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通常关注纵向风险因素特征与个体后期疾病结局之间的关系。这些特征可能因治疗或环境影响而发生中间结构性变化。对此类研究的分析可通过联合模型框架进行处理。然而，当前的联合模型既未考虑风险特征残差异质性的结构性变化，也未考虑个体特异性残差异质性对时间-事件结局的影响。本文扩展了联合模型框架以解决这两种个体内异质性问题。采用贝叶斯方法估计未知参数，并通过模拟研究评估该方法的表现。所提出的联合模型被应用于弗拉明汉心脏研究，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风险的关系。结果表明，抗高血压药物与收缩压变异性升高相关，而变异性增加会进一步加剧心血管疾病的发病风险。