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Validation of the Adenomyosis Calculator

NCT ID: NCT04135118

Last Updated: 2023-12-27

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

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-01-02

Study Completion Date

2022-09-01

Brief Summary

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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.

Detailed Description

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Conditions

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Adenomyosis Pelvic Pain Syndrome

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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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
Maximum Eligible Age

52 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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The Hospital of Vestfold

OTHER

Sponsor Role collaborator

University Hospital, Akershus

OTHER

Sponsor Role collaborator

St. Olavs Hospital

OTHER

Sponsor Role collaborator

Turku University Hospital

OTHER_GOV

Sponsor Role collaborator

Oslo University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Marit Lieng

Head of department, dept. of gynecology, Oslo University Hospital

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Marit Lieng, Phd

Role: PRINCIPAL_INVESTIGATOR

Oslo University Hospital, Oslo, Norway

Locations

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Turku University Hospital

Turku, , Finland

Site Status

Akershus University Hospital, Dept. of gynecology

Lørenskog, Akershus, Norway

Site Status

St. Olavs Hospital, Dept. of Gynecology

Trondheim, Trøndelag, Norway

Site Status

Sykehuset i Vestfold

Tønsberg, Vestfold, Norway

Site Status

Department of Gynecology, Oslo University Hospital Ullevål and Rikshospital

Oslo, , Norway

Site Status

Countries

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Finland Norway

References

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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.

Reference Type BACKGROUND
PMID: 30316443 (View on PubMed)

Other Identifiers

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OUS P360

Identifier Type: -

Identifier Source: org_study_id