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

To identify second primary malignancies (SPMs) death risk factors in prostate cancer (PCa) survivors and high-risk PCa patients for SPMs. With improved PCa survival, there's a growing need to study second SPMs in PCa survivors. PCa patients from 2004 to 2015 in the surveillance, epidemiology, and end results 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 correlation index, receiver operating characteristic curve, calibration curve, and area under the curve. 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 area under the curves in training were 0.75 (95% confidence interval (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. A competing risk model predicts SPM mortality in PCa survivors, aiding high-risk patient identification and guiding survival-oriented treatment and follow-up strategies.