Suicide risk in prostate cancer patients: Trends, predictors, and development of predictive nomograms using SEER data

Purpose

To assess suicide risk in prostate cancer (PCa) patients by analyzing trends, key predictors, and developing predictive tools. Using the Surveillance, Epidemiology, and End Results (SEER) database data, we aimed to identify high-risk populations and guide strategies to reduce suicide-related mortality.

Methods

A retrospective analysis was conducted using SEER data from 2010 to 2020. Standardized mortality ratios (SMRs) were calculated to compare suicide risk in PCa patients with that of the general male population, with subgroup analyses stratified by age and race. Proportional mortality ratios (PMRs) were determined for the leading causes of death, including suicide, across clinical and demographic variables. Predictive nomograms for 3-year and 5-year suicide risk were developed using Cox regression models and validated through calibration curves and concordance indices.

Results

PCa patients exhibited elevated suicide SMRs, particularly among younger (<55 years, SMR = 8.50) and White patients (SMR = 14.98). While overall suicide risk declined over the study period, specific subgroups remained disproportionately affected. PMR analysis indicated younger age, White race, and earlier disease stages were associated with higher suicide proportions. Time-to-event analysis revealed that 20.28 % of suicide cases occurred within the first year after diagnosis. Predictive modeling identified age, race, radiotherapy, and marital status as independent risk factors for suicide mortality.

Conclusions

Suicide poses a significant yet preventable risk for PCa patients, especially among younger (especially<55 years), White, and unmarried individuals (both separated, divorced, and widowed and never married). The developed predictive tools can aid in identifying high-risk patients and implementing targeted psychosocial interventions.