King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
King's College London, Department of Biostatistics, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Child Abuse Negl. 2019 Dec;98:104188. doi: 10.1016/j.chiabu.2019.104188. Epub 2019 Sep 27.
Childhood victimization elevates the average risk of developing functional impairment in adulthood. However, not all victimized children demonstrate poor outcomes. Although research has described factors that confer vulnerability or resilience, it is unknown if this knowledge can be translated to accurately identify the most vulnerable victimized children.
To build and internally validate a risk calculator to identify those victimized children who are most at risk of functional impairment at age 18 years.
We utilized data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative birth cohort of 2232 UK children born in 1994-95.
Victimization exposure was assessed repeatedly between ages 5 and 12 years along with a range of individual-, family- and community-level predictors. Functional outcomes were assessed at age 18 years. We developed and evaluated a prediction model for psychosocial disadvantage and economic disadvantage using the Least Absolute Shrinkage and Selection Operator (LASSO) regularized regression with nested 10-fold cross-validation.
The model predicting psychosocial disadvantage following childhood victimization retained 12 of 22 predictors, had an area under the curve (AUC) of 0.65, and was well-calibrated within the range of 40-70% predicted risk. The model predicting economic disadvantage retained 10 of 22 predictors, achieved excellent discrimination (AUC = 0.80), and a high degree of calibration.
Prediction modelling techniques can be applied to estimate individual risk for poor functional outcomes in young adulthood following childhood victimization. Such risk prediction tools could potentially assist practitioners to target interventions, which is particularly useful in a context of scarce resources.
童年期受虐会增加成年后出现功能障碍的平均风险。然而，并非所有受虐儿童都表现出不良结局。尽管研究已经描述了易感性或弹性的因素，但尚不清楚这些知识是否可以转化为准确识别最易受伤害的受虐儿童。
构建和内部验证一个风险计算器，以识别那些在 18 岁时最有可能出现功能障碍的受虐儿童。
我们利用了来自环境风险（E-Risk）纵向双胞胎研究的数据，该研究是一项全国代表性的出生队列研究，共有 2232 名 1994-1995 年出生的英国儿童。
在 5 至 12 岁之间反复评估受虐暴露情况，并评估一系列个体、家庭和社区层面的预测因素。在 18 岁时评估功能结局。我们使用套索（LASSO）正则化回归进行嵌套 10 折交叉验证，开发和评估了用于预测心理社会劣势和经济劣势的预测模型。
用于预测童年受虐后心理社会劣势的模型保留了 22 个预测因素中的 12 个，曲线下面积（AUC）为 0.65，在 40-70%预测风险范围内具有良好的校准。用于预测经济劣势的模型保留了 22 个预测因素中的 10 个，具有出色的区分度（AUC=0.80）和高度的校准。
预测建模技术可用于估计童年受虐后年轻成年期功能不良结局的个体风险。这种风险预测工具可以帮助临床医生有针对性地进行干预，这在资源稀缺的情况下尤其有用。
