Doan Tu Tran

Comparative diagnostic performance of the early‐stage ovarian malignancy score versus other risk prediction models in early‐stage ovarian cancer: A Vietnamese prospective cohort study

Abstract Objective This study compares the diagnostic performance of the early‐stage ovarian malignancy (EOM) score against other risk prediction models for identifying early‐stage ovarian cancer. Methods This prospective cohort study involved 925 cases from the obstetrics and gynecology departments of two tertiary hospitals from May 2018 to December 2023. The data included gynecologic examination and/or ultrasound findings, menopausal status, ultrasonography features, serum CA125, and HE4 values, which were used to calculate the EOM score and compare it with other algorithms. Preoperative predictions were validated against postoperative histopathological data. Results In total, 792 cases (85.62%) were benign tumors, 74 cases (8.00%) were identified as early‐stage ovarian cancer, and 59 cases (6.38%) were classified as advanced‐stage ovarian cancer. With a cut‐off of ≥13, the EOM score achieved an area under the curve (AUC) value of 0.908 for distinguishing between cancer and non‐cancer, demonstrating sensitivity of 83.46% and specificity of 82.90%. For early‐stage cancer, the EOM score had an AUC value of 0.843. The EOM score outperformed the risk of malignancy index, the risk of ovarian malignancy algorithm, CPH‐I, CA125, and HE4 ( P  < 0.05). Conclusion The EOM score is a straightforward and effective tool for predicting early‐stage ovarian cancer, yielded performance similar to the IOTA Simple Rules combined with CA125.

Diagnostic performances of the Ovarian Adnexal Reporting and Data System, the Risk of Ovarian Malignancy Algorithm, and the Copenhagen Index in the preoperative prediction of ovarian cancer: a prospective cohort study

This study aimed to assess the diagnostic performance of the Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH-I), and Ovarian Adnexal Reporting and Data System (O-RADS) for the preoperative prediction of ovarian cancer (OC). A prospective cohort study was conducted on 462 patients diagnosed with ovarian tumors admitted to the Departments of Obstetrics and Gynecology, Hue University of Medicine and Pharmacy Hospital, and Hue Central Hospital from May 2020 to December 2022. ROMA and CPH-I were calculated using cancer antigen 125 (CA125), human epididymal protein 4 (HE4) levels, and patient characteristics (age and menopausal status). O-RADS criteria were applied to describe ovarian tumor characteristics from ultrasound findings. Compared with histopathological results, the predictive values of ROMA, CPH-I, and O-RADS alone or in combination with CA125/HE4 for OC were calculated. Among 462 patients, 381 had benign tumors, 11 had borderline tumors, and 50 had OC. At optimal cut-off points, ROMA's and CPH-I's areas under the curves (AUCs) were 0.880 (95% confidence interval [CI]=0.846-0.909) and 0.890 (95% CI=0.857-0.918), respectively, and ROMA and CPH-I sensitivities/specificities (Se/Sp) were 68.85%/95.01% and 77.05%/91.08%, respectively. O-RADS ≥3 yielded an AUCs of 0.949 (95% CI=0.924-0.968), with Se/Sp of 88.52%/88.98% (p<0.001). Combining O-RADS with CA125 demonstrated the highest predictive value, with AUCs of 0.969 (95% CI=0.949-0.983) and Se/Sp of 98.36%/86.09% (p<0.001). The ROMA, CPH-I, O-RADS, O-RADS + CA125, and O-RADS + HE4 models demonstrated good predictive values for OC; the combination of O-RADS and CA125 yielded the highest values.