Predicting Gastric Cancer Response to Chemo With Multimodal AI Model

June 8, 2024 updated by: Sixth Affiliated Hospital, Sun Yat-sen University

A Radio-Pathomic Multimodal Machine Learning Model for Predicting Pathological Complete Response to Neoadjuvant Chemotherapy in Advanced Gastric Cancer: A Retrospective Observational Study

This study aims to develop a multimodal model combining radiomic and pathomic features to predict pathological complete response (pCR) in advanced gastric cancer patients undergoing neoadjuvant chemotherapy (NAC). The researchers intended to collected pre-intervention CT images and pathological slides from patients, extract radiomic and pathomic features, and build a prediction model using machine learning algorithms. The model will be validated using a separate cohort of patients. This research intend to build a radiomic-pathomic model that can outperform models based on either radiomic or pathomic features alone, aiming to improve the prediction of pCR in gastric cancer.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 510655
        • Recruiting
        • The Sixth Affiliated Hospital, Sun Yat-sen University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients with histologically confirmed adenocarcinoma of the stomach or esophagogastric junction who received neoadjuvant chemotherapy and radical gastrectomy;

Description

Inclusion Criteria:

  • patients with histologically confirmed adenocarcinoma of the stomach or esophagogastric junction who received NAC and radical gastrectomy;
  • patients who underwent abdominal multidetector computed tomography (CT) inspection, gastroscope, and tumor tissue biopsy before any intervention started;
  • Lesions that are assessable according to The Response Evaluation Criteria in Solid Tumors Version 1.1

Exclusion Criteria:

  • Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection;
  • patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling;
  • patients with insufficient data.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Neoadjuvant chemotherapy with radical tumor resection surgery
(i) Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection; (ii) patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling; (iii) patients with insufficient data.
Drug: Neoadjuvant chemotherapy with radical tumor resection surgery
All patients were pathologically diagnosed as advanced gastric cancer, all receive neoadjuvant chemotherapy, after the completion of neoadjuvant chemotherapy, all patients receive radical tumor resection surgery (partial gastrectomy or total gastrectomy, as proper).

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Pathological Complete Response
Time Frame: Assessed within 30 days after radical resection surgery.
Pathological complete response (pCR) was defined as no viable cells remained in the primary tumor lesions and the dissected lymph nodes.
Assessed within 30 days after radical resection surgery.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sixth Affiliated Hospital, Sun Yat-sen University

Investigators

  • Principal Investigator: Junsheng Peng, MD, The Sixth Affiliated Hospital, Sun Yat-sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 1, 2013

Primary Completion (Actual)

September 30, 2022

Study Completion (Estimated)

December 30, 2026

Study Registration Dates

First Submitted

June 4, 2024

First Submitted That Met QC Criteria

June 8, 2024

First Posted (Actual)

June 11, 2024

Study Record Updates

Last Update Posted (Actual)

June 11, 2024

Last Update Submitted That Met QC Criteria

June 8, 2024

Last Verified

June 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • E2021088

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

The data that support the findings of this study are available from Dr. Junsheng Peng (E-mail: pengjsh@mail.sysu.edu.cn) upon reasonable request.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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