A European multicenter comparison of quantitative ultrasound measurement variables: the OPUS study

Quantitative ultrasound (QUS) measurement variables vary between European countries in a different way to hip bone mineral density. Standardization of data can be achieved through statistical approaches to reduce any between-center differences in QUS measurement variables. However, further validation of this method is required before it can be widely applied.

European between-center differences in hip bone mineral density (BMD) have been shown to exist; however, little is known about the geographical heterogeneity of QUS measurement variables. We aimed to examine the differences in QUS variables between three different European countries.

Five calcaneal and phalangeal QUS devices in Sheffield, Aberdeen (UK), Kiel and Berlin (Germany), and three devices in Paris (France) were used to measure QUS variables in younger (n = 463, 20-39 years old) and older (n = 2,399, 55-79 years old) women participating in the European multicenter Osteoporosis and Ultrasound (OPUS) study. Broadband ultrasound attenuation, speed of sound, stiffness index, amplitude-dependent speed of sound, bone transmission time, and ultrasonic bone profiler index data were collected. Between-center differences were examined using ANOVA followed by post hoc Fisher's least significant difference tests, and ANCOVA with linear contrasts. p < 0.05 indicated statistical significance.

Between-center differences in nonstandardized QUS measurement variables existed for younger (p = 0.0023 to p < 0.0001) and older women (p < 0.001). Anthropometric characteristics exerted a significant influence on nonstandardized data (p = 0.045 to p < 0.001). However, following statistical standardization, based on height and weight or based on measurements made in young people, geographical heterogeneity in QUS measurement variables was no longer apparent.

QUS measurement variables vary between European countries in a different way to those for hip BMD. Standardization of data can be achieved through statistical approaches to reduce any between-center differences in QUS measurement variables. However, further validation of this method is required before it can be widely applied.