biostudies-literatureShen Cthe Clinical special research fund project of Nantong University3000605251399460https://www.ebi.ac.uk/biostudies/studies/S-EPMC12681682biostudies-literatureUnknown53(12)ObjectiveThe correlation between depression and prostatitis is widely acknowledged; however, there is a dearth of comprehensive risk models that can predict the risk of depression in patients with chronic prostatitis/chronic pelvic pain syndrome. In this investigation, we devised a predictive model to ascertain the likelihood of depression in these patients.MethodsThis prospective study enrolled 599 patients with chronic prostatitis/chronic pelvic pain syndrome between January 2022 and January 2025. The patients were randomly divided into training (70%, n = 419) and validation (30%, n = 180) cohorts. Using depression (Patient Health Questionnaire-9 score ≥10) as the primary outcome, we developed a nomogram using Boruta and least absolute shrinkage and selection operator feature selection fThe Journal of international medical researchRisk model for depression in patients with chronic prostatitis/chronic pelvic pain syndrome: A retrospective cross-sectional study.PMC126816822024LQ019Zhang WFang XYou JZheng BShen CJi YfalseRisk model for depression in patients with chronic prostatitis/chronic pelvic pain syndrome: A retrospective cross-sectional study.ObjectiveThe correlation between depression and prostatitis is widely acknowledged; however, there is a dearth of comprehensive risk models that can predict the risk of depression in patients with chronic prostatitis/chronic pelvic pain syndrome. In this investigation, we devised a predictive model to ascertain the likelihood of depression in these patients.MethodsThis prospective study enrolled 599 patients with chronic prostatitis/chronic pelvic pain syndrome between January 2022 and January 2025. The patients were randomly divided into training (70%, n = 419) and validation (30%, n = 180) cohorts. Using depression (Patient Health Questionnaire-9 score ≥10) as the primary outcome, we developed a nomogram using Boruta and least absolute shrinkage and selection operator feature selection f2025-01-01T00:00:00Z2025 Dec2026-06-05T23:24:10.221Z2026-05-23T03:13:03.027ZS-EPMC126816824134221410.1177/03000605251399460