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Design and Statistical Innovations in a Platform Trial for Amyotrophic Lateral Sclerosis.

Authors :
Quintana, Melanie
Saville, Benjamin R.
Vestrucci, Matteo
Detry, Michelle A.
Chibnik, Lori
Shefner, Jeremy
Berry, James D.
Chase, Marianne
Andrews, Jinsy
Sherman, Alexander V.
Yu, Hong
Drake, Kristin
Cudkowicz, Merit
Paganoni, Sabrina
Macklin, Eric A.
Macklin, Eric
Hayden, Douglas
Lai, PoYing
Donahue, Rachel
Marion, Joseph
Source :
Annals of Neurology; Sep2023, Vol. 94 Issue 3, p547-560, 14p
Publication Year :
2023

Abstract

Platform trials allow efficient evaluation of multiple interventions for a specific disease. The HEALEY ALS Platform Trial is testing multiple investigational products in parallel and sequentially in persons with amyotrophic lateral sclerosis (ALS) with the goal of rapidly identifying novel treatments to slow disease progression. Platform trials have considerable operational and statistical efficiencies compared with typical randomized controlled trials due to their use of shared infrastructure and shared control data. We describe the statistical approaches required to achieve the objectives of a platform trial in the context of ALS. This includes following regulatory guidance for the disease area of interest and accounting for potential differences in outcomes of participants within the shared control (potentially due to differences in time of randomization, mode of administration, and eligibility criteria). Within the HEALEY ALS Platform Trial, the complex statistical objectives are met using a Bayesian shared parameter analysis of function and survival. This analysis serves to provide a common integrated estimate of treatment benefit, overall slowing in disease progression, as measured by function and survival while accounting for potential differences in the shared control group using Bayesian hierarchical modeling. Clinical trial simulation is used to provide a better understanding of this novel analysis method and complex design. ANN NEUROL 2023;94:547–560 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03645134
Volume :
94
Issue :
3
Database :
Complementary Index
Journal :
Annals of Neurology
Publication Type :
Academic Journal
Accession number :
171369122
Full Text :
https://doi.org/10.1002/ana.26714