In this work, we introduce a personalised and age-specific Net Benefit function, composed of benefits and costs, to recommend optimal timing of risk assessments for cardiovascular disease prevention. We extend the 2-stage landmarking model to estimate patient-specific CVD risk profiles, adjusting for time-varying covariates. We apply our model to data from the Clinical Practice Research Datalink, comprising primary care electronic health records from the UK. We find that people at lower risk could be recommended an optimal risk-assessment interval of 5 years or more. Time-varying risk-factors are required to discriminate between more frequent schedules for higher-risk people.

翻译：本文引入了一个个性化且年龄特异性的净收益函数，该函数由收益与成本构成，旨在为心血管疾病预防的风险评估推荐最优时机。我们将两阶段标志性模型进行扩展，以估计患者特异性的心血管疾病风险特征，并对时变协变量进行调整。我们将该模型应用于来自临床实践研究数据链（Clinical Practice Research Datalink）的数据，该数据包含英国初级保健电子健康记录。研究发现，低风险人群可被推荐进行间隔为5年或更长时间的最优风险评估；而对于高风险人群，则需利用时变风险因素来区分更频繁的评估安排。