Construction and validation of a competing risk model for specific survival of patients with second primary malignancies after prostate cancer

Abstract

Objective To identify SPM death risk factors in PCa survivors and high-risk PCa patients for SPMs. With improved prostate cancer (PCa) survival, there's a growing need to study second primary malignancies (SPMs) in PCa survivors. Methods PCa patients from 2004–2015 in the SEER database were screened for SPM risk. The Fine and Gray competing risk model identified SPM mortality risk factors via univariate and multivariate analyses. A competing risk nomogram predicted 3-, 5-, and 10-year SPM mortality risk, stratifying patients by total scores for risk assessment. Model performance was assessed using the C-index, ROC curve, calibration curve, and AUC. Results SPM-diagnosed PCa patients (2004–2015) were split into a 7:3 training (n = 31,435) and validation set (n = 13,472). The nomogram included 12 factors: age, chemotherapy, radiation, Gleason Score, race, grade, marital status, tumor size, surgical site, surgery/radiation sequence, scope, and stage. C-index values were 0.70 (se: 0.001) and 0.684 (se: 0.002) in training and validation, respectively, indicating high discriminative power. The 3-, 5-, and 10-year AUCs in training were 0.75 (95% CI: 0.72–0.77), 0.73 (95% CI: 0.72–0.75), and 0.72 (95% CI: 0.7–0.73), and in validation were 0.7 (95% CI: 0.65–0.74), 0.7 (95% CI: 0.67–0.73), and 0.71 (95% CI: 0.69–0.73), respectively, showing good predictive accuracy. The calibration curve confirmed model fit. Conclusions A competing risk model predicts SPM mortality in PCa survivors, aiding high-risk patient identification and guiding survival-oriented treatment and follow-up strategies.