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RecruitingNCT07354295Updated Mar 10, 2026

Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer （Radiogenomics-Esophagus）

An observational study in Esophageal Cancer, sponsored by Shu Peng. Recruiting at 1 site in China. Per ClinicalTrials.gov, last updated 2026-03-10.

Sponsored by Shu Peng · Observational

From the registry’s dates

  • Started Jul 2025; still recruiting 1 year 2 months later.
Study type
Observational
Model
Cohort
Time perspective
Other
Enrollment
1,500
Sex
All
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Study summary

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.

Read the detailed description

Built upon retrospective cohorts for model development and rigorously validated in prospective cohorts, the proposed AI predictive model integrates multimodal data (radiomics, pathomics, genomics, and multi-omics)-each reflecting distinct dimensions of tumor heterogeneity-to enable joint prediction of treatment response and clinical outcomes.

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Conditions studied

  • Esophageal Cancer

Keywords

  • Esophageal Cancer; AI; prediction; prognosis
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In context

Esophageal Neoplasms

1,593 studies on the registry are indexed under Esophageal Neoplasms; 461 are open to participants now.

This study's planned enrollment of 1,500 is above the median of 200 across 341 observational studies indexed under Esophageal Neoplasms.

Browse Esophageal Neoplasms studies →

Lead sponsor

This is the only study on the registry with Shu Peng as lead sponsor.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
Child (0–17), Adult (18–64), Older adult (65+)
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Patients diagnosed with esophgeal cancer and have received treatment in Tongji hospital

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

Exclusion Criteria:

  1. Imaging data quality insufficient for analysis
  2. Presence of another primary malignant tumor
  3. Severe systemic disease
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Study design

Observational model
Cohort
Time perspective
Other
Enrollment
1,500 participants (estimated)
Patient registry
No
Biospecimen retention
Samples with dna

Groups and cohorts

  • Surgical resection cohort

    neither neoajuvant therapy nor anti-tumor treatment prior to surgery

  • neoadjuvant therapy cohort

    received neoadjuvant therapy and esophagectomy

  • conservative treatment

    concervative treatment includes chemo/immuno/radiotherapy and targeted theray

  • Endoscopic submucosal dissection (ESD)

    Endoscopic submucosal dissection (ESD)

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What researchers measure

Primary outcomes

  1. overall survival

    overall survival rate in 3-years

    Time frame: From enrollment to the end of treatment at 3 years

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Study locations

1 of 1 sites recruiting
  • Tongji hospital, Tongji medical college, Huazhong university of science and technology
    Wuhan, Other (Non U.s.) 430030, China
    Recruiting
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References and documents

Publications

  • Xia 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. PubMed 41015514 ↗

Individual participant data

Plan to share: No — In accordance with the institution's data confidentiality requirements

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Mar 10, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT07354295
Lead sponsor
Shu Peng
Collaborators
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, The First Affiliated Hospital of Henan University of Science and Technology, Henan Provincial People's Hospital, Zhongnan Hospital, Renmin Hospital of Wuhan University
Responsible party
Shu Peng (Dr, Tongji Hospital) — Sponsor-investigator
First posted
Jan 21, 2026
Start date
Jul 26, 2025
Primary completion
Sep 30, 2030 (estimated)
Completion
Sep 30, 2030 (estimated)
Last update
Mar 10, 2026

Study contacts

Shu Peng, Doctor
Contact
drpeng90@hotmail.com
+8618571716422

Oversight

Data monitoring committee
No
View the source record on ClinicalTrials.gov ↗

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