Development of a nomogram prediction model for suicide risk in schizophrenia patients

ZHANG Yin; YANG Xiao-yun; TAO Fang-fang

doi:10.13820/j.cnki.gdyx.20241975

Abstract：Objective To analyze the risk factors for suicidal behavior in schizophrenia patients and construct a nomogram prediction model to provide a reference for rehabilitation strategies.Methods A total of 152 schizophrenia pa-tients were selected as study subjects and divided into a suicide group(n=43)and a non-suicide group(n=109)based on the occurrence of suicidal behavior.The clinical data of both groups were compared,and multivariate logistic re-gression analysis was conducted to identify influencing factors.The"rms"package in R software was used to construct the nomogram prediction model.Results Significant differences were observed between the two groups in terms of smoking,family relationships,depression,anxiety,sleep disorders,negative stressful events,pre-morbid personality,medication adherence,years of education,PSSS scores,PANSS total scores,and general psychopathology(P＜0.05).Smoking,depression,negative stressful events,medication adherence,PSSS scores,and general psychopathology were identified as independent risk factors for suicide in schizophrenia patients.The nomogram prediction model constructed based on these factors showed a C-index of 0.853(95％CI:0.782-0.924),and the calibration curve was close to the ideal curve.Decision curve analysis indicated that when the risk threshold was＞0.08,this nomogram prediction model provided a higher clinical net benefit in predicting high probability of suicide compared to single independent predictive factors.Con-clusion The nomogram prediction model based on smoking,depression,negative stressful events,medication adherence,PSSS scores,and general psychopathology can personalize the prediction of suicide risk in schizophrenia patients,assisting healthcare professionals in formulating appropriate intervention measures.