Development and Application of Chronic Disease Risk Prediction Models.
10.3349/ymj.2014.55.4.853
- Author:
Sun Min OH
1
;
Katherine M STEFANI
;
Hyeon Chang KIM
Author Information
1. Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea. hckim@yuhs.ac
- Publication Type:Review ; Research Support, Non-U.S. Gov't
- Keywords:
Non-communicable diseases;
chronic diseases;
risk prediction;
disease prediction;
health risk appraisal;
Korea
- MeSH:
Cardiovascular Diseases/epidemiology;
Chronic Disease/*epidemiology;
Communicable Diseases/*epidemiology;
Humans;
Korea/epidemiology;
*Models, Theoretical;
Risk Factors
- From:Yonsei Medical Journal
2014;55(4):853-860
- CountryRepublic of Korea
- Language:English
-
Abstract:
Currently, non-communicable chronic diseases are a major cause of morbidity and mortality worldwide, and a large proportion of chronic diseases are preventable through risk factor management. However, the prevention efficacy at the individual level is not yet satisfactory. Chronic disease prediction models have been developed to assist physicians and individuals in clinical decision-making. A chronic disease prediction model assesses multiple risk factors together and estimates an absolute disease risk for the individual. Accurate prediction of an individual's future risk for a certain disease enables the comparison of benefits and risks of treatment, the costs of alternative prevention strategies, and selection of the most efficient strategy for the individual. A large number of chronic disease prediction models, especially targeting cardiovascular diseases and cancers, have been suggested, and some of them have been adopted in the clinical practice guidelines and recommendations of many countries. Although few chronic disease prediction tools have been suggested in the Korean population, their clinical utility is not as high as expected. This article reviews methodologies that are commonly used for developing and evaluating a chronic disease prediction model and discusses the current status of chronic disease prediction in Korea.
