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Joint modeling quality of life and survival using a terminal decline model in palliative care studies

机译:在姑息治疗研究中使用终末下降模型对生活和生存质量进行联合建模

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Palliative medicine is a relatively new specialty that focuses on preventing and relieving the suffering of patients facing life-threatening illness. For cancer patients, clinical trials have been carried out to compare concurrent palliative care with usual cancer care in terms of longitudinal measurements of quality of life (QOL) until death, and overall survival is usually treated as a secondary endpoint. It is known that QOL of patients with advanced cancer decreases as death approaches; however, in previous clinical trials, this association has generally not been taken into account when inferences about the effect of an intervention on QOL or survival have been made. We developed a new joint modeling approach, a terminal decline model, to study the trajectory of repeated measurements and survival in a recently completed palliative care study. This approach takes the association of survival and QOL into account by modeling QOL retrospectively from death. For those patients whose death times are censored, marginal likelihood is used to incorporate them into the analysis. Our approach has two submodels: a piecewise linear random intercept model with serial correlation and measurement error for the retrospective trajectory of QOL and a piecewise exponential model for the survival distribution. Maximum likelihood estimators of the parameters are obtained by maximizing the closed-form expression of log-likelihood function. An explicit expression of quality-adjusted life years can also be derived from our approach. We present a detailed data analysis of our previously reported palliative care randomized clinical trial. ? 2012 John Wiley & Sons, Ltd.
机译:姑息医学是一个相对较新的专业,致力于预防和缓解面临生命危险的患者的痛苦。对于癌症患者,已经进行了临床试验,以纵轴测量生活质量(QOL)直至死亡,比较了同时姑息治疗和常规癌症治疗,并且通常将总体生存作为次要终点。众所周知,晚期癌症患者的生存质量会随着死亡的临近而降低;然而,在先前的临床试验中,当做出关于干预措施对QOL或生存的影响的推断时,通常没有考虑这种关联。我们开发了一种新的联合建模方法,即终末下降模型,以在最近完成的姑息治疗研究中研究重复测量和生存的轨迹。该方法通过从死亡中回顾性地对QOL进行建模,从而将生存率和QOL的关联考虑在内。对于那些检查了死亡时间的患者,使用边际可能性将其纳入分析。我们的方法有两个子模型:分段线性随机截距模型,具有QOL追溯轨迹的序列相关性和测量误差,以及分段生存率分布的指数模型。通过最大化对数似然函数的闭式表达式,可以获得参数的最大似然估计器。质量调整生命年的明确表达也可以从我们的方法中得出。我们对我们先前报道的姑息治疗随机临床试验进行了详细的数据分析。 ? 2012年John Wiley&Sons,Ltd.

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