Clinical trial · Observational
Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer （Radiogenomics-Esophagus）
Multimodal AI-based Therapy Response Prediction and Risk Stratification for Esophageal Cancer
NCT07354295CI-TRIAL-00105154recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This AI-driven model leverages multimodal data-such as radiomics, pathomics, genomics, and broader multi-omics profiles-to capture complementary aspects of tumor biology and predict treatment response and prognosis.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Esophageal Cancer | Malignant Esophageal Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (4)
- label
- Surgical resection cohort
- description
- neither neoajuvant therapy nor anti-tumor treatment prior to surgery
- label
- neoadjuvant therapy cohort
- description
- received neoadjuvant therapy and esophagectomy
- label
- conservative treatment
- description
- concervative treatment includes chemo/immuno/radiotherapy and targeted theray
- label
- Endoscopic submucosal dissection (ESD)
- description
- Endoscopic submucosal dissection (ESD)
Primary outcomes (1)
- measure
- overall survival
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: 1. Histopathologically diagnosed esophageal cancer 2. Complete baseline clinical data available (including demographic characteristics, ECOG performance score, TNM staging, etc.) 3. No other primary malignant tumors 4. Provision of informed consent 5. Availability of pre-treatment CT imaging Exclusion Criteria: 1. Imaging data quality insufficient for analysis 2. Presence of another primary malignant tumor 3. Severe systemic disease
References
Publications (1)
- RESULTXia T, Peng S, Yang F, Wang X, Yao W. Data-driven models in locally advanced oesophageal cancer. Lancet. 2025 Sep 27;406(10510):1334-1335. doi: 10.1016/S0140-6736(25)01766-0. No abstract available. PMID 41015514