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Screening for Ovarian Malignancy

NCT06348784 — Completed, 50 participants, Ain Shams Maternity Hospital

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Assessment of Different Neoplasias in the Adenxa Model Versus Risk of Malignancy Index as a Tool for Predicting Ovarian Malignancy in Postmenopausal Ovarian Cysts

RegistryNCT06348784
StatusCompleted
Study typeObservational
Enrollment50 (Actual)
SponsorAin Shams Maternity Hospital (Other)
ConditionsEarly Detection of Ovarian Cancer
InterventionsAssesment of Different NEoplasias in the adenexa model, Risk of malignancy index, Histopathologic examination (Diagnostic test)
Datesstart 2022-01-01, primary completion 2023-01-01, completion 2023-01-01, first posted 2024-04-05, last updated 2024-04-05
Locations1 site in Egypt

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-Summary

Ovarian cancer is the second most common gynecologic malignancy. In 2008, it was the seventh leading cause of cancer deaths in women worldwide. Estimating the risk of malignancy is essential in the management of adnexal masses and several mathematical models and scoring systems have been developed to be used for discrimination between benign and malignant adnexal masses. Knowledge of the specific type of adnexal pathology before surgery is likely to improve patient triage with high accuracy, and it also makes it possible to optimize treatment. The correct identification of stage I cancer is particularly important

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+Detailed description

Ovarian cancer (OC) is the third most common gynecological malignancy worldwide and carries the highest mortality. OC has an incidence of 11.7 - 12.1 per 100,000 in the USA and Europe, with slightly lower rates of disease in Asia and the Middle East. Most patients (60%) are diagnosed with advanced disease which is associated with significant mortality. The most important factor for survival is the stage at diagnosis and nowadays there isn't a proven effective screening strategy. It is necessary to identify the best tool to detect early-stage disease. To reduce the diagnostic dilemma between benign and malignant ovarian masses, a formula-based scoring system known as the risk of malignancy index (RMI) was introduced in 1990, which was termed RMI 1. RMI is a combined parameter that is simple, specific, and highly sensitive for the evaluation of adnexal masses. It is a product of ultrasound findings (U), the menopausal status (M), and serum CA-125 levels (RMI = U X M XCA-125). The original RMI (RMI-1) was modified in 1996 as (RMI 2) and again in 1999 known as (RMI 3), and the last modification was in 2009 by adding the tumor size (S) to the equation and calling it RMI 4. A systematic review of diagnostic studies concluded that the RMI I was the most effective for women with suspected ovarian malignancy.

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

+Arms and interventions

  • Assesment of Different NEoplasias in the adenexa model (Diagnostic test): 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 (Diagnostic test): 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 (Diagnostic test): Histopathologic examination of all excised specimens was done as this is the gold standard test for detecting ovarian malignancy

+Outcome measures

Primary outcomes

  • Sensitivity, specificity, positive predictive, and negative predictive value of Assessment of Different NEoplasias in the adneXa model for differentiating between benign and malignant ovarian tumors [within 120 days from the scheduled surgery date]: The diagnostic performance of the ADNEX model for differentiating between benign and malignant ovarian tumors was assessed at a threshold of 10%. The diagnostic performance was expressed as Area Under Receiver Operating Characteristic Curve (AUC)

+Eligibility

Sex: Female, ages: 40 Years to any

Inclusion Criteria:

* All the included patients were postmenopausal; postmenopausal status was defined as having ≥ 1 year of amenorrhea without using any contraceptive method in women ≥ 45 years while for women < 45 years, two consecutive FSH samples one 1month apart with levels ≥ 30 IU/L were required to confirm menopause

Exclusion Criteria:

* Accidental discovery of ovarian mass during surgery for other reasons
* Patients with known ovarian cancer who were scheduled for interval debulking after neoadjuvant chemotherapy

+Locations (1)

FacilityCityCountryStatus
AinShams university maternity hospitalCairoEgypt

+Publications

  • 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. PMID 32273169
  • 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. PMID 29709594
  • 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. PMID 33197624
  • 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. PMID 38375077
  • 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. PMID 36929789
  • 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. PMID 30198563
  • 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. PMID 37674925
  • 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. PMID 35747594
  • 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. PMID 31526390
  • 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. PMID 36185223
  • 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. PMID 36037125
  • 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. PMID 27492896
  • 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. PMID 35312720
  • 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. PMID 15561986
  • 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. PMID 36694251
  • 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. PMID 30149898

+Investigators

My Notes