Background/purpose: Osteoporosis has been linked to an increased fracture risk and subsequent mortality in the later life. Previous prediction models have focused on osteoporosis in postmenopausal women; however, a prediction tool for osteopenia is needed. Our objective was to establish a prediction model for osteopenia risk in women aged 40-55 years.
Methods: This was a cross-sectional study. A total of 1350 Taiwanese women aged 40-55 years were recruited from a health checkup center from 2009 to 2010. The main outcome measure was osteopenia (-1≥bone mineral density T-score > -2.5).
Results: The Osteoporosis Preclinical Assessment Tool (OPAT) developed in this study was based on variables with biological importance to osteopenia and variables that remained significant (p<0.05) in the multivariable analysis, which include age, menopausal status, weight, and alkaline phosphatase level. The OPAT has a total score that ranges from 0 to 7, and categorizes women into high-, moderate-, and low-risk groups. The predictive ability of the OPAT (area under the receiver operating characteristic curve=0.77) was significantly better than that of the Osteoporosis Self-assessment Tool for Asians (area under the receiver operating characteristic curve=0.69). The inclusion of serum total alkaline phosphatase level in the model, which is easy to obtain from routine health checkups, significantly enhanced the sensitivity (McNemar test, p=0.004) for detecting osteopenia in women aged 40-55 years.
Conclusion: Our findings provide an important tool for identifying women at risk of osteoporosis at the preclinical phase.
Keywords: osteopenia; osteoporosis; prediction model; women.
Copyright © 2017. Published by Elsevier B.V.