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Establish a molecule-clinicopathology-imaging system to accurately predict cervical cancer lymphatic metastasis and its recurrence or survival prognosis based on artificial intelligence

Establish a molecule-clinicopathology-imaging system to accurately predict cervical cancer lymphatic metastasis and its recurrence or survival prognosis based on artificial intelligence

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000037348
Enrollment
Unknown
Registered
2020-08-28
Start date
2020-09-02
Completion date
Unknown
Last updated
2020-10-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cervical cancer

Interventions

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Sponsors

Obstetrics and Gynecology Hospital of Fudan University
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to 65 Years

Inclusion criteria

Inclusion criteria: 1. Cervical cancer patients who underwent surgical treatment with pathological confirmation in our four institutions; 2. Had complete medical records; 3. Had complete follow-up data more than two years and received treatment from doctor's instructions; 4. Agreed to join in our study and signed the informed consent.

Exclusion criteria

Exclusion criteria: 1. Less than 18 years old; 2. Those who were pregnant; 3. Those who had prior malignancy; 4. Those who had preexisting chemotherapy or radiotherapy history for other conditions; 5. Those who declined to provide the follow-up data; 6. Those who participating other studies and can't enrolled in our study; 7. Those who died within 30 days after surgery.

Design outcomes

Primary

MeasureTime frame
Survival outcome;Recurrence status;Lymphatic metastasis status;SEN, SPE, ACC, AUC of ROC, PPV, NPV;

Countries

China

Contacts

Public ContactJunjun Qiu

Obstetrics and Gynecology Hospital of Fudan University

guochenyan357901@163.com+86 15221908721

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026