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Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial

机译：间皮瘤试验中使用潜在生长建模方法对纵向结果和生存进行联合建模

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Joint modeling of longitudinal and survival data can provide more efficient and less biased estimates of treatment effects through accounting for the associations between these two data types. Sponsors of oncology clinical trials routinely and increasingly include patient-reported outcome (PRO) instruments to evaluate the effect of treatment on symptoms, functioning, and quality of life. Known publications of these trials typically do not include jointly modeled analyses and results. We formulated several joint models based on a latent growth model for longitudinal PRO data and a Cox proportional hazards model for survival data. The longitudinal and survival components were linked through either a latent growth trajectory or shared random effects. We applied these models to data from a randomized phase HI oncology clinical trial in mesothelioma. We compared the results derived under different model specifications and showed that the use of joint modeling may result in improved estimates of the overall treatment effect.
机译：纵向和生存数据的联合建模可以通过考虑这两种数据类型之间的关联，从而提供更有效且偏差较小的治疗效果估计。肿瘤学临床试验的赞助商通常并越来越多地使用患者报告的结局（PRO）工具来评估治疗对症状，功能和生活质量的影响。这些试验的已知出版物通常不包括联合建模的分析和结果。我们基于纵向PRO数据的潜在增长模型和生存数据的Cox比例风险模型，制定了几个联合模型。纵向和生存部分通过潜在的生长轨迹或共享随机效应联系在一起。我们将这些模型应用于间皮瘤的HI阶段随机临床试验的数据。我们比较了在不同模型规范下得出的结果，并表明使用联合建模可能会改善总体治疗效果的估计值。

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