Predicting the risk of type 1 diabetes using advanced statistical models

Dynamic prediction of type 1 diabetes risk and autoantibody status by a joint model of longitudinal and multistate models

NIH-funded research University of South Florida · NIH-10903719

This study is working on a smart way to predict who might develop type 1 diabetes by looking at certain health markers over time, so that people at risk can be identified and helped earlier.

Quick facts

Grant typeR03 grant
Study typeNIH-funded research
Funding institutionUniversity of South Florida NIH-funded
Lab location1 site (Tampa, United States)
Project IDNIH-10903719 on NIH RePORTER

What this research studies

This research aims to develop a sophisticated statistical model that predicts the risk of developing type 1 diabetes by analyzing autoantibody status and other relevant health markers over time. By continuously monitoring these factors, the model seeks to provide dynamic predictions tailored to individual patients. The research utilizes data from the Environmental Determinants of Diabetes in the Young (TEDDY) study, employing advanced statistical methodologies to enhance the accuracy of predictions. This approach could lead to earlier identification and intervention for those at risk of type 1 diabetes.

Who could benefit from this research

Good fit: Ideal candidates for this research include children and young individuals aged 0-21 who may be at risk for developing type 1 diabetes.

Not a fit: Patients who are already diagnosed with type 1 diabetes or those outside the age range of 0-21 may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could enable earlier diagnosis and personalized management strategies for individuals at risk of type 1 diabetes.

How similar studies have performed: Other research has shown promise in using statistical models for predicting diabetes risk, indicating that this approach has potential for success.

Where this research is happening

Tampa, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.