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Machine learning-based pathomics signature could act as a novel prognostic marker for patients with Esophageal Squamous Cell Carcinoma:A multicenter cohort study

Machine learning-based pathomics signature could act as a novel prognostic marker for patients with Esophageal Squamous Cell Carcinoma:A multicenter cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400083568
Enrollment
Unknown
Registered
2024-04-28
Start date
2024-05-01
Completion date
Unknown
Last updated
2024-04-29

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

Conditions

Esophageal Cancer

Interventions

Tranning Cohort:None
Internal Validation Cohort:None

Sponsors

Fujian Medical University Union Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Confirmed cases: Patients diagnosed pathologically with esophageal squamous cell carcinoma (ESCC). 2. Complete treatment information: There are complete records of treatment history, including surgery, radiotherapy, chemotherapy, or other comprehensive treatment plans. 3. Available pathological samples: High-quality pathological slides available for machine learning analysis, including but not limited to paraffin-embedded blocks and frozen sections. 4. Follow-up data: Reliable follow-up data available, with a minimum follow-up time of one year, including survival status, recurrence information, and survival time. 5. Age range: Aged 18 and above.

Exclusion criteria

Exclusion criteria: 1. Other cancer history: Presence of an active case or treatment history of other types of cancer. 2. Incomplete data: Lack of complete treatment or follow-up data. 3. Poor sample quality: Pathological samples of poor quality due to improper fixation, handling, or prolonged storage, making them unsuitable for effective machine learning analysis. 4. Serious comorbidities: Presence of serious comorbidities that affect prognosis assessment, such as uncontrolled heart disease, liver failure, etc. 5. Age restriction: Patients under the age of 18.

Design outcomes

Primary

MeasureTime frame
Survival Status;Overall Survival;

Secondary

MeasureTime frame
Recurrence Status;Disease-Free Survival ;

Countries

China

Contacts

Public ContactMingqiang Kang

Fujian Medical University Union Hospital

mingqiang_kang@163.com+86 156 5910 0468

Outcome results

None listed

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