Department of Mathematics, Syracuse University, Syracuse, New York, USA.
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA.
Stat Med. 2022 Jul 20;41(16):3102-3130. doi: 10.1002/sim.9407. Epub 2022 May 6.
Since its release of Version 1.0 in 1998, Joinpoint software developed for cancer trend analysis by a team at the US National Cancer Institute has received a considerable attention in the trend analysis community and it became one of most widely used software for trend analysis. The paper published in Statistics in Medicine in 2000 (a previous study) describes the permutation test procedure to select the number of joinpoints, and Joinpoint Version 1.0 implemented the permutation procedure as the default model selection method and employed parametric methods for the asymptotic inference of the model parameters. Since then, various updates and extensions have been made in Joinpoint software. In this paper, we review basic features of Joinpoint, summarize important updates of Joinpoint software since its first release in 1998, and provide more information on two major enhancements. More specifically, these enhancements overcome prior limitations in both the accuracy and computational efficiency of previously used methods. The enhancements include: (i) data driven model selection methods which are generally more accurate under a broad range of data settings and more computationally efficient than the permutation test and (ii) the use of the empirical quantile method for construction of confidence intervals for the slope parameters and the location of the joinpoints, which generally provides more accurate coverage than the prior parametric methods used. We show the impact of these changes in cancer trend analysis published by the US National Cancer Institute.
自 1998 年美国国家癌症研究所的一个团队发布 1.0 版本以来，用于癌症趋势分析的 Joinpoint 软件在趋势分析社区中受到了相当大的关注，它已成为最广泛使用的趋势分析软件之一。2000 年发表在《统计医学》上的一篇论文（之前的一项研究）描述了选择连接点数量的置换检验程序，Joinpoint 1.0 实现了置换程序作为默认模型选择方法，并采用参数方法对模型参数进行渐近推断。从那时起，Joinpoint 软件进行了各种更新和扩展。本文回顾了 Joinpoint 的基本特征，总结了自 1998 年首次发布以来 Joinpoint 软件的重要更新，并提供了有关两个主要增强功能的更多信息。更具体地说，这些增强功能克服了之前使用的方法在准确性和计算效率方面的局限性。这些增强功能包括：（i）数据驱动的模型选择方法，在广泛的数据设置下通常更准确，并且比置换检验更具计算效率；（ii）使用经验分位数方法构建斜率参数和连接点位置的置信区间，通常比之前使用的参数方法提供更准确的覆盖范围。我们展示了这些变化在美国国家癌症研究所发布的癌症趋势分析中的影响。
