title: Development of a Korean Fracture Risk Score (KFRS) for Predicting Osteoporotic Fracture Risk: Analysis of Data from the Korean National Health Insurance Service.
abstract: BACKGROUND
  Asian-specific prediction models for estimating individual risk of osteoporotic fractures are rare. We developed a Korean fracture risk prediction model using clinical risk factors and assessed validity of the final model.
  
  
  METHODS
  A total of 718,306 Korean men and women aged 50-90 years were followed for 7 years in a national system-based cohort study. In total, 50% of the subjects were assigned randomly to the development dataset and 50% were assigned to the validation dataset. Clinical risk factors for osteoporotic fracture were assessed at the biennial health check. Data on osteoporotic fractures during the follow-up period were identified by ICD-10 codes and the nationwide database of the National Health Insurance Service (NHIS).
  
  
  RESULTS
  During the follow-up period, 19,840 osteoporotic fractures were reported (4,889 in men and 14,951 in women) in the development dataset. The assessment tool called the Korean Fracture Risk Score (KFRS) is comprised of a set of nine variables, including age, body mass index, recent fragility fracture, current smoking, high alcohol intake, lack of regular exercise, recent use of oral glucocorticoid, rheumatoid arthritis, and other causes of secondary osteoporosis. The KFRS predicted osteoporotic fractures over the 7 years. This score was validated using an independent dataset. A close relationship with overall fracture rate was observed when we compared the mean predicted scores after applying the KFRS with the observed risks after 7 years within each 10th of predicted risk.
  
  
  CONCLUSIONS
  We developed a Korean specific prediction model for osteoporotic fractures. The KFRS was able to predict risk of fracture in the primary population without bone mineral density testing and is therefore suitable for use in both clinical setting and self-assessment. The website is available at http://www.nhis.or.kr.
authors.affiliation: Department of Internal Medicine, Wonkwang University Sanbon Hospital, Gunpo, Republic of Korea.
authors.forename: Ha Young
authors.identifier: http://orcid.org/0000-0002-0651-2213
authors.initials: HY
authors.lastname: Kim
authors.affiliation: Department of information Statistics, Andong National University, Andong, South Korea.
authors.forename: Eun Jin
authors.initials: EJ
authors.lastname: Jang
authors.affiliation: Department of Statistics, Kyungpook National University, Daegu, South Korea.
authors.forename: ByeongJu
authors.initials: B
authors.lastname: Park
authors.affiliation: Department of Orthopaedic Surgery, School of Medicine, Hallym University, Anyang, Korea.
authors.forename: Tae-Young
authors.initials: TY
authors.lastname: Kim
authors.affiliation: Big Data Steering Department, National Health Insurance Service, Seoul, Korea.
authors.forename: Soon-Ae
authors.initials: SA
authors.lastname: Shin
authors.affiliation: Department of Orthopaedic Surgery, Chung-Ang University College of Medicine, Seoul, South Korea.
authors.forename: Yong-Chan
authors.initials: YC
authors.lastname: Ha
authors.affiliation: College of Pharmacy, Gachon University, Incheon, Korea.
authors.forename: Sunmee
authors.initials: S
authors.lastname: Jang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D016208:Databases, Factual; D005260:Female; D006801:Humans; D015994:Incidence; D007348:Insurance, Health; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D058866:Osteoporotic Fractures / Q000453:epidemiology*; D056910:Republic of Korea / Q000453:epidemiology; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors