AI Article Synopsis

  • - This study evaluated the effectiveness of three diagnostic tools—Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH-I), and Ovarian Adnexal Reporting and Data System (O-RADS)—for predicting ovarian cancer in patients with ovarian tumors.
  • - Conducted on 462 patients between May 2020 and December 2022, the research found that O-RADS combined with cancer markers like CA125 provided the most accurate predictions, demonstrating high sensitivity and specificity.
  • - The results indicated that while all models showed good predictive values, the combination of O-RADS with CA125 yielded the highest predictive accuracy for ovarian cancer detection.

Article Abstract

Objective: 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).

Methods: 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.

Results: 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).

Conclusion: 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.

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http://dx.doi.org/10.3802/jgo.2025.36.e30DOI Listing

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Article Synopsis
  • - This study evaluated the effectiveness of three diagnostic tools—Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH-I), and Ovarian Adnexal Reporting and Data System (O-RADS)—for predicting ovarian cancer in patients with ovarian tumors.
  • - Conducted on 462 patients between May 2020 and December 2022, the research found that O-RADS combined with cancer markers like CA125 provided the most accurate predictions, demonstrating high sensitivity and specificity.
  • - The results indicated that while all models showed good predictive values, the combination of O-RADS with CA125 yielded the highest predictive accuracy for ovarian cancer detection.
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Background: We aimed to analyze the benign and malignant identification efficiency of CA125, HE4, risk of ovarian malignancy algorithm (ROMA), Copenhagen Index (CPH-I) in ovarian neoplasms and establish a nomogram to improve the preoperative evaluation value of ovarian neoplasms.

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Article Synopsis
  • This study aimed to assess how well CA125, HE4, ROMA, and CPH-I can differentiate primary ovarian cancer from borderline and benign ovarian tumors while finding optimal cutoff values for each marker.
  • The research included 684 patients and analyzed pre-surgery marker levels, revealing that all tested markers were significantly higher in ovarian cancer cases compared to borderline and benign tumors.
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