Departments of Pathology and Geriatrics, University of Michigan, Ann Arbor, MI 48109-2200, USA.
Exp Gerontol. 2009 Mar;44(3):190-200. doi: 10.1016/j.exger.2008.10.005. Epub 2008 Oct 25.
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.
生存实验在衰老研究中起着核心作用，用于评估干预措施是否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，但提供了一种潜在有用的统计方法，该方法基于生存曲线而不是危险函数。在这项研究中，使用 AFT 模型分析了 16 项生存实验的数据，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对生存具有乘法效应，与年龄无关，并且很好地由 AFT 模型“减速因子”来描述。AFT 模型的减速因子也提供了比危险比更直观的处理效果衡量指标，并且对模型假设的偏离具有鲁棒性。当存在年龄相关的治疗效果时，使用分位数回归模型进行了研究。这些结果提供了与当前已知的长寿小鼠模型相关的生存数据的信息丰富和定量总结。此外，从衰老研究的角度来看，这些统计方法具有吸引人的特性，并为生存数据的分析提供了有价值的工具。
