Study Results
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Basic Information
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COMPLETED
50 participants
OBSERVATIONAL
2022-01-01
2023-01-01
Brief Summary
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Detailed Description
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Malignant tumors benefit from management in specialized oncology centers, but borderline malignancies, stage I primary invasive tumors, and advanced primary invasive tumors might require different surgical approaches. To optimize patient triage without operating on all masses, diagnostic models can be used to estimate the likelihood of malignancy and hence to plan treatment for patients. The International Ovarian Tumor Analysis Group (IOTA) has developed a multi-tumor prediction model, Assessment of Different NEoplasias in the adneXa (ADNEX) model, which is used to describe in detail the characteristics of adnexal masses. ADNEX model can not only distinguish the probability of benign and malignant AMs, but also distinguish between borderline ovarian tumors, stage I ovarian cancer, stage II-IV ovarian cancer, and secondary metastatic ovarian cancers, which includes three clinical features and six ultrasound features
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Assesment of Different NEoplasias in the adenexa model
The ADNEX model includes nine parameters; Age, CA-125 level, Oncology center (yes/no), and 6 ultrasound features which are maximal diameter of the lesion, maximal diameter of the largest solid part, more than 10 locules (yes/no), number of papillary projections (0/1/2/3/more than 3), acoustic shadow, and ascites
Risk of malignancy index
The RMI was measured as follows; Menopausal status (score is 3 as all patients were postmenopausal X Ultrasound score is based on assessment of 5 features and with the presence of one feature, the score is 1 while if more than one feature is present, the score is 3; the five ultrasound features are the presence of solid components, multilocularity, bilaterality, ascites, and metastases X CA - 125 level
Histopathologic examination
Histopathologic examination of all excised specimens was done as this is the gold standard test for detecting ovarian malignancy
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Patients with known ovarian cancer who were scheduled for interval debulking after neoadjuvant chemotherapy
40 Years
FEMALE
No
Sponsors
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Ain Shams Maternity Hospital
OTHER
Responsible Party
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Ahmed Mohammed Elmaraghy
Lecturer of Obstetrics and Gynecology
Principal Investigators
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Amr H El-Shalakany, M.D.
Role: STUDY_DIRECTOR
Ain Shams University
Kareem M Labib, M.D.
Role: STUDY_CHAIR
Ain Shams University
Hassan Morsi, PhD
Role: STUDY_CHAIR
Ain Shams University
Mortada Elsayed, M.D.
Role: STUDY_CHAIR
Ain Shams University
Locations
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AinShams university maternity hospital
Cairo, , Egypt
Countries
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References
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Nash Z, Menon U. Ovarian cancer screening: Current status and future directions. Best Pract Res Clin Obstet Gynaecol. 2020 May;65:32-45. doi: 10.1016/j.bpobgyn.2020.02.010. Epub 2020 Mar 3.
Nohuz E, De Simone L, Chene G. Reliability of IOTA score and ADNEX model in the screening of ovarian malignancy in postmenopausal women. J Gynecol Obstet Hum Reprod. 2019 Feb;48(2):103-107. doi: 10.1016/j.jogoh.2018.04.012. Epub 2018 Apr 28.
Ali MN, Habib D, Hassanien AI, Abbas AM. Comparison of the four malignancy risk indices in the discrimination of malignant ovarian masses: A cross-sectional study. J Gynecol Obstet Hum Reprod. 2021 May;50(5):101986. doi: 10.1016/j.jogoh.2020.101986. Epub 2020 Nov 13.
Barrenada L, Ledger A, Dhiman P, Collins G, Wynants L, Verbakel JY, Timmerman D, Valentin L, Van Calster B. ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies. BMJ Med. 2024 Feb 17;3(1):e000817. doi: 10.1136/bmjmed-2023-000817. eCollection 2024.
Wang R, Yang Z. Evaluating the risk of malignancy in adnexal masses: validation of O-RADS and comparison with ADNEX model, SA, and RMI. Ginekol Pol. 2023;94(10):799-806. doi: 10.5603/GP.a2023.0019. Epub 2023 Mar 17.
