In summary, the SHAP-based interpretability analysis not only confirmed the critical role of PSMA-avid tumor burden-related parameters in predicting prostate cancer metastasis but also highlighted the potential of the XGBoost model in providing individualized risk assessments. This evidence concerns the gene FOLH1 and prostate carcinoma.