Prospective Validation and Comparison of Different Ultrasound Methods for Discrimination Between Benign and Malignant Ovarian/Tubal Masses Prior to Surgery
NCT ID: NCT02847832
Last Updated: 2020-04-14
Study Results
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Basic Information
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UNKNOWN
1700 participants
OBSERVATIONAL
2016-10-31
2020-12-31
Brief Summary
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The general objective of this study is to prospectively validate the Simple Rules, ADNEX, the Simple Rules risk model, LR2, and RMI on a large multicenter dataset to allow direct comparison of these tools.
IOTA7 is an international multicenter prospective observational study including different types of ultrasound centers and examiners with different levels of ultrasound experience. In total, about 1700 adnexal masses with histological outcome will be included in IOTA 7.
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Detailed Description
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The best ultrasound method for discrimination between benign and malignant adnexal masses is subjective assessment, i.e. subjective evaluation of ultrasound findings. Subjective assessment, however, requires a very experienced ultrasound examiner. More objective methods may be preferred by less experienced examiners who are not confident with using subjective assessment. The Risk of Malignancy Index (RMI) is one such method. There are also more recently developed methods. The International Ovarian Tumor Analysis (IOTA) group have created logistic regression models (LR1, LR2, and the ADNEX model) including clinical and ultrasound information to calculate the likelihood of malignancy in adnexal masses.
The IOTA group has also suggested simple ultrasound rules that can be used to classify adnexal masses as benign or malignant.
The ability of different methods to discriminate between benign and malignant adnexal masses has been compared in a meta-analysis showing that the IOTA Simple Rules and the IOTA logistic regression model LR2 were superior to RMI and to all other methods for predicting malignancy in an adnexal mass included in the meta-analysis. However, a fair comparison of methods requires them to be applied on the same tumor population.
The general objective of this study is to prospectively validate the Simple Rules, ADNEX, the Simple Rules risk model, LR2, and RMI on a large multicenter dataset to allow direct comparison of these tools. The patients will be examined by operators of varying levels of experience, such that the investigators can study how experience might affect diagnostic performance.
IOTA7 is an international multicenter prospective observational study including different types of ultrasound centers and examiners with different levels of ultrasound experience. In total, about 1700 adnexal masses with histological outcome will be included in IOTA 7.
Patients with a known or suspected adnexal mass examined with transvaginal (or transrectal if vaginal is not possible) ultrasound by an IOTA certified ultrasound examiner and confirmed to have an adnexal mass judged not to be physiological but likely to undergo surgery (primarily planned for surgical management based on subjective assessment by the ultrasound investigator) will be recruited consecutively Upon inclusion in the study, an oral or written (depending on the requirements of the local Ethics Committee) informed consent is obtained from the patient.
Data collection is done through the web-based clinical data miner (CDM) software. Data are stored on a secure server.
First, clinical information about the patient is entered into CDM. Second, the ultrasound examiner provides a diagnosis based on subjective assessment, and notes the suggested management. Third, detailed ultrasound information needed for the different models to be validated is entered. When these data have been frozen (so they can no longer be changed) the examiner gets access to the results of the Simple Rules and ADNEX. The ultrasound examiner then records whether these results make him/her change the management suggested on the basis of subjective assessment. If so the new management is specified.
Gold standard for validation of discriminative ability and calibration is the histology of the adnexal mass within 180 days after the ultrasound examination following surgical removal by laparotomy or laparoscopy as considered appropriate by the surgeon. In case of malignancy, the stage of the malignant tumors using the classification of the International Federation of Gynecology and Obstetrics (FIGO) is noted.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Standardized transvaginal ultrasound examination
Eligibility Criteria
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Inclusion Criteria
* Pregnant patients can be included but will be analysed separately.
* Patients finally selected for conservative management can be included but will not be used for all statistical analyses.
* For patients selected for surgery, delay of surgery is not an exclusion criterion for this study, but for selected objectives only those patients in whom surgery was performed within 180 days after the ultrasound examination will be assessed.
* Patients can be selected at any age, but for patients \<18 years old, a guardian's permission should be obtained.
* Patients that only underwent transabdominal scanning can be included in the study, but will be analysed separately.
Exclusion Criteria
* Denial or withdrawal of informed consent
FEMALE
No
Sponsors
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KU Leuven
OTHER
Responsible Party
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Dirk Timmerman
Prof. Dr.
Principal Investigators
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Tom Bourne, MD, PhD
Role: STUDY_CHAIR
Queen Charlotte's & Chelsea Hospital, Imperial College London, London, UNITED KINGDOM
Ben Van Calster, MSc, PhD
Role: STUDY_CHAIR
Department Development & Regeneration, KU Leuven, Leuven, BELGIUM
Ignace Vergote, MD, PhD
Role: STUDY_CHAIR
Department of Obstetrics and Gynecology, University Hospitals KU Leuven, Leuven, BELGIUM
Lil Valentin, MD, PhD
Role: STUDY_CHAIR
Department of Obstetrics and Gynecology, Skåne University Hospital, Malmö, SWEDEN
Antonia C Testa, MD, PhD
Role: STUDY_CHAIR
Unità Operativa di Ginecologia Oncologica Dipartimento Tutela della Salute della Donna e della Vita Nascente, Università Cattolica di Sacro Cuore, Roma, ITALY
Sabine Van Huffel, MSc, PhD
Role: STUDY_CHAIR
Department of electrical engineering (ESAT SCD-SISTA), KU Leuven, Heverlee-Leuven, BELGIUM
Locations
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University Hospitals Leuven
Leuven, , Belgium
Countries
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Central Contacts
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Facility Contacts
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Dirk Timmerman, PhD
Role: primary
References
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Woo YL, Kyrgiou M, Bryant A, Everett T, Dickinson HO. Centralisation of services for gynaecological cancers - a Cochrane systematic review. Gynecol Oncol. 2012 Aug;126(2):286-90. doi: 10.1016/j.ygyno.2012.04.012. Epub 2012 Apr 13.
