title: Development and validation of the ORACLE score to predict risk of osteoporosis.
abstract: OBJECTIVE
  To develop and validate a composite index, the Osteoporosis Risk Assessment by Composite Linear Estimate (ORACLE), that includes risk factors and ultrasonometric outcomes to screen for osteoporosis.
  
  
  METHODS
  Two cohorts of postmenopausal women aged 45 years and older participated in the development (n = 407) and the validation (n = 202) of ORACLE. Their bone mineral density was determined by dual energy x-ray absorptiometry and quantitative ultrasonometry (QUS), and their historical and clinical risk factors were assessed (January to June 2003). Logistic regression analysis was used to select significant predictors of bone mineral density, whereas receiver operating characteristic (ROC) analysis was used to assess the discriminatory performance of ORACLE.
  
  
  RESULTS
  The final logistic regression model retained 4 biometric or historical variables and 1 ultrasonometric outcome. The ROC areas under the curves (AUCs) for ORACLE were 84% for the prediction of osteoporosis and 78% for low bone mass. A sensitivity of 90% corresponded to a specificity of 50% for identification of women at risk of developing osteoporosis. The corresponding positive and negative predictive values were 86% and 54%, respectively, in the development cohort. In the validation cohort, the AUCs for identification of osteoporosis and low bone mass were 81% and 76% for ORACLE, 69% and 64% for QUS T score, 71% and 68% for QUS ultrasonometric bone profile index, and 76% and 75% for Osteoporosis Self-assessment Tool, respectively. ORACLE had the best discriminatory performance in identifying osteoporosis compared with the other approaches (P < .05).
  
  
  CONCLUSIONS
  ORACLE exhibited the highest discriminatory properties compared with ultrasonography alone or other previously validated risk indices. It may be helpful to enhance the predictive value of QUS.
authors.affiliation: Department of Public Health, Epidemiology and Health Economics, Université de Liège, Liège, Belgium. florent.richy@ulg.ac.be
authors.forename: Florent
authors.initials: F
authors.lastname: Richy
authors.forename: Fréderic
authors.initials: F
authors.lastname: Deceulaer
authors.forename: Olivier
authors.initials: O
authors.lastname: Ethgen
authors.forename: Olivier
authors.initials: O
authors.lastname: Bruyère
authors.forename: Jean-Yves
authors.initials: JY
authors.lastname: Reginster
mesh_terms: D015502:Absorptiometry, Photon; D000368:Aged; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D015663:Osteoporosis, Postmenopausal / Q000175:diagnosis* / Q000000981:diagnostic imaging; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D014463:Ultrasonography