Screening for Ovarian Malignancy

NCT ID: NCT06348784

Last Updated: 2024-04-05

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

50 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-01-01

Study Completion Date

2023-01-01

Brief Summary

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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

Detailed Description

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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

Conditions

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Early Detection of Ovarian Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

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

Intervention Type DIAGNOSTIC_TEST

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

Intervention Type DIAGNOSTIC_TEST

Histopathologic examination

Histopathologic examination of all excised specimens was done as this is the gold standard test for detecting ovarian malignancy

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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
Minimum Eligible Age

40 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Ain Shams Maternity Hospital

OTHER

Sponsor Role lead

Responsible Party

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Ahmed Mohammed Elmaraghy

Lecturer of Obstetrics and Gynecology

Responsibility Role PRINCIPAL_INVESTIGATOR

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

Site Status

Countries

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Egypt

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.

Reference Type BACKGROUND
PMID: 32273169 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 29709594 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 33197624 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 38375077 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36929789 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 30198563 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 37674925 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 35747594 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 31526390 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36185223 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36037125 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 27492896 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 35312720 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 15561986 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36694251 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 30149898 (View on PubMed)

Other Identifiers

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11

Identifier Type: -

Identifier Source: org_study_id

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