Prediction models for self-harm and suicide: a systematic review and critical appraisal

作者：Aida Seyedsalehi, J.p.m. Bailey, Maya G. T. Ogonah, Thomas Fanshawe, Seena Fazel · 发表于：BMC Medicine · 年份：2025 · DOI：10.1186/s12916-025-04367-6 · 被引用次数：14 · 研究领域：Suicide and Self-Harm Studies、COVID-19 and Mental Health、Treatment of Major Depression

BACKGROUND: The number of prediction models for self-harm and suicide has grown substantially in recent years. However, their potential role in improving assessment of suicide risk is debated. In this systematic review, we provide an overview and critical appraisal of the predictive performance and methodological quality of prognostic risk models for self-harm and suicide. METHODS: We searched MEDLINE, EMBASE, PsycINFO, CINAHL, and Global Health from inception to 30/11/2021. The search was updated on 25/10/2024 to include new external validations. We included studies describing the development and/or external validation of statistical models for predicting risk of non-fatal self-harm and/or death by suicide. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS: We included 91 articles describing the development of 167 models and 29 external validations. Most models predicted risk of self-harm (76 models), followed by suicide (51 models), and the composite outcome of suicide or non-fatal self-harm (40 models). Only 8% of developed models (14/167) were externally validated, and 17% (28/167) were presented in a format enabling validation or use by others. The reported C indices ranged from 0.61 to 0.97 (median 0.82) in development studies and from 0.60 to 0.86 (median 0.81) in external validations. Calibration was assessed for 9% of models (15/167) in development studies and 31% of external validations (9/29). Of these, the OxMIS a...