Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy

NCT07088354 | Recruiting

• 1 other identifier: ESRA-01
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to develop and validate a deep learning model to predict pathological complete response (pCR) in patients with esophageal squamous cell carcinoma who have undergone neoadjuvant immunochemotherapy. Clinical, imaging, and pathological data from previously treated patients will be collected and analyzed. The model is expected to assist in predicting treatment outcomes and guide personalized therapeutic strategies.

Conditions

Esophageal Squamous Cell Carcinoma; Neoadjuvant Immunochemotherapy; Pathological Complete Response; Deep Learning

Keywords

Esophageal Squamous Cell Carcinoma; Neoadjuvant Immunochemotherapy; Deep Learning; Pathological Complete Response

Outcome Measures

Primary Outcomes (1)

• Pathological Complete Response (pCR) Rate

  The proportion of patients achieving complete pathological remission after neoadjuvant immunochemotherapy followed by surgery.

  Assessed at the time of surgery, within 1 month post-treatment.

Secondary Outcomes (1)

• Model Performance Metrics (AUC, Accuracy, Sensitivity, Specificity, PPV, NPV)

  At the time of model validation, approximately one year on average after the completion of the research.

Study Arms (1)

ESCC Patients Undergoing Neoadjuvant Immunochemotherapy and Surgery

Patients with esophageal squamous cell carcinoma treated with neoadjuvant immunochemotherapy followed by surgery.

Diagnostic Test: The high-throughput extraction of large amounts of quantitative image features from medical images

Interventions

The high-throughput extraction of large amounts of quantitative image features from medical images DIAGNOSTIC_TEST

The high-throughput extraction of large amounts of quantitative image features from medical images

ESCC Patients Undergoing Neoadjuvant Immunochemotherapy and Surgery

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients diagnosed with esophageal squamous cell carcinoma who received at least one cycle of neoadjuvant chemotherapy combined with immunotherapy, with available contrast-enhanced chest CT scans before and after neoadjuvant treatment, and who underwent surgical resection.

You may qualify if:

• Pathologically confirmed esophageal squamous cell carcinoma (ESCC).
• Received at least one cycle of neoadjuvant chemotherapy combined with immunotherapy.
• Underwent contrast-enhanced chest CT before initiation of neoadjuvant treatment.
• Underwent contrast-enhanced chest CT after completion of neoadjuvant treatment and prior to surgery.

You may not qualify if:

• Diagnosis of other malignancies.
• Received other anti-tumor therapies before or during neoadjuvant chemo-immunotherapy.
• Incomplete clinical data.
• Poor-quality CT imaging.

Sponsors & Collaborators

• Tongji Hospital: lead

Study Sites (1)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

RECRUITING

MeSH Terms

Conditions

Esophageal Squamous Cell Carcinoma

Condition Hierarchy (Ancestors)

Carcinoma, Squamous Cell; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Squamous Cell; Esophageal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Head and Neck Neoplasms; Digestive System Diseases; Esophageal Diseases; Gastrointestinal Diseases

Study Officials

• Yangkai Li, MD, PhD

  Tongji Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Yangkai Li, MD, PhD

CONTACT

+8613995516396; doclyk@163.com

Lin Zhou, MSc

CONTACT

zhoul0928@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: professor

Study Record Dates

• First Submitted: July 17, 2025
• First Posted: July 28, 2025
• Study Start: March 1, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: July 28, 2025

Record last verified: 2025-07

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)