Validation of Three Tools for Estimating the Risk of Primary Osteoporosis in an Elderly Male Population in Beijing

The Significance of Combined OSTA, HU Value and VBQ Score in Osteoporosis Screening Before Spinal Surgery

OBJECTIVE

This study aimed to assess the utility of a combined assessment using the Osteoporosis Self-Assessment Tool for Asians (OSTA), Hounsfield unit (HU) value, and vertebral bone quality (VBQ) score for preoperative osteoporosis (OP) screening in patients scheduled for spinal surgery.

METHODS

This study encompassed 288 participants, including 128 males and 160 females. Patients were stratified into 2 groups: the OP group (T-score ≤ -2.5) and the non-OP group (T-score > -2.5), determined by dual-energy X-ray absorptiometry (DEXA). Binary logistic regression was used to construct a combined diagnostic model, and the receiver operating characteristic (ROC) curve evaluated the sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of these metrics individually or in combination to screen for OP.

RESULTS

Osteoporosis patients exhibited significantly lower OSTA and HU values in comparison to non-OP patients, while their VBQ scores were significantly higher (P < 0.001). The ROC curve analysis results indicated that within the male group, the combined diagnosis had a sensitivity of 93.8%, specificity of 82.3%, accuracy of 85.2%, PPV of 63.8%, and NPV of 97.5%. In the female group, the combined diagnosis had a sensitivity of 93.9%, specificity of 87.4%, accuracy of 90.0%, PPV of 83.6%, and NPV of 95.4%.

CONCLUSIONS

The combined use of OSTA, HU values, and VBQ scores in preoperative OP screening for spinal surgery demonstrates significantly higher accuracy and superior screening value compared to individual assessments. These results establish a robust scientific foundation for conducting preoperative OP screening in patients undergoing spinal surgery.

Construction of a predictive model for osteoporosis risk in men: using the IOF 1-min osteoporosis test

OBJECTIVE

To construct a clinical prediction nomogram model using the 1-min IOF osteoporosis risk test as an evaluation tool for male osteoporosis.

METHODS

The 1-min test results and the incidence of osteoporosis were collected from 354 patients in the osteoporotic clinic of our hospital. LASSO regression model and multi-factor logistic regression were used to analyze the risk factors of osteoporosis in patients, and the risk prediction model of osteoporosis was established. Verify with an additional 140 objects.

RESULTS

We used logistic regression to construct a nomogram model. According to the model, the AUC value of the training set was 0.760 (0.704-0.817). The validation set has an AUC value of 0.806 (0.733-0.879). The test set AUC value is 0.714 (0.609-0.818). The calibration curve shows that its advantage is that the deviation correction curve of the nomogram model can maintain a good consistency with the ideal curve. In terms of clinical applicability, compared with the "total intervention" and "no intervention" schemes, the clinical net return rate of the nomogram model showed certain advantages.

CONCLUSION

Using the 1-min osteoporosis risk test provided by IOF, we built a male osteoporosis risk prediction model with good prediction effect, which can provide greater reference and help for clinicians.