Clinical trial NCT06204133: Model Study on Cervical Cancer Screening Strategies and Risk Prediction
Official title: Model Study on Cervical Cancer Screening Strategies and Risk Prediction
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Cervical Cancer Screening
Risk Assessment
Artificial Intelligence
Machine Learning
Lead sponsor: Fujian Maternity and Child Health Hospital
Sponsor class: OTHER
First posted: 2024-01-12
Enrollment: 1112846
Sex: FEMALE
Minimum age (years): 25
Maximum age (years): 64
Standard ages: ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: RETROSPECTIVE
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.

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.

Detailed description: 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. The effect of clinical application of the model was evaluated by internal data from Fujian Province and external data from several other regions in China.

Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

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

Primary outcomes:
measure: Cervical histopathology
timeFrame: within 8 weeks，
measure: colposcopy
timeFrame: Percentage of patients diagnosed with cervical intraepithelial neoplasia of grade 3 (CIN3) or worse by cervical histopathological measurements within 8 weeks
Secondary outcomes:
Other outcomes:
Locations:
city: Fuzhou
country: China
facility: Fujian Maternity and Child Health Hospital
state: Fujian
city: Ningde
country: China
facility: Ningde maternal and child health hospital
state: Fujian
city: Lanzhou
country: China
facility: Gansu Provincial Maternity and Child-care Hospital
state: Ganshu
city: Foshan
country: China
facility: Shunde Women's and Children's Hospital of Guangdong Medical University
state: Guangdong
city: Shenzhen
country: China
facility: Shenzhen Maternal and Child Health Hospital
state: Guangdong
city: Guiyang
country: China
facility: Guiyang maternal and child health care hospital
state: Guizhou
city: Wuhan
country: China
facility: Hubei Maternal and Child Health Hospital
state: Hubei
Study officials:
affiliation: Fujian Maternal and Child Health Hospital
name: Pengming Sun
role: STUDY_CHAIR
References: