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A Multimodal Deep Learning Model for Predicting Response to Neoadjuvant Chemotherapy Combined with Immunotherapy in Esophageal Cancer

Multimodal Deep Learning for Predicting Treatment Response to Neoadjuvant Chemoimmunotherapy in Esophageal Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600128721
Enrollment
Unknown
Registered
2026-07-24
Start date
2026-08-01
Completion date
Unknown
Last updated
2026-08-03

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

Conditions

Esophageal cancer

Interventions

Locally advanced esophageal cancer patients receiving neoadjuvant chemotherapy combined with immunotherapy:None

Sponsors

The Second Xiangya Hospital of Central South University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients with histologically confirmed esophageal cancer by biopsy; 2. Patients recommended for neoadjuvant chemotherapy combined with immunotherapy after multidisciplinary team (MDT) consultation or evaluation by thoracic surgery experts; 3. Patients who underwent neoadjuvant chemotherapy combined with immunotherapy at our center; 4. Availability of complete imaging data at our center before and after neoadjuvant treatment.

Exclusion criteria

Exclusion criteria: 1. Patients who were deemed surgically operable by thoracic surgeons at our center but refused surgery; 2. Patients with missing or poor-quality CT imaging data; 3. Patients with concurrent malignancies; 4. Patients with incomplete clinical data.

Design outcomes

Primary

MeasureTime frame
Postoperative successful resection;Pathological complete response (pCR);

Secondary

MeasureTime frame
Recurrence status;

Countries

China

Contacts

Public ContactHe Xue

The Second Xiangya Hospital of Central South University

hexuehuxi@csu.edu.cn+86 731 85295188

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Aug 10, 2026