Performance of Pre-Operative IOTA Three-Step Algorithm in Detecting Ovarian Carcinoma in a Referral Center in Indonesia
Abstract
Background: To assess the diagnostic performance of a three-step algorithm using the International Ovarian Tumor Analysis (IOTA) Group ‘simple rules’, ‘simple descriptors’, and Assessment of Different NEoplasias in the adneXa (ADNEX) model for discriminating benign and malignant adnexal masses.
Methods: This was a retrospective observational study, performed at a tertiary-care university hospital, on women diagnosed with adnexal mass on ultrasonography from January 2021 and February 2022. The examiner first classified the mass using ‘simple descriptors’ (first step) and, if not possible, using ‘simple rules’ (second step). For inconclusive masses, an assessment using the ADNEX model was done as the third step. All masses were managed surgically. Histopathology results were used as the reference standard.
Results: One hundred and forty-one women were included (median age of 48 years). Histopathology results showed 104 (73.76%) mass to be malignant, and 37 (26.24%) mass to be benign. Twelve (8.51%) of 141 masses could be classified using simple descriptors, 89 (63.12%) masses were classified using simple rules, and 40 (28.37%) masses were classified using the ADNEX model. Overall accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of the three-step algorithm were 89.36%, 94.23%, 75.68%, 91.59%, 82.35%, 3.87, and 0.08 respectively.
Conclusions: The IOTA three-step algorithm, based on the sequential use of simple descriptors, simple rules, and ADNEX model, performs well for classifying adnexal masses as benign or malignant
Keywords
DOI: 10.33371/ijoc.v18i1.1044
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References
Curry SJ, Krist AH, Owens DK, et al. Screening for cervical cancer us preventive services task force recommendation statement. JAMA - J Am Med Assoc. American Medical Association; 2018 Aug 21;320(7):674–86.
Momenimovahed Z, Tiznobaik A, Taheri S, Salehiniya H. Ovarian cancer in the world: epidemiology and risk factors. Int J Womens Health. Dove Press; 2019;11:287.
Pusat Data dan Informasi Kementerian Kesehatan RI. Beban Kanker di Indonesia. 2019.
Westwood M, Ramaekers B, Lang S, et al. Risk scores to guide referral decisions for people with suspected ovarian cancer in secondary care: a systematic review and cost-effectiveness analysis. Health Technol Assess (Rockv). NIHR Journals Library; 2018 Aug 1;22(44):V–264.
American College of Obstetricians and Gynecologists Committee on Practice Bulletins. ACOG Practice Bulletin No. 83: Management of Adnexal Masses. Obstet Gynecol. 2007 Jul;110(1):201–14.
Sokalska A, Timmerman D, Testa AC, et al. Diagnostic accuracy of transvaginal ultrasound examination for assigning a specific diagnosis to adnexal masses. Ultrasound Obstet Gynecol. Ultrasound Obstet Gynecol; 2009 Oct;34(4):462–70.
Alcázar JL, Pascual MA, Graupera B, et al. External validation of IOTA simple descriptors and simple rules for classifying adnexal masses. Ultrasound Obstet Gynecol. 2016 Sep;48(3):397–402.
Timmerman D, Testa AC, Bourne T, et al. Simple ultrasound-based rules for the diagnosis of ovarian cancer. Ultrasound Obstet Gynecol. Ultrasound Obstet Gynecol; 2008 Jun;31(6):681–90.
Ameye L, Timmerman D, Valentin L, et al. Clinically oriented three-step strategy for assessment of adnexal pathology. Ultrasound Obstet Gynecol. 2012 Nov;40(5):582–91.
Sayasneh A, Kaijser J, Preisler J, et al. A multicenter prospective external validation of the diagnostic performance of IOTA simple descriptors and rules to characterize ovarian masses. Gynecol Oncol. 2013 Jul;130(1):140–6.
Viora E, Piovano E, Baima Poma C, et al. The ADNEX model to triage adnexal masses: An external validation study and comparison with the IOTA two-step strategy and subjective assessment by an experienced ultrasound operator. Eur J Obstet Gynecol Reprod Biol. 2020 Apr;247:207–11.
Gaurilcikas A, Gedgaudaite M, Cizauskas A, et al. Performance of the IOTA ADNEX Model on Selected Group of Patients with Borderline Ovarian Tumours. Medicina (B Aires). Multidisciplinary Digital Publishing Institute (MDPI); 2020 Dec 1;56(12):1–10.
Chan JK, Urban R, Cheung MK, et al. Ovarian cancer in younger vs older women: a population-based analysis. Br J Cancer. 2006 Nov 20;95(10):1314–20.
Zheng G, Yu H, Kanerva A, et al. Familial risks of ovarian cancer by age at diagnosis, proband type and histology. Akbari MR, editor. PLoS One. 2018 Oct 3;13(10):e0205000.
Poole EM, Merritt MA, Jordan SJ, et al. Hormonal and Reproductive Risk Factors for Epithelial Ovarian Cancer by Tumor Aggressiveness. Cancer Epidemiol Biomarkers Prev. 2013 Mar 1;22(3):429–37.
Huang X, Wang Z, Zhang M, Luo H. Diagnostic Accuracy of the ADNEX Model for Ovarian Cancer at the 15% Cut-Off Value: A Systematic Review and Meta-Analysis. Front Oncol. 2021 Jun 17;11.
Van Calster B, Van Hoorde K, Valentin L, et al. Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study. BMJ. 2014 Oct 15;349(oct07 3):g5920–g5920.
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