Development and Validation of Osteoporosis Risk-Assessment Model for Korean Men.
10.3349/ymj.2016.57.1.187
- Author:
Sun Min OH
1
;
Bo Mi SONG
;
Byung Ho NAM
;
Yumie RHEE
;
Seong Hwan MOON
;
Deog Young KIM
;
Dae Ryong KANG
;
Hyeon Chang KIM
Author Information
1. Cardiovascular and Metabolic Disease Etiology Research Center, Yonsei University College of Medicine, Seoul, Korea. hckim@yuhs.ac
- Publication Type:Original Article ; Research Support, Non-U.S. Gov't
- Keywords:
Osteoporosis;
risk assessment;
men;
Korea
- MeSH:
Aged;
Asian Continental Ancestry Group/*statistics & numerical data;
Bone Density;
Female;
Humans;
Male;
Middle Aged;
*Models, Biological;
Nutrition Surveys;
Osteoporosis/*diagnosis/ethnology;
Predictive Value of Tests;
Prevalence;
ROC Curve;
Reproducibility of Results;
Republic of Korea/epidemiology;
Risk Assessment/*methods;
Sensitivity and Specificity;
Surveys and Questionnaires/*standards
- From:Yonsei Medical Journal
2016;57(1):187-196
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: The aim of the present study was to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean men. MATERIALS AND METHODS: The study used data from 1340 and 1110 men > or =50 years who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score < or =-2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self-assessment Tool for Asian (OSTA) was compared with sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). A net reclassification improvement was further calculated to compare the developed Korean Osteoporosis Risk-Assessment Model for Men (KORAM-M) with OSTA. RESULTS: In the development dataset, the prevalence of osteoporosis was 8.1%. KORAM-M, consisting of age and body weight, had a sensitivity of 90.8%, a specificity of 42.4%, and an AUC of 0.666 with a cut-off score of -9. In the validation dataset, similar results were shown: sensitivity 87.9%, specificity 39.7%, and AUC 0.638. Additionally, risk categorization with KORAM-M showed improved reclassification over that of OSTA up to 22.8%. CONCLUSION: KORAM-M can be simply used as a pre-screening tool to identify candidates for dual energy X-ray absorptiometry tests.
