Simple clinical predictors for making directive decisions in osteoporosis screening for women: a cross-sectional study
Abstract
Osteoporosis screening strategies vary according to a country’s policies. Simple and highly accurate diagnostic predictors should be developed and utilized. This cross-sectional study aimed to determine the diagnostic performances of weight, body mass index (BMI), and age for osteoporosis. Moreover, this study proposes and validates new cutoff values for these indicators. Women aged 50 years or older who underwent Dual-energy x-ray absorptiometry (DXA) and did not receive any treatment for osteoporosis were enrolled. Age, weight, and BMI were used to analyze the diagnostic models. New cutoff values were proposed using the maximum Youden index value. A total of 1598 women were classified into normal bone mineral density, osteopenia, and osteoporosis groups. The mean age, weight, and BMI were 73.2 years, 53.6 kg, and 23.2 kg/m2, respectively, in the osteoporosis group, which significantly differed from those of the other groups. The new cutoff values for diagnosing osteoporosis at any site were 57.4 kg for weight, 23.8 kg/m2 for BMI, and 72 years for age. The area under the receiver operating characteristic curve (AUC) for weight < 57.4 kg, BMI < 23.8 kg/m2, and age ≥ 72 years cutoff values were 0.664, 0.633, and 0.558, respectively. The weight cutoff value yielded a significantly higher AUC than the BMI and age cutoff values (P = 0.002 and P < 0.001, respectively). This study proposes new cutoff values for simple clinical predictors to facilitate directive decision-making in…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 1,598 participants or records.
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