Development and Validation of a Digital Twin-based Clinical Research System (X Town Stage I)

Chronic diseases, characterized by their prolonged duration and slow progression, have emerged as predominant contributors to global morbidity and mortality. The investigators have developed a digital twin-based clinical research system (termed X Town) for chronic diseases, to predict clinical outcomes under various interventions. In this study, the investigators aim to evaluate the reliability of the developed digital twin-based clinical research system in predicting short-term clinical outcomes via virtual and real-world clinical studies.

Study Overview

• Status: Recruiting
• Conditions: Chronic Disease

• Study Type: Observational
• Enrollment (Estimated): 1500

Contacts and Locations

• Study Contact: Name: Huating Li, MD, PhD; Phone Number: +86-17749716891; Email: huarting99@sjtu.edu.cn

Study Locations

• China
  • Jiangsu
    • Wuxi, Jiangsu, China
      • Recruiting
      • Shanghai Health and Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

We will mainly include participants at high-risk of or with chronic diseases.

Description

Inclusion Criteria:

1. Age≥18 years old
2. Receiving care at a community health service centre
3. Able to understand and comply with the study procedures
4. Agrees to participate in the study and signs the informed consent form

Exclusion Criteria:

1. Patients with severe mental illness
2. Patients expected to be unable to complete follow-ups

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Virtual clinical studies
Real-world clinical studies

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The agreement between the simulated short-term clinical outcomes in the virtual clinical studies and the real-world short-term clinical outcomes in the real-world clinical studies	We will use three predefined binary metrics to evaluate the agreement: (1) full statistical significance agreement, defined by effect estimates and CIs of the virtual and real-world clinical studies on the same side of the null; (2) estimate agreement, defined by whether effect estimates for the virtual clinical studies fell within the 95% CI for the real-world clinical study results; (3) standardized difference agreement between treatment effect estimates from the real-world clinical studies and the virtual clinical studies, defined by standardized differences (Reference: JAMA. 2023;329(16):1376-1385. doi:10.1001/jama.2023.4221).	Within 3 months

Collaborators and Investigators

• Sponsor: Shanghai 6th People's Hospital
• Collaborators: Shanghai Jiao Tong University School of Medicine; Tsinghua University

Study record dates

Study Major Dates

• Study Start (Actual): April 13, 2025
• Primary Completion (Estimated): July 10, 2025
• Study Completion (Estimated): August 10, 2025

Study Registration Dates

• First Submitted: February 18, 2025
• First Submitted That Met QC Criteria: February 28, 2025
• First Posted (Actual): March 6, 2025

Study Record Updates

• Last Update Posted (Actual): May 15, 2025
• Last Update Submitted That Met QC Criteria: May 14, 2025
• Last Verified: February 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Disease Attributes; Chronic Disease
• Other Study ID Numbers: 2025-KY-025(K)

Drug and device information, study documents

• product manufactured in and exported from the U.S.: No