Mean residual lifetime is an important measure utilized in various fields, including pharmaceutical companies, manufacturing companies, and insurance companies for survival analysis. However, the computation of mean residual lifetime can be laborious and challenging. To address this issue, the R package reslife has been developed, which enables efficient calculation of mean residual lifetime based on closed-form solution in a user-friendly manner. reslife offers the capability to utilize either the results of a flexsurv regression or user-provided parameters to compute mean residual lifetime. Furthermore, there are options to return median and percentile residual lifetime. If the user chooses to use the outputs of a flexsurv regression, there is an option to input a data frame with unobserved data. In this article, we present reslife, explain its underlying mathematical principles, illustrate its functioning, and provide examples on how to utilize the package. The aim is to facilitate the use of mean residual lifetime, making it more accessible and efficient for practitioners in various disciplines, particularly those involved in survival analysis within the pharmaceutical industry. This package has been approved and available on CRAN: https://cran.r-project.org/web/packages/reslife/index.html

翻译：平均剩余寿命是生存分析中的一个重要指标，广泛应用于制药公司、制造企业和保险公司等多个领域。然而，平均剩余寿命的计算过程可能既繁琐又具有挑战性。为解决此问题，研究者开发了R包reslife，该工具基于闭式解以用户友好的方式高效计算平均剩余寿命。reslife支持通过flexsurv回归结果或用户提供的参数来计算平均剩余寿命，并提供中位剩余寿命和百分位剩余寿命的选项。若用户选择使用flexsurv回归的输出，还可输入包含未观测数据的数据框。本文介绍reslife，阐述其底层数学原理，展示其运行机制，并提供使用该包的示例。旨在促进平均剩余寿命的应用，使其对多学科从业者（尤其是制药行业从事生存分析的研究者）更易获取且高效。该包已获批准并发布于CRAN：https://cran.r-project.org/web/packages/reslife/index.html