Validation of the Adenomyosis Calculator

Adenomyosis Clinical Trial

Official title:

Prospective Validation of a Prediction Model for Diagnosing Adenomyosis With Ultrasound.

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04135118
• Other study ID #: OUS P360
• Status: Completed
• Start date: January 2, 2020
• Est. completion date: September 1, 2022

Study information

• Verified date: December 2023
• Source: Oslo University Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Adenomyosis is a disease where ectopic endometrial glands affect the muscular wall of the uterus. Women that suffer from dysmenorrhea or infertility caused by adenomyosis need to confirm or rule out adenomyosis, and therefore tools for non-histologic confirmation of adenomyosis are indubitably required. Transvaginal ultrasound has been shown to be useful in diagnosing adenomyosis, but the interpretation of findings requires significant expertise in ultrasound and experience with diagnosing adenomyosis. This is because adenomyosis shows a very heterogeneous appearance in ultrasound. There are many different diagnostic signs that have to be considered and weighed.

In a previous study, the investigators have developed a diagnostic algorithm that helps clinicians diagnose adenomyosis with transvaginal ultrasound and a clinical examination. It showed good diagnostic accuracy and seemed to be very robust with regards to artifacts and experience of the examiner. It is now necessary to validate this prediction model in a new, prospective study so it can be used in clinical practice.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 500
• Est. completion date: September 1, 2022
• Est. primary completion date: June 23, 2022
• Accepts healthy volunteers: No
• Gender: Female
• Age group: N/A to 52 Years

Eligibility

Inclusion Criteria:

• Premenopausal (defined by having had menstruation the last six month)

• If amenorrhea with levonorgestrel intrauterine device, the woman should be < 45 years old

• Hysterectomy planned due to a benign condition

• Hysterectomy does not require morcellation it is allowed to divide the uterus into 2-3 pieces, given that the orientation of the specimen is still possible for the pathologist)

• Written consent is given

• Can communicate in Norwegian or English at the Norwegian study sites, and Finnish, Swedish or English at the Finnish study site.

Exclusion Criteria:

• Gynecological cancer present at the time of inclusion

• Use of gonadotropin-releasing hormone agonist or antagonist within the last 3 months prior to the ultrasound evaluation

• Prior endometrial ablation or resection

• Postmenopausal status or no menstrual bleeding for the last 6 months, or amenorrhea with levonorgestrel-intrauterine device and age >45 years.

• Need for morcellation of the uterus

Related Conditions & MeSH terms

• Adenomyosis
• Pelvic Pain
• Pelvic Pain Syndrome

Locations

Country	Name	City	State
Finland	Turku University Hospital	Turku
Norway	Akershus University Hospital, Dept. of gynecology	Lørenskog	Akershus
Norway	Department of Gynecology, Oslo University Hospital Ullevål and Rikshospital	Oslo
Norway	Sykehuset i Vestfold	Tønsberg	Vestfold
Norway	St. Olavs Hospital, Dept. of Gynecology	Trondheim	Trøndelag

Sponsors (5)

Lead Sponsor	Collaborator
Oslo University Hospital	St. Olavs Hospital, The Hospital of Vestfold, Turku University Hospital, University Hospital, Akershus

Countries where clinical trial is conducted

Finland,  Norway, 

References & Publications (1)

Tellum T, Nygaard S, Skovholt EK, Qvigstad E, Lieng M. Development of a clinical prediction model for diagnosing adenomyosis. Fertil Steril. 2018 Oct;110(5):957-964.e3. doi: 10.1016/j.fertnstert.2018.06.009. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Diagnostic accuracy of the prediction model for adenomyosis	Diagnostic accuracy will be described using sensitivity (in %), specificity (in %), positive predictive value (in %), negative predictive value (in %), positive likelihood ratio (calculated by sensitivity/1-specificity), negative likelihood ratio (calculated as 1-sensitivity/specificity) and the area under the receiver-operator curve (as calculated with the (0-1) of the model.	1 year
Secondary	Intraclass correlation coefficient (ICC) between readers	ICC values are categorized as follows: 0-0.20, slight agreement; 0.21-0.40, fair agreement; 0.41-0.60, moderate agreement; 0.61-0.80, substantial agreement; and 0.81-1, almost perfect agreement	2 years