Construction and application of models for the efficacy of NVBG
To determine who is suitable for hip preservation with NVBG, we constructed predictive models for the efficacy of NVBG. The hips were randomly divided into a training cohort (n = 130) and a validation cohort (n = 52) at a ratio of 7:3 using computer-generated random numbers to ensure that there was no overlap of hips in the two datasets. In the training cohort, clinical data were analyzed by univariate and multivariate analyses to screen for clinical predictors. The least absolute shrinkage and selection operator (LASSO) method was used to select the most useful radiomics features for prediction, and the radiomics score (Rad-scores) was calculated for each patient through a linear combination of selected features weighted according to their respective coefficients.Three models were constructed in the training cohort based on the extracted features: the Clinical model, Radiomics model, and C-R model based on the combination of clinical predictors and Rad-scores. The predictive performance of the three models was evaluated and validated in both cohorts through the receiver operating characteristic curve (ROC), area under curve (AUC), and DeLong test to compare the AUCs. The predictive performance of each model was assessed based on AUC, sensitivity, and specificity, while the goodness of fit of each model was evaluated using a calibration curve with Hosmer-Lemeshow test. To provide clinicians with a quantitative approach for assessing the efficacy of NVBG, we visualized the optimal model by constructing a nomogram and estimated the clinical utility using Decision Curve Analysis (DCA). DCA was performed by calculating the net benefits for a range of threshold probabilities in both the training and validation cohorts.