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Pre Surgical Evaluation of International Ovarian Tumor Analysis (IOTA) Classification in Premenopausal Ovarian Cysts to Differentiate Benign VS Malignant: Comparison with Postoperative Histopathology

Neelum Zahir¹, Asma Hameed² and Ayesha¹

ABSTRACT

Objective: Our study aims at comparing how well the International Ovarian Tumor Analysis (IOTA) classification system can help in the distinction between the benign and malignant ovarian cysts in women below fifty years and in the light of this finding, compare the results with the conclusive post-surgical histopathological results.

Study Design: A cross-sectional-study

Place and Duration of Study: This study was conducted at the Department of Gyne, Saidu Teaching Hospital Swat from January 2019 to January 2024.

Methods: In this cross-sectional study, 150 premenopausal women diagnosed with ovarian cysts were recruited through the hospital and classified according to the IOTA system. Accompanying histopathological findings were used as the reference standard.

Results: The number of participants was 360 and the mean age of participants was 34. 2 years (SD = 5. 8). Among 150 patients, there were 30 malignant and 120 benign as per histopathological grading. Using the IOTA classification system, sensitivity of the system was 85%, specificity was 90%, the PPV was 80%, while NPV was 92%. To this end, there was a significant relationship of IOTA classification with histopathology results with
p<0. 01.

Conclusion: Hence, the IOTA classification system is very useful for distinguishing between benign and malignant cysts in premenopausal women with a high-degree sensitivity and specificity. It also assists in enhancing preoperative assessment and directs estimable clinical management.

Key Words: IOTA Classification, Ovarian Cysts, Premenopausal Women, Histopathology

Citation of article: Zahir N, Hameed A, Ayesha. Pre Surgical Evaluation of International Ovarian Tumor Analysis (IOTA) Classification in Premenopausal Ovarian Cysts to Differentiate Benign VS Malignant: Comparison with Postoperative Histopathology. Med Forum 2024;35(8):55-58. doi:10.60110/medforum.350812.