Large Cohort Data Based Cost-Effective Disease Prevention Design Strategy: Strong Heart Study

Area of Science:

• Epidemiology
• Public Health
• Biostatistics

Background:

• Large cohort studies generate extensive data on chronic disease incidence and risk factors.
• Current methods for utilizing this data to inform clinical disease prevention are underdeveloped.
• Translating epidemiological findings into practical, cost-effective prevention strategies is a significant challenge.

Purpose of the Study:

• To propose a novel conceptual strategy for cost-effective disease prevention design.
• To address the challenge of intervening in large target groups when universal intervention is unaffordable.
• To provide a framework for translating large cohort study results into clinical practice.

Main Methods:

• Utilized data from the Strong Heart Study, including a diabetes risk prediction model.
• Employed a utility function and regression models to develop the strategy.
• Illustrated the application of the strategy using diabetes prevention as an example.

Main Results:

• A conceptual cost-effective disease prevention design strategy was initiated.
• The strategy was demonstrated through an application to diabetes prevention.
• The approach aims to optimize intervention by identifying high-risk individuals.

Conclusions:

• The proposed strategy offers solutions for cost-effective prevention design, considering complex risk factor associations.
• It facilitates the selection of high-risk individuals, accommodates individual health differences, and sets adaptive intervention goals.
• The strategy and methods are adaptable for preventing other diseases and bridging epidemiological research with clinical application.