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Related Concept Videos

Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
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Models of Health Promotion and Illness Prevention I

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Related Experiment Videos

Predictions in an illness-death model.

Célia Touraine1, Catherine Helmer2, Pierre Joly2

  • 1ISPED, University of Bordeaux, INSERM U-897-Epidemiologie-Biostatistique, Bordeaux, France celia.touraine@isped.u-bordeaux2.fr.

Statistical Methods in Medical Research
|May 24, 2013
PubMed
Summary
This summary is machine-generated.

This study reviews and proposes methods for estimating key quantities in multi-state models, beyond transition intensities. It enhances clinical and epidemiological insights using illness-death models with real-world data.

Keywords:
Illness-death modelinterval-censored datalife expectancieslifetime riskpredictionstransition probabilities

Related Experiment Videos

Area of Science:

  • Biostatistics
  • Epidemiology
  • Survival Analysis

Background:

  • Multi-state models are crucial for analyzing transitions between health states over time.
  • Current methods often focus on transition intensities and regression parameters.
  • Clinical and epidemiological questions may require estimating other relevant quantities.

Purpose of the Study:

  • To review various quantities beyond transition intensities in multi-state models.
  • To propose estimation methods for these quantities, particularly within illness-death models.
  • To provide practical applications using real-world interval-censored data.

Main Methods:

  • Review of established and novel estimation techniques for multi-state models.
  • Focus on illness-death models, a common framework in medical research.
  • Application of methods to interval-censored data from a cognitive ageing cohort study.

Main Results:

  • Identified and reviewed a comprehensive set of clinically relevant quantities.
  • Proposed a unified approach for estimating transition probabilities, cumulative probabilities, and life expectancies.
  • Demonstrated the utility of the proposed methods with a practical example.

Conclusions:

  • Estimating quantities beyond transition intensities provides richer insights in multi-state models.
  • The proposed methods enhance the applicability of illness-death models in clinical and epidemiological research.
  • The approach is effective for analyzing complex, real-world health data.