• Brian C Healy and David Schoenfeld.
• Biostatistics Center, Massachusetts General Hospital, 50 Staniford Street, Suite 560, Boston, Massachusetts 02114, USA. bchealy@partners.org
• Muscle Nerve. 2012 Oct 1; 46 (4): 506-11.

IntroductionIn this study we explore several methods for incorporating survival information in the analysis of Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS) scores.MethodsALSFRS scores and patient survival times were simulated based on estimates from a recent clinical trial. Six analysis approaches were applied to the data. Each approach was based on ALSFRS scores, the survival time, or a combination of the 2. The power of each approach to detect potential treatment effects was estimated.ResultsWhen the treatment acted solely on the change in ALSFRS, the shared parameter model provided the most power, although all of the models based on random effects were similar. As the effect on survival increased, rank-based analysis showed potential gains in power. Survival analysis was superior under a small effect on ALSFRS and a larger effect on mortality.ConclusionsThe shared parameter model and rank-based approach can offer improvements in power over traditional approaches.Copyright © 2012 Wiley Periodicals, Inc.

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