Internal validation of an 11-yr prediction model for new vertebral fractures using the vertebral bone quality score: a prospective cohort study.

The vertebral bone quality score is used to assess bone quality using magnetic resonance imaging. This study aimed to perform internal validation of a previously developed prediction model for the occurrence of new vertebral fractures (NVFs) over 11 yrs using the vertebral bone quality score. A prospective cohort of 157 participants from the Minami-Aizu study, with lumbar magnetic resonance imaging follow-ups over 11 yrs, was analyzed from an initial 200-participant cohort, applying the exclusion criteria. The primary outcome was the presence or absence of NVFs over 11 yrs. The predictors included age, sex, existing vertebral fractures at baseline, and VBQ scores. The prediction model, constructed using multiple logistic regression analysis and the Akaike information criterion, was evaluated for its discrimination power using the receiver operating characteristic curve and area under the curve (AUC). Internal validation was performed using the bootstrapping method with model reconstruction through regularization to correct for overfitting. In the multiple logistic regression analysis, predictors with a