Munro MG, Critchley HOD, Fraser IS; FIGO Menstrual Disorders Committee. The two FIGO systems for normal and abnormal uterine bleeding symptoms and classification of causes of abnormal uterine bleeding in the reproductive years: 2018 revisions. Int J Gynaecol Obstet. 2018 Dec;143(3):393-408. doi: 10.1002/ijgo.12666. Epub 2018 Oct 10.
Ali AT, Al-Ani O, Al-Ani F. Epidemiology and risk factors for ovarian cancer. Prz Menopauzalny. 2023 Jun;22(2):93-104. doi: 10.5114/pm.2023.128661. Epub 2023 Jun 14.
Huwidi A, Abobrege A, Assidi M, Buhmeida A, Ermiah E. Diagnostic value of risk of malignancy index in the clinical evaluation of ovarian mass. Mol Clin Oncol. 2022 May 30;17(1):118. doi: 10.3892/mco.2022.2551. eCollection 2022 Jul.
Zhang S, Yu S, Hou W, Li X, Ning C, Wu Y, Zhang F, Jiao YF, Lee LTO, Sun L. Diagnostic extended usefulness of RMI: comparison of four risk of malignancy index in preoperative differentiation of borderline ovarian tumors and benign ovarian tumors. J Ovarian Res. 2019 Sep 16;12(1):87. doi: 10.1186/s13048-019-0568-3.
Yang S, Tang J, Rong Y, Wang M, Long J, Chen C, Wang C. Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer. Front Oncol. 2022 Sep 16;12:949766. doi: 10.3389/fonc.2022.949766. eCollection 2022.
Lam Huong L, Thi Phuong Dung N, Hoang Lam V, Tran Thao Nguyen N, Minh Tam L, Vu Quoc Huy N. The Optimal Cut-Off Point of the ADNEX Model for the Prediction of the Ovarian Cancer Risk. Asian Pac J Cancer Prev. 2022 Aug 1;23(8):2713-2718. doi: 10.31557/APJCP.2022.23.8.2713.
Alberg AJ, Moorman PG, Crankshaw S, Wang F, Bandera EV, Barnholtz-Sloan JS, Bondy M, Cartmell KB, Cote ML, Ford ME, Funkhouser E, Kelemen LE, Peters ES, Schwartz AG, Sterba KR, Terry P, Wallace K, Schildkraut JM. Socioeconomic Status in Relation to the Risk of Ovarian Cancer in African-American Women: A Population-Based Case-Control Study. Am J Epidemiol. 2016 Aug 15;184(4):274-83. doi: 10.1093/aje/kwv450. Epub 2016 Aug 3.
Elshami M, Tuffaha A, Yaseen A, Alser M, Al-Slaibi I, Jabr H, Ubaiat S, Khader S, Khraishi R, Jaber I, Abu Arafeh Z, Al-Madhoun S, Alqattaa A, Abd El Hadi A, Barhoush O, Hijazy M, Eleyan T, Alser A, Abu Hziema A, Shatat A, Almakhtoob F, Mohamad B, Farhat W, Abuamra Y, Mousa H, Adawi R, Musallam A, Abu-El-Noor N, Bottcher B. Awareness of ovarian cancer risk and protective factors: A national cross-sectional study from Palestine. PLoS One. 2022 Mar 21;17(3):e0265452. doi: 10.1371/journal.pone.0265452. eCollection 2022.
Rossing MA, Tang MT, Flagg EW, Weiss LK, Wicklund KG. A case-control study of ovarian cancer in relation to infertility and the use of ovulation-inducing drugs. Am J Epidemiol. 2004 Dec 1;160(11):1070-8. doi: 10.1093/aje/kwh315.
Yu L, Sun J, Wang Q, Yu W, Wang A, Zhu S, Xu W, Wang X. Ovulation induction drug and ovarian cancer: an updated systematic review and meta-analysis. J Ovarian Res. 2023 Jan 24;16(1):22. doi: 10.1186/s13048-022-01084-z.
Lycke M, Kristjansdottir B, Sundfeldt K. A multicenter clinical trial validating the performance of HE4, CA125, risk of ovarian malignancy algorithm and risk of malignancy index. Gynecol Oncol. 2018 Oct;151(1):159-165. doi: 10.1016/j.ygyno.2018.08.025. Epub 2018 Aug 24.
Other Identifiers
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11
Identifier Type: -
Identifier Source: org_study_id
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