title: Comparison of different screening tools (FRAX®, OST, ORAI, OSIRIS, SCORE and age alone) to identify women with increased risk of fracture. A population-based prospective study.
abstract: OBJECTIVE
  To compare the power of FRAX® without bone mineral density (BMD) and simpler screening tools (OST, ORAI, OSIRIS, SCORE and age alone) in predicting fractures.
  
  
  METHODS
  This study was a prospective, population-based study performed in Denmark comprising 3614 women aged 40-90 years, who returned a questionnaire concerning items on risk factors for osteoporosis. Fracture risk was calculated using the different screening tools (FRAX®, OST, ORAI, OSIRIS and SCORE) for each woman. The women were followed using the Danish National Register registering new major osteoporotic fractures during 3 years, counting only the first fracture per person. Area under the receiver operating characteristic curve (ROC) and statistics and Harrell's index were calculated. Agreement between the tools was calculated by kappa statistics.
  
  
  RESULTS
  A total of 4% of the women experienced a new major osteoporotic fracture during the follow-up period. There were no differences in the area under the curve (AUC) values between FRAX® and the simpler tools; AUC values between 0.703 and 0.722 (p = 0.86). Also, Harrell's C values were very similar between the tools. Agreement between the tools was modest.
  
  
  CONCLUSIONS
  During 3 years follow-up FRAX® did not perform better in the fracture risk prediction compared with simpler tools such as OST, ORAI, OSIRIS, SCORE or age alone in a screening scenario where BMD was not measured. These findings suggest that simpler models based on fewer risk factors, which would be easier to use in clinical practice by the GP or the patient herself, could just as well as FRAX® be used to identify women with increased risk of fracture.
  
  
  CONCLUSIONS
  Comparison of FRAX® and simpler screening tools (OST, ORAI, OSIRIS, SCORE) in predicting fractures indicate that FRAX® did not perform better in fracture risk prediction compared with the simpler tools or even age alone in a screening scenario without bone mineral density assessment.
authors.affiliation: Institute of Clinical Research, University of Southern Denmark, Denmark. Krubin@health.sdu.dk
authors.forename: Katrine Hass
authors.initials: KH
authors.lastname: Rubin
authors.forename: Bo
authors.initials: B
authors.lastname: Abrahamsen
authors.forename: Teresa
authors.initials: T
authors.lastname: Friis-Holmberg
authors.forename: Jacob V B
authors.initials: JV
authors.lastname: Hjelmborg
authors.forename: Mickael
authors.initials: M
authors.lastname: Bech
authors.forename: Anne Pernille
authors.initials: AP
authors.lastname: Hermann
authors.forename: Reinhard
authors.initials: R
authors.lastname: Barkmann
authors.forename: Claus C
authors.initials: CC
authors.lastname: Glüer
authors.forename: Kim
authors.initials: K
authors.lastname: Brixen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology*; D019540:Area Under Curve; D003718:Denmark / Q000453:epidemiology; D005260:Female; D050723:Fractures, Bone / Q000453:epidemiology*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008875:Middle Aged; D058866:Osteoporotic Fractures / Q000453:epidemiology*; D015995:Prevalence; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors
keywords: Epidemiology; Fracture; Prediction; Risk factors; Screening tools