Analysis of longitudinal data in an Alzheimer's disease clinical trial

✍ Scribed by Ronald G. Thomas; Julie D. Berg; Mary Sano; Leon Thal

• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 128 KB
• Volume: 19
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(20000615/30)19:11/12<1433::aid-sim435>3.0.co;2-f

✦ Synopsis

Evidence of delayed progression is the primary mechanism for demonstrating therapeutic e cacy in clinical trials in Alzheimer's disease. In the major trials of therapeutic treatment of AD, to date, measures based on clinical judgement and cognitive performance, instead of mortality, have been used as the primary response measures. There is good reason for this since the course of the disease is quite long, and AD trials designed around mortality would require either very large sample sizes or very long follow-up in order to have adequate power. However, the evaluation of progression in AD using clinical markers is subject to a number of challenges often found in longitudinal databases, for example, missing data, oor and ceiling e ects and non-linearity. Unfortunately, few of these issues are being addressed in the typical analysis of progression data. This paper explores these analytic issues in the context of the recently completed Alzheimer's Disease Cooperative Study trial of vitamin E and Selegeline in moderate AD patients.