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

StatusRecruiting
PhaseNot specified
Started
View on ClinicalTrials.gov ↗

Record History

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  1. Primary completion pushed from Mar 31, 2026 to Dec 31, 2026
    • Study completion pushed from May 31, 2026 to Dec 31, 2026
    v6
  2. Re-verified, no change to tracked fieldsv5
  3. Primary completion date: Dec 31, 2025 to Mar 31, 2026v4
  4. Trial status: Active, Not Recruiting to Recruiting
    • Site details revised
    v3
  5. Eligibility criteria shortened, about 6 wordsv2
  6. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
This observational study aims to investigate a clinical cohort of patients with locally advanced esophageal cancer undergoing neoadjuvant chemoimmunotherapy. By integrating multimodal clinical data-including demographic characteristics, medical history, imaging studies, pathological findings, and laboratory tests-and employing deep learning algorithms, the study seeks to develop predictive models for the early and accurate assessment of treatment response prior to surgery. Specifically, this study focuses on addressing the following key scientific questions: 1. Can multimodal clinical data be used to construct an accurate model for predicting pathological complete response (pCR) following neoadjuvant therapy? 2. Can deep learning models enable early identification of patients with suboptimal response to neoadjuvant therapy, defined as stable disease (SD) or progressive disease (PD), before surgery?
Trial Details
NCT Number NCT07063901
Lead Sponsor Central South University
Conditions
(from sponsor)		 Esophagus Cancer
Related terms Esophageal Neoplasms
Enrollment 200 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov