Abstract
Background and Objectives: To assess the risk of osteoporotic fractures in patients with rheumatic diseases (RDs), we introduced a new approach for predicting incident osteoporotic fractures (OF), employing a risk-weight calculation for each candidate risk factor. Materials and Methods: RD outpatients were picked up, and their histories, including OFs, were studied. A Cox regression analysis that evaluated candidate risk factors was conducted with a multivariate model. The variants were selected as candidate risk factors that showed statistical significance using a univariate model. Using the risk ratio or the β-value and p-value, different approaches to acquire a total risk weight (TRW) for each patient were determined to compare the sensitivity and specificity among the approach methods. The cut-off index (COI) was determined using receiver operating characteristic analysis. Sensitivity and specificity for incident OFs were determined using the Kaplan–Meier survival analysis. Results: In a total of 1228 patients, incidental OF occurred in 179 (14.58%) who were included. Factors with significantly higher risk ratios were a history of vertebral and non-vertebral fractures (p < 0.001), cognitive impairment (p < 0.001), anti-osteoporosis drug intervention (p < 0.001), and rehabilitation (p < 0.001). The excellent approach to acquire the best sensitivity and specificity was to calculate the β-value multiplied by the logarithm of the p-value based on 0.05, including non-significant factors (sensitivity: 31.2%, specificity: 94.9%, and area under the curve (AUC): 0.774) compared to 29.4%, 91.6%, and 0.723, respectively, with a counted significant risk factors approach. Conclusions: This novel approach, which includes non-significant factors, can achieve a more accurate sensitivity and specificity to accidental OF in patients with RDs.
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