Reference : Development and validation of the ORACLE score to predict risk of osteoporosis
Scientific journals : Article
Human health sciences : General & internal medicine
http://hdl.handle.net/2268/26322
Development and validation of the ORACLE score to predict risk of osteoporosis
English
Richy, F. [> > > >]
Deceulaer, F. [> > > >]
Ethgen, Olivier mailto [Université de Liège - ULg > Département des sciences de la santé publique > Santé publique : aspects spécifiques >]
Bruyère, Olivier mailto [Université de Liège - ULg > Département des sciences de la santé publique > Epidémiologie et santé publique >]
Reginster, Jean-Yves mailto [Université de Liège - ULg > Département des sciences de la santé publique > Epidémiologie et santé publique >]
Nov-2004
Mayo Clinic Proceedings
Mayo Clinic Proceedings
79
11
1402-1408
Yes (verified by ORBi)
International
0025-6196
Rochester
[en] 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. SUBJECTS AND 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). CONCLUSION: 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.
http://hdl.handle.net/2268/26322

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Restricted access
Development and validation of the ORACLE score to predict risk of osteoporosis.pdfPublisher postprint69 kBRequest copy

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.