, demonstrating better diagnostic performance of HE4, ROMA, and CPH-I than CA125 alone; the diagnostic sensitivity was 56.9% for HE4, 70.2% for CA125, 69.1% for ROMA, and 63.8% for CPH-I; the specificity was the best with HE4 (94.4%) and CPH-I (94.7%). In sub-analysis of EOC benign lesions, the AUCs of HE4, ROMA, and CPH-I increased to 0.946, 0.947, and 0.943, respectively, all greater than that of CA125 (0.888). In other sub-analyses, HE4, ROMA, and CPH-I all showed greater AUCs than CA125 alone.@*CONCLUSIONS@#This study confirms the accuracy of HE4, ROMA, and CPH-I for differentiating malignant from benign ovarian mass, and all these 3 tests show better performance than CA125. Furthermore, HE4 and CPH-I is superior to ROMA and CA125 in terms of specificity, while CA125 and ROMA have better diagnostic sensitivities.