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Earle CC, Schrag D, Neville BA, Yabroff KR, Topor M, Fahey A, Trimble EL, Bodurka DC, Bristow RE, Carney M, Warren JL. Effect of surgeon specialty on processes of care and outcomes for ovarian cancer patients. J Natl Cancer Inst. 2006 Feb 1;98(3):172-80. doi: 10.1093/jnci/djj019.
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Valentin L, Hagen B, Tingulstad S, Eik-Nes S. Comparison of 'pattern recognition' and logistic regression models for discrimination between benign and malignant pelvic masses: a prospective cross validation. Ultrasound Obstet Gynecol. 2001 Oct;18(4):357-65. doi: 10.1046/j.0960-7692.2001.00500.x.
Timmerman D. The use of mathematical models to evaluate pelvic masses; can they beat an expert operator? Best Pract Res Clin Obstet Gynaecol. 2004 Feb;18(1):91-104. doi: 10.1016/j.bpobgyn.2003.09.009.
Jacobs I, Oram D, Fairbanks J, Turner J, Frost C, Grudzinskas JG. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br J Obstet Gynaecol. 1990 Oct;97(10):922-9. doi: 10.1111/j.1471-0528.1990.tb02448.x.
Kaijser J, Sayasneh A, Van Hoorde K, Ghaem-Maghami S, Bourne T, Timmerman D, Van Calster B. Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis. Hum Reprod Update. 2014 May-Jun;20(3):449-62. doi: 10.1093/humupd/dmt059. Epub 2013 Dec 9.
Timmerman D, Testa AC, Bourne T, Ferrazzi E, Ameye L, Konstantinovic ML, Van Calster B, Collins WP, Vergote I, Van Huffel S, Valentin L; International Ovarian Tumor Analysis Group. Logistic regression model to distinguish between the benign and malignant adnexal mass before surgery: a multicenter study by the International Ovarian Tumor Analysis Group. J Clin Oncol. 2005 Dec 1;23(34):8794-801. doi: 10.1200/JCO.2005.01.7632.
Van Calster B, Van Hoorde K, Valentin L, Testa AC, Fischerova D, Van Holsbeke C, Savelli L, Franchi D, Epstein E, Kaijser J, Van Belle V, Czekierdowski A, Guerriero S, Fruscio R, Lanzani C, Scala F, Bourne T, Timmerman D; International Ovarian Tumour Analysis Group. 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:g5920. doi: 10.1136/bmj.g5920.
Timmerman D, Testa AC, Bourne T, Ameye L, Jurkovic D, Van Holsbeke C, Paladini D, Van Calster B, Vergote I, Van Huffel S, Valentin L. Simple ultrasound-based rules for the diagnosis of ovarian cancer. Ultrasound Obstet Gynecol. 2008 Jun;31(6):681-90. doi: 10.1002/uog.5365.
Timmerman D, Van Calster B, Testa A, Savelli L, Fischerova D, Froyman W, Wynants L, Van Holsbeke C, Epstein E, Franchi D, Kaijser J, Czekierdowski A, Guerriero S, Fruscio R, Leone FPG, Rossi A, Landolfo C, Vergote I, Bourne T, Valentin L. Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group. Am J Obstet Gynecol. 2016 Apr;214(4):424-437. doi: 10.1016/j.ajog.2016.01.007. Epub 2016 Jan 19.
Installe AJ, Van den Bosch T, De Moor B, Timmerman D. Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research. JMIR Med Inform. 2014 Oct 20;2(2):e28. doi: 10.2196/medinform.3251.
Heintz AP, Odicino F, Maisonneuve P, Quinn MA, Benedet JL, Creasman WT, Ngan HY, Pecorelli S, Beller U. Carcinoma of the ovary. FIGO 26th Annual Report on the Results of Treatment in Gynecological Cancer. Int J Gynaecol Obstet. 2006 Nov;95 Suppl 1:S161-92. doi: 10.1016/S0020-7292(06)60033-7. No abstract available.
Landolfo C, Ceusters J, Valentin L, Froyman W, Van Gorp T, Heremans R, Baert T, Wouters R, Vankerckhoven A, Van Rompuy AS, Billen J, Moro F, Mascilini F, Neumann A, Van Holsbeke C, Chiappa V, Bourne T, Fischerova D, Testa A, Coosemans A, Timmerman D, Van Calster B. Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery. Br J Cancer. 2024 Apr;130(6):934-940. doi: 10.1038/s41416-024-02578-x. Epub 2024 Jan 19.
Other Identifiers
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IOTA7 s59207
Identifier Type: -
Identifier Source: org_study_id
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