Description

Richy et al developed the ORACLE (Osteoporosis Risk Assessment by Composite Linear Estimate) for identifying postmenopausal women at risk for osteoporosis. This can help identify women who may benefit from additional evaluation for osteoporosis. The authors are from the Universite de Liege in Belgium.


 

Patient selection: postmenopausal women > 45 years of age

 

Parameters:

(1) ultrasonometric bone profile index (UBPI), determined using the quantitative ultrasonometric (QUS) instrument from IGEA (www.igea.it)

(2) age

(3) body mass index (BMI)

(4) hormone replacement therapy

(5) history of fractures after 45 years of age

Parameter

Finding

Points

hormone replacement therapy

no

0

 

yes

1

history of fractures after 45 years

no

0

 

yes

1

 

X =

= (0.02 * (age in years)) - (3 * (UBPI)) - (0.13 * (BMI)) - (0.39 * (points for hormone replacement therapy)) + (0.74 * (history of fracture))

 

ORACLE =

= (-1) / X

 

Interpretation:

• Values in the study population ranged from 0.15 to 1.42.

• A cutoff >= 0.27 or >= 0.33 can be used to identify women who are increased risk for osteoporosis.

 

Performance:

• A cutoff of 0.27 gave a sensitivity of 90% and specificity of 50%. The positive predictive value was 83% and negative predictive value 52%.

• A cutoff of 0.33 gave a sensitivity of 76% and specificity of 76%. The positive predictive value was 88% and negative predictive value 54%.

• Neither of these are particularly exciting, but they were better than other approaches the authors tested (Figures 1 and 2, page 1407).

 

Limitations:

• The ultrasonometric bone profile index (UBPI) is derived based on graphic traces specific to the QUS instrument (DBMSonic 1200, IGEA, Carpi, Italy).

 


To read more or access our algorithms and calculators, please log in or register.