Suppr超能文献

临床试验中处理缺失数据和信息性删失的问题。

Problems in dealing with missing data and informative censoring in clinical trials.

作者信息

Shih Weichung

机构信息

Division of Biometrics, University of Medicine and Dentistry of New Jersey School of Public Health, New Brunswick, New Jersey, USA.

出版信息

Curr Control Trials Cardiovasc Med. 2002 Jan 8;3(1):4. doi: 10.1186/1468-6708-3-4.

Abstract

Acommon problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to bias. There are no universally applicable methods for handling missing data. We recommend the following: (1) Report reasons for dropouts and proportions for each treatment group; (2) Conduct sensitivity analyses to encompass different scenarios of assumptions and discuss consistency or discrepancy among them; (3) Pay attention to minimize the chance of dropouts at the design stage and during trial monitoring; (4) Collect post-dropout data on the primary endpoints, if at all possible; and (5) Consider the dropout event itself an important endpoint in studies with many.

摘要

临床试验中的一个常见问题是出现缺失数据,即患者未完成研究且未进行进一步测量就退出。缺失数据会导致对完整或所有可用数据进行的常规统计分析产生偏差。目前尚无普遍适用的处理缺失数据的方法。我们建议如下:(1)报告各治疗组的退出原因及比例;(2)进行敏感性分析以涵盖不同的假设情况,并讨论它们之间的一致性或差异;(3)在设计阶段和试验监测期间注意尽量减少退出的可能性;(4)如果可能,收集关于主要终点的退出后数据;以及(5)在有许多退出情况的研究中,将退出事件本身视为一个重要终点。

相似文献

引用本文的文献

本文引用的文献

10
Combining mortality and longitudinal measures in clinical trials.在临床试验中结合死亡率和纵向测量指标。
Stat Med. 1999 Jun 15;18(11):1341-54. doi: 10.1002/(sici)1097-0258(19990615)18:11<1341::aid-sim129>3.0.co;2-7.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验