Analyzing the timing of disease onset in cohort studies
Official title: Semiparametric Regression Analysis of Interval-Censored Data in Current Cohort Studies
Funded at University of Michigan at Ann Arbor · NIH-11051189 · Data updated 2026-11-12
This study is looking at new ways to understand how diseases like diabetes and cancer develop over time when we can't pinpoint exactly when they start, so we can help improve health outcomes for people at risk.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | March 10, 2024 |
| Project end | February 29, 2028 |
| Funding year | 2025 |
| Award (this year) | $377,809 |
| NIH project number | 5R01HL173128-02 |
| Project ID | NIH-11051189 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals who are part of cohort studies and are at risk for diseases such as diabetes, hypertension, or cancer.
✕Less likely to help
Patients with well-defined disease onset or those not participating in cohort studies may not benefit from this research.
What this research studies
This research focuses on developing advanced statistical models to analyze data from cohort studies where the onset of diseases like diabetes or cancer cannot be pinpointed exactly but is known to occur between two medical examinations. By creating semiparametric regression models, the research aims to better understand how these diseases progress over time and their impact on future health outcomes. The study will also explore methods to validate these models and improve the accuracy of data analysis in epidemiological research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of disease onset and progression, ultimately improving patient care and treatment strategies.
How similar studies have gone: Previous research has shown promise in using advanced statistical methods for analyzing interval-censored data, indicating that this approach could yield valuable insights.
Where this research is happening
-
University of Michigan at Ann Arbor
Ann Arbor, United States Active
Researchers
- Principal investigator: Zeng, Donglin — University of Michigan at Ann Arbor
- Study coordinator: Zeng, Donglin
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.