Accelerated failure time models provide a useful statistical framework for aging research.
Accelerated failure time models provide a useful statistical framework for aging research.
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DOI：
10.1016/j.exger.2008.10.005
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发表时间：
2009-03
影响因子：
3.9
通讯作者：
Swindell, William R.
中科院分区：
文献类型：
--
作者：
Swindell, William R.
生存实验在衰老研究中发挥着核心作用，并用于评估干预措施是否会改变衰老速度并延长寿命。加速失效时间（AFT）模型很少用于分析生存数据，但提供了一个潜在的有用的统计方法，是基于生存曲线，而不是危险函数。在这项研究中，AFT模型被用来分析来自16个生存实验的数据，这些实验评估了一种或多种遗传操作对小鼠寿命的影响。大多数遗传操作被发现有一个倍增效应的生存率是独立的年龄和良好的特点是AFT模型的“减速因子”。AFT模型减速因子还提供了比风险比更直观的治疗效果测量，并且对偏离建模假设具有稳健性。使用分位数回归模型研究了药物依赖性治疗效应（如果存在）。这些结果提供了与目前已知的长寿小鼠模型相关的存活率数据的信息和定量总结。此外，从老龄化研究的角度来看，这些统计方法具有吸引人的属性，并为生存数据的分析提供了有价值的工具。
Survivorship experiments play a central role in aging research and are performed to evaluate whether interventions alter the rate of aging and increase lifespan. The accelerated failure time (AFT) model is seldom used to analyze survivorship data, but offers a potentially useful statistical approach that is based upon the survival curve rather than the hazard function. In this study, AFT models were used to analyze data from 16 survivorship experiments that evaluated the effects of one or more genetic manipulations on mouse lifespan. Most genetic manipulations were found to have a multiplicative effect on survivorship that is independent of age and well-characterized by the AFT model “deceleration factor”. AFT model deceleration factors also provided a more intuitive measure of treatment effect than the hazard ratio, and were robust to departures from modeling assumptions. Age-dependent treatment effects, when present, were investigated using quantile regression modeling. These results provide an informative and quantitative summary of survivorship data associated with currently known long-lived mouse models. In addition, from the standpoint of aging research, these statistical approaches have appealing properties and provide valuable tools for the analysis of survivorship data.
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