Machine Learning for Early Diagnosis of Endometriosis(MLEndo)

NCT06147687 | Unknown

• 1 other identifier: Semmelweis
• Study Type: observational
• Target: 10,000
• Locations: 1 country
• Sites: 2

Brief Summary

The project aims to create a large prospective data bank using the Lucy medical mobile application and collect and analyze patient profiles and structured clinical data with artificial intelligence. In addition, authors will investigate the association of removed or restricted dietary components with quality of life, pain, and central sensitization.

Conditions

Endometriosis; Pelvic Pain; Infertility, Female

Keywords

endometriosis; infertility

Outcome Measures

Primary Outcomes (1)

• Patient- profiling using the Lucy app

  Establish a comprehensive and extensive prospective big data repository using the Lucy app. This initiative aims to identify unique clinical cohorts by leveraging various factors such as digital footprints, symptoms, patient experiences, comorbidities, clinical severity, and lifestyle patterns. By employing Using ML for big data analysis, authors can build patient profiles and structured clinical data that facilitate the early detection of endometriosis with pelvic pain. Self-reported data of the participants will be measured as follows: * Evaluating the quality of life using the 5-level EQ-5D (EQ-5D-5L) * Endometriosis Health Profile 5 (EHP-5) . * Pain scores using the Visual Analogue Scale (VAS) . * Central pain sensitization using the short version of Central Sensitization Inventory (CSI-9)

  24 month

Secondary Outcomes (1)

• Impact of diet and lifestyle on the development of endometriosis

  24 month

Other Outcomes (1)

• Economical burden of endometriosis

  24 month

Study Arms (2)

Patients with endometriosis and Healthy controls

5 000 people with endometriosis will be enrolled and followed up for 1one year. To participate in the study, the women must meet the inclusion criteria.

Diagnostic Test: Self reported data collection

Control

5 000 people in a control group will be enrolled and followed up for 1one year. To participate in the study, the women must meet the inclusion criteria.

Diagnostic Test: Self reported data collection

Interventions

Self reported data collection DIAGNOSTIC_TEST

ML assessement of colleceted data

Also known as: ML assessement

Control; Patients with endometriosis and Healthy controls

Eligibility Criteria

• Age: 14 Years - 45 Years
• Gender Eligibility Details: Women suffering from endometriosis and healthy controls
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

5000/5000 patienets with/without endometriosis This study is conducted as a multicenter, parallel-group trial. Study participants are being recruited through the Lucy app. Data are collected in the following countries: Hungary, Denmark, Sweden, Germany, and Austria. Participant recruitment began in December 2021 and is expected to continue until December 2024.

You may qualify if:

• Women in reproductive age
• patients with endometriosis
• patients without endometriosis

You may not qualify if:

• Ongoing pregnancy
• Malignant condition of ovary/uterus/breast

Sponsors & Collaborators

• Semmelweis University: lead
• University of Aarhus: collaborator

Study Sites (2)

Bokor Attila

Budapest, 1028, Hungary

RECRUITING

Semmelweis University

Budapest, 1088, Hungary

RECRUITING

MeSH Terms

Conditions

Endometriosis; Pelvic Pain; Infertility, Female; Infertility

Condition Hierarchy (Ancestors)

Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases; Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Attila Bokor

  Semmelweis University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Attila Bokor

CONTACT

703118868; attila.z.bokor@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 24 Months
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 25, 2023
• First Posted: November 28, 2023
• Study Start: January 1, 2022
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: November 28, 2023

Record last verified: 2023-09

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: Data will become available from 01.01.2025 for 5 years
• Access Criteria: Data will be available for researchers in the field

Locations

HU (2)