Departments of Gastroenterology and Biostatistics, Sanjay Gandhi Postgraduate Institute of Medical Science, Raebareli Road, Lucknow, 226 014, India.
Indian J Gastroenterol. 2021 Oct;40(5):541-549. doi: 10.1007/s12664-021-01232-1. Epub 2022 Jan 10.
Survival analysis is a collection of statistical procedures employed on time-to-event data. The outcome variable of interest is time until an event occurs. Conventionally, it dealt with death as the event, but it can handle any event occurring in an individual like disease, relapse from remission, and recovery. Survival data describe the length of time from a time of origin to an endpoint of interest. By time, we mean years, months, weeks, or days from the beginning of being enrolled in the study. The major limitation of time-to-event data is the possibility of an event not occurring in all the subjects during a specific study period. In addition, some of the study subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. Life table and Kaplan-Meier techniques are employed to obtain the descriptive measures of survival times. The main objectives of survival analysis include analysis of patterns of time-to-event data, evaluating reasons why data may be censored, comparing the survival curves, and assessing the relationship of explanatory variables to survival time. Survival analysis also offers different regression models that accommodate any number of covariates (categorical or continuous) and produces adjusted hazard ratios for individual factor.
生存分析是一组用于处理事件时间数据的统计程序。感兴趣的结果变量是发生事件之前的时间。传统上，它以死亡作为事件，但它可以处理个体中发生的任何事件，如疾病、缓解后复发和康复。生存数据描述了从起源时间到感兴趣的终点的时间长度。在这里，时间是指从开始参与研究的年、月、周或日。事件时间数据的主要限制是在特定研究期间，所有受试者都有可能不会发生事件。此外，一些研究对象可能会提前退出研究。这种情况导致了所谓的删失观察，因为对于这些对象，没有完整的信息可用。寿命表和 Kaplan-Meier 技术用于获得生存时间的描述性测量。生存分析的主要目标包括分析事件时间数据的模式、评估数据可能被删失的原因、比较生存曲线以及评估解释变量与生存时间的关系。生存分析还提供了不同的回归模型，可以适应任意数量的协变量（分类或连续），并为个体因素生成调整后的危险比。
