Model Study on Cervical Cancer Screening Strategies and Risk Prediction

NCT06204133 | Completed DMC

• 1 other identifier: CSRM2304
• Study Type: observational
• Target: 1,112,846
• Locations: 1 country
• Sites: 7

Brief Summary

By collecting non-image medical data of women undergoing cervical screening in multiple centers in China, including age, HPV infection status, HPV infection type, TCT results, and colposcopy biopsy pathology results, a multi-source heterogeneous cervical lesion collaborative research big data platform was established. Based on artificial intelligence (AI) machine learning, cervical lesion screening features are refined, a multi-modal cervical cancer intelligent screening prediction and risk triage model is constructed, and its clinical application value is preliminarily explored.

Conditions

Cervical Cancer Screening; Risk Assessment; Artificial Intelligence; Machine Learning

Outcome Measures

Primary Outcomes (2)

• Cervical histopathology

  Cervical histopathological diagnosis within 8 weeks

  within 8 weeks，

• colposcopy

  Colposcopists use colposcopic equipment to investigate the occurrence of cervical and vaginal lesions within 8 weeks

  Percentage of patients diagnosed with cervical intraepithelial neoplasia of grade 3 (CIN3) or worse by cervical histopathological measurements within 8 weeks

Interventions

Artificial intelligence model building OTHER

Using non-image medical data of cervical lesions and clinical pathology results in different medical institutions, machine learning is adopted to establish multiple multi-modal cervical cancer intelligent screening prediction models. This method was used to analyze the prediction performance of the multi-modal cervical cancer intelligent screening prediction and risk triage model, and to evaluate and optimize the self-learning ability of the established multi-modal cervical cancer intelligent screening prediction model.

Eligibility Criteria

• Age: 25 Years - 64 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Probability Sample

Study Population

For women aged 25-64 years who undergo cervical cancer screening, all women use HR-HPV testing as a primary screening strategy.

You may qualify if:

• Age 25-64 years old;
• There was no history of precancerous lesions or cervical cancer;
• No previous cervical surgery or cervical removal;

You may not qualify if:

• HPV test results are not available;
• Pregnant or lactating women;
• There is a serious immune system disease, and the disease is active;

Sponsors & Collaborators

• Fujian Maternity and Child Health Hospital: lead

Study Sites (7)

Fujian Maternity and Child Health Hospital

Fuzhou, Fujian, 350001, China

Location

Ningde maternal and child health hospital

Ningde, Fujian, China

Location

Gansu Provincial Maternity and Child-care Hospital

Lanzhou, Ganshu, China

Location

Shunde Women's and Children's Hospital of Guangdong Medical University

Foshan, Guangdong, China

Location

Shenzhen Maternal and Child Health Hospital

Shenzhen, Guangdong, China

Location

Guiyang maternal and child health care hospital

Guiyang, Guizhou, China

Location

Hubei Maternal and Child Health Hospital

Wuhan, Hubei, China

Location

Study Officials

• Pengming Sun

  Fujian Maternal and Child Health Hospital

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 15, 2023
• First Posted: January 12, 2024
• Study Start: November 1, 2023
• Primary Completion: April 30, 2024
• Study Completion: June 30, 2024
• Last Updated: July 22, 2024

Record last verified: 2024-07

Locations

CN (7)