自我伤害和自杀的预测模型:系统审查和批判性评估
Aida Seyedsalehi1, James Bailey2, Maya G T Ogonah1
1Department of Psychiatry, University of Oxford, Oxford, UK.
BMC medicine
|October 10, 2025
概括
这一系统性审查批判性地评估了自杀风险预测模型. 五种模型在外部验证中表现出良好的预测性能,突出显示了未来研究中需要严格的方法和外部验证的需要.
科学领域:
- 精神病学是一个精神病学.
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 自杀风险预测模型的开发增加了,但它们的临床实用性仍在争论中.
- 需要进行系统审查,以批判性地评估这些预测模型的预测性能和方法质量.
研究的目的:
- 提供自我伤害和自杀的预后风险模型的预测性能和方法质量的概述和批判性评估.
- 在外部验证中识别具有足够性能的模型.
主要方法:
- 系统搜索多个数据库 (MEDLINE,EMBASE,PsycINFO,CINAHL,Global Health) 从创建到2021年11月,并于2024年10月更新,以获得新的外部验证.
- 包括关于开发和/或外部验证用于预测自我伤害和/或自杀风险的统计模型的研究.
- 使用预测模型的偏差风险评估工具 (PROBAST) 进行偏差风险评估.
主要成果:
- 91篇文章描述了167个模型;只有8%得到了外部验证.
- 报告的C指数在0.60至0.97之间,中位数约为0.81-0.82.82.
- 在外部验证中,OxMIS和西蒙模型显示了充分的歧视和校准,尽管大多数研究由于方法上的缺陷而存在高偏差风险.
结论:
- 尽管存在怀疑,但五种模型在外部验证中显示出良好的预测性能.
- 研究浪费是显而易见的,因为过多的未经验证的模型和方法上的缺陷.
- 未来的研究必须优先考虑方法严谨性,外部验证,模型更新和透明报告.
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