Table 2.
Performance of LS-BSI to predict vertebral fractures in logistic regression models adjusted for different covariates
| Model | R 2 | LS-BSI ≥ 2.2 adjusted OR; 95% CI (P value) | Adjustments | AUC (95% CI); P value |
|---|---|---|---|---|
| # 1 | 0.243 | 6.887 (1.628-29.138); P = 0.009 | Sex, Age | 0.768 (0.597-0.938); P = 0.019 |
| # 2 | 0.270 | 7.709 (1.752-33.924); P = 0.007 | Sex, Age, BMI | 0.795 (0.618-0.972); P = 0.009 |
| # 3 | 0.376 | 9.602 (1.251-73.696); P = 0.030 | Sex, Age, BMI, CTX, P1NP | 0.825 (0.666-0.984); P = 0.004 |
| # 4 | 0.189 | 5.739 (1.244-26.481); P = 0.025 | TBS | 0.735 (0.535-0.935); P = 0.039 |
| # 5 | 0.251 | 7.152 (1.355-37.755); P = 0.020 | TBS, Sex, Age, BMI | 0.795 (0.616-0.974); P = 0.009 |
| # 6 | 0.388 | 15.120 (1.059-215.786); P = 0.045 | TBS, Sex, Age, BMI, CTX, P1NP | 0.830 (0.676-0.984); P = 0.004 |
Abbreviations: AUC, area under the receiver operating characteristics curve; BMI, body mass index (kg/m2); CTX, collagen telepeptide (ng/mL); LS-BSI, lumbar spine bone strain index; P1NP, aminoterminal propeptide (ng/mL); TBS, trabecular bone score.