Abstract
INTRODUCTION
Estimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods.
METHODS
We propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial.
RESULTS
Our study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm.
DISCUSSION
Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods.
Highlights
We explore the statistical considerations of the current method for estimating time savings.
We proposed alternative methods that provide time savings estimations based on the observed absolute differences.
By using various methods, a more comprehensive estimation of time savings can be achieved.
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This post is Copyright: Guoqiao Wang,
Gary Cutter,
Neil P. Oxtoby,
Guogen Shan,
Whedy Wang,
Brian Mangal,
Yijie Liao,
Jorge J. Llibre‐Guerra,
Yan Li,
Chengjie Xiong,
Eric McDade,
Paul Delmar,
Randall J. Bateman,
Lon Schneider | June 21, 2024