Medical studies for chronic disease are often interested in the relation between longitudinal risk factor profiles and individuals' later life disease outcomes. These profiles may typically be subject to intermediate structural changes due to treatment or environmental influences. Analysis of such studies may be handled by the joint model framework. However, current joint modeling does not consider structural changes in the residual variability of the risk profile nor consider the influence of subject-specific residual variability on the time-to-event outcome. In the present paper, we extend the joint model framework to address these two heterogeneous intra-individual variabilities. A Bayesian approach is used to estimate the unknown parameters and simulation studies are conducted to investigate the performance of the method. The proposed joint model is applied to the Framingham Heart Study to investigate the influence of anti-hypertensive medication on the systolic blood pressure variability together with its effect on the risk of developing cardiovascular disease. We show that anti-hypertensive medication is associated with elevated systolic blood pressure variability and increased variability elevates risk of developing cardiovascular disease.

翻译：慢性疾病的医学研究常关注纵向风险因素特征与个体后期疾病结局之间的关联。此类特征通常可能因治疗或环境因素发生中间结构性变化，而联合建模框架可用于分析此类研究。然而，当前联合建模方法既未考虑风险因素特征残差变异性的结构性变化，也未考虑个体特异性残差变异性对时间至事件结局的影响。本文扩展了联合建模框架，以处理这两种异质性个体内变异性。研究采用贝叶斯方法估计未知参数，并通过模拟实验评估该方法的性能。所提出的联合模型被应用于弗拉明汉心脏研究，用以探究抗高血压药物对收缩压变异性的影响及其与心血管疾病发生风险的关联。结果表明，抗高血压药物与收缩压变异性升高相关，而增大的变异性进一步提升了心血管疾病的发生风险。