%TTD 和 %TUDD：新的 SAS 宏程序，用于计算肿瘤患者报告结局数据恶化时间的生存数据。
%TTD and %TUDD: New SAS macro programs to calculate the survival data of the time to deterioration for patient-reported outcomes data in oncology.
机构信息
Human and Social Sciences Department, Centre Léon Bérard, Lyon, France; Methodology and Quality of Life Unit in Oncology, University Hospital of Besançon, Besançon, France; UMR1098, University Bourgogne Franche-Comté, INSERM, EFS BFC, Interactions Hôte-Greffon-Tumeur/Ingénierie Cellulaire et Génique, France.
Methodology and Quality of Life Unit in Oncology, University Hospital of Besançon, Besançon, France; UMR1098, University Bourgogne Franche-Comté, INSERM, EFS BFC, Interactions Hôte-Greffon-Tumeur/Ingénierie Cellulaire et Génique, France.
出版信息
Comput Methods Programs Biomed. 2022 Feb;214:106537. doi: 10.1016/j.cmpb.2021.106537. Epub 2021 Nov 21.
BACKGROUND AND OBJECTIVE
Longitudinal analysis of patient-reported outcome (PRO) data remains challenging, as no standardization of statistical methods has been proposed, making comparison of PRO results between clinical trials difficult. In this context, the time to deterioration approach has recently been proposed and is regularly used as a modality of longitudinal PRO analysis in oncology.
METHODS
Two new SAS macro programs were developed, %TTD and %TUDD, which implement longitudinal analysis of PRO data according to the time to deterioration approach. These programs implement the recommended deterioration definitions. We described the programs with their different functionalities.
RESULTS
The %TTD macro calculates the time to first or transient deterioration, and the %TUDD macro calculates the time until definitive deterioration. These macros allow to obtain the survival variables from the time to deterioration approach. We illustrate our programs by presenting different applications on the randomized phase II AFUGEM GERCOR clinical trial.
CONCLUSION
The implementation of the deterioration definitions in SAS software allows the dissemination of this approach, in order to move toward the goal of standardization of longitudinal PRO analysis in oncology clinical trials.
背景与目的
患者报告结局（PRO）数据的纵向分析仍然具有挑战性，因为目前尚未提出标准化的统计方法，使得临床试验之间的 PRO 结果比较变得困难。在这种情况下，最近提出了恶化时间方法，并经常将其用作肿瘤学中纵向 PRO 分析的一种方式。
方法
开发了两个新的 SAS 宏程序，%TTD 和 %TUDD，它们根据恶化时间方法对 PRO 数据进行纵向分析。这些程序实现了推荐的恶化定义。我们描述了这些程序及其不同的功能。
结果
%TTD 宏计算首次或短暂恶化的时间，%TUDD 宏计算直至明确恶化的时间。这些宏允许从恶化时间方法中获得生存变量。我们通过呈现 AFUGEM GERCOR 随机二期临床试验的不同应用来说明我们的程序。
结论
在 SAS 软件中实现恶化定义允许该方法的传播，以便朝着肿瘤学临床试验中纵向 PRO 分析标准化的目标迈进。
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