NCT07190040Completed
Integrating Multi-Omics Data for Enhanced Prognosis Prediction in Gastric Cancer Post-Neoadjuvant Therapy
Source: ClinicalTrials.gov · Last updated 24 Sept 2025
Brief summary (registry, in English)
Study Protocol: Integrating Multi-Omics Data for Prognosis Prediction in Gastric Cancer Post-Neoadjuvant Therapy Objective: To develop and validate an integrative prognostic nomogram for patients with locally advanced gastric cancer (LAGC) undergoing neoadjuvant therapy, combining deep learning-derived radiomic features (DeepScore), transcriptome-based immune scores (ImmuneScore), and ypTNM staging. Study Design: A retrospective, single-center cohort study. Participants: A total of 179 LAGC patients who received neoadjuvant therapy followed by radical gastrectomy at Fujian Medical University Union Hospital between January 2019 and December 2022. Patients were divided into a training cohort (n = 125) and an independent validation cohort (n = 54). Data Collection: Baseline contrast-enhanced CT scans prior to neoadjuvant therapy were used for radiomic analysis. Postoperative tumor RNA sequencing data were used for immune profiling. Clinical and pathological data, including ypTNM stage, were collected from medical records. Methods: DeepScore: Extracted from CT images using a ResNet18-based deep learning model. Significant features were selected via univariate Cox and LASSO regression. ImmuneScore: Calculated from RNA-seq data using the ESTIMATE algorithm to assess tumor immune infiltration. Nomogram Construction: A multi-omics nomogram was developed using multivariate Cox regression incorporating DeepScore, ImmuneScore, and ypTNM stage. Validation: Model performance was evaluated using time-dependent ROC analysis (AUC) and Kaplan-Meier survival analysis with log-rank tests in both cohorts. Primary Outcomes: Disease-free survival (DFS) and overall survival (OS). Statistical Analysis: Survival analyses were performed using Kaplan-Meier and Cox regression models. AUC values were computed for 1-, 2-, and 3-year DFS predictions. All analyses were conducted in R (v4.4.3).
- Status (registry)
- Completed
- Study type
- Observational
- Enrollment
- 179 (actual)
- First submitted
- 13 Sept 2025
- Start date
- 1 Jan 2019
- Primary completion date
- 31 Dec 2022
- Lead sponsor
- Chang-Ming Huang, Prof.
- Diseases
- Gastric and esophageal cancer
- NCT number
- NCT07190040
What you commit to
- Study type: Observational
- Participants enrolled: 179
- From 1 Jan 2019 to the primary completion date, 31 Dec 2022
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Absence of baseline computed tomography (CT) data prior to treatment or suboptimal CT image quality that could compromise the accuracy of radiomic information extraction
Other illness
- Gastric cancer originating from the remnant stomach
Other
- Absence of postoperative transcriptome data
Who the study is looking for
- Gastric adenocarcinoma confirmed pathologically via gastroscopy;
- Clinical staging of cT3/T4N0/+M0 with a history of receiving at least two cycles of neoadjuvant therapy
- No prior history of other malignant tumors
- Completion of radical gastrectomy
Age in the registry: 18 years to - · Sex: All
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Fujian Medical University Coordinator of this site? Confirm its status | Fuzhou | China | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.