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Comparative study on the diagnostic accuracy of the different international ovarian tumor analysis (IOTA) predictive model in discriminating between benign and malignant ovarian new growths: Logistic regression 1 and 2 (LR1 and LR2) and assessment of the different neoplasias of the adnexa (ADNEX) model

Marnie Ann Espiritu-Concepcion, MD, DPOGS and Kareen N. Reforma, MD, FPOGS, FPSUOG
Department of Obstetrics and Gynecology, Philippine General Hospital, University of the Philippines-Manila

Objective: To compare the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA)- Logistic Regression 1 and 2 (LR1 and LR2) and the Assessment of Different Neoplasias in the Adnexa (ADNEX) model in discriminating between benign and malignant ovarian new growths

Methods: The study was a prospective validation study. It included all patients admitted at the Gynecology ward of the Philippine General Hospital for elective surgery for ovarian new growths. Demographic information and clinical data were recorded for eligible patients. Two-dimensional ultrasonography with Doppler studies were performed. Ovarian new growths were classified based on IOTA LR1, LR2 and ADNEX model. Correlation of the ultrasound findings with the histopathology report and final staging based on Federation of Gynecology and Obstetrics (FIGO) classification was done.

Results: Sixty seven (67) patients were included in the final analysis. The mean age was 43 years old (range of 17-78). There were sixteen (16) nulligravid patients (22%). Eighteen (18) out of the 67 patients (27%) had malignant ovarian masses on histopathology. The IOTA LR1 had an area under the curve (AUC) of 0.96, sensitivity of 89% (95%CI, 74-100) and specificity of 92% (95%CI, 84-100). The IOTA LR2 had an AUC of 0.88, sensitivity of 61% (95%CI, 39-84) and specificity of 96% (95%CI, 90-100). The IOTA ADNEX had an AUC of 0.96, sensitivity of 89% (95%CI, 74-100) and specificity of 76% (95%CI, 63-88). Sensitivity and specificity of IOTA ADNEX for the diagnosis of specific malignant subtypes were as follows: Borderline, 80% and 76%, Stage I, 100% and 100, Stage II-IV, 86% and 100%. Accuracy values were not computed for the metastatic cancer since there was only one case seen. There was no significant difference in the accuracy values of IOTA ADNEX with or without CA 125.

Conclusion: In conclusion, IOTA LR1, LR 2 and ADNEX models were all useful tools in discriminating between benign and malignant ovarian masses. IOTA LR1 had the highest accuracy in differentiating between benign and malignant ovarian masses.

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