Multifactor nomogram predicts bone metastasis in patients initially diagnosed with prostate cancer

Objectives To explore the correlation between prostate-specific antigen density (PSAD), Cystatin C (CysC), systemic immune-inflammatory index (SII), and bone metastasis in initially diagnosed prostate cancer patients, and to develop a predictive nomogram model. Methods A retrospective analysis was conducted on 208 newly diagnosed prostate cancer patients, divided into a modeling group (146 cases) and a validation group (62 cases). Logistic regression analyses identified independent risk factors for bone metastasis, which were used to construct a nomogram. Model accuracy was assessed using AUC and calibration curves. Results Gleason score (GLS), PSAD, CysC, fibrinogen (FIB), SII, and pelvic lymph node metastasis were identified as independent risk factors for bone metastasis (OR > 1, P  < 0.05). The model showed an AUC of 0.897 (95% CI : 0.845–0.948) in the modeling group and 0.840 (95% CI : 0.741–0.940) in the validation group. Conclusion PSAD, CysC, SII, FIB, GLS, and pelvic lymph node metastasis are significant risk factors for bone metastasis in newly diagnosed prostate cancer patients. The nomogram model can assist in clinical diagnosis, especially in hospitals lacking bone scanning equipment. This study aimed to explore the clinical correlation among PSAD, CysC, SII, and bone metastasis in initial prostate cancer patients. Additionally, a nomogram incorporating relevant risk factors was developed.