Daniel M Goldenholz1, Alex Strashny2, Mark Cook3, Robert Moss4, William H Theodore5. 1. National Institutes of Health, NINDS, United States; Beth Israel Deaconess Medical Center, Department of Neurology, United States. Electronic address: daniel.goldenholz@bidmc.harvard.edu. 2. Centers for Disease Control, United States. Electronic address: kpr9@cdc.gov. 3. University of Melbourne, Department of Neurology, Australia. Electronic address: markcook@unimelb.edu.au. 4. SeizureTracker.com, United States. Electronic address: rob@seizuretracker.com. 5. National Institutes of Health, NINDS, United States. Electronic address: theodorw@ninds.nih.gov.
Abstract
PURPOSE: Clinical epilepsy drug trials have been measuring increasingly high placebo response rates, up to 40%. This study was designed to examine the relationship between the natural variability in epilepsy, and the placebo response seen in trials. We tested the hypothesis that 'reversing' trial direction, with the baseline period as the treatment observation phase, would reveal effects of natural variability. METHOD: Clinical trial simulations were run with time running forward and in reverse. Data sources were: SeizureTracker.com (patient reported diaries), a randomized sham-controlled TMS trial, and chronically implanted intracranial EEG electrodes. Outcomes were 50%-responder rates (RR50) and median percentage change (MPC). RESULTS: The RR50 results showed evidence that temporal reversal does not prevent large responder rates across datasets. The MPC results negative in the TMS dataset, and positive in the other two. CONCLUSIONS: Typical RR50s of clinical trials can be reproduced using the natural variability of epilepsy as a substrate across multiple datasets. Therefore, the placebo response in epilepsy clinical trials may be attributable almost entirely to this variability, rather than the "placebo effect". Published by Elsevier Ltd.
RCT Entities:
PURPOSE: Clinical epilepsy drug trials have been measuring increasingly high placebo response rates, up to 40%. This study was designed to examine the relationship between the natural variability in epilepsy, and the placebo response seen in trials. We tested the hypothesis that 'reversing' trial direction, with the baseline period as the treatment observation phase, would reveal effects of natural variability. METHOD: Clinical trial simulations were run with time running forward and in reverse. Data sources were: SeizureTracker.com (patient reported diaries), a randomized sham-controlled TMS trial, and chronically implanted intracranial EEG electrodes. Outcomes were 50%-responder rates (RR50) and median percentage change (MPC). RESULTS: The RR50 results showed evidence that temporal reversal does not prevent large responder rates across datasets. The MPC results negative in the TMS dataset, and positive in the other two. CONCLUSIONS: Typical RR50s of clinical trials can be reproduced using the natural variability of epilepsy as a substrate across multiple datasets. Therefore, the placebo response in epilepsy clinical trials may be attributable almost entirely to this variability, rather than the "placebo effect". Published by Elsevier Ltd.
Authors: Hyunmi Choi; Gary A Heiman; Heidi Munger Clary; Mill Etienne; Stanley R Resor; W Allen Hauser Journal: Epilepsy Res Date: 2010-12-21 Impact factor: 3.045
Authors: Daniel M Goldenholz; Shira R Goldenholz; Juan Romero; Rob Moss; Haoqi Sun; Brandon Westover Journal: Ann Neurol Date: 2020-07-09 Impact factor: 10.422
Authors: Daniel M Goldenholz; Robert Moss; David A Jost; Nathan E Crone; Gregory Krauss; Rosalind Picard; Chiara Caborni; Jose E Cavazos; John Hixson; Tobias Loddenkemper; Tracy Dixon Salazar; Laura Lubbers; Lauren C Harte-Hargrove; Vicky Whittemore; Jonas Duun-Henriksen; Eric Dolan; Nitish Kasturia; Mark Oberemk; Mark J Cook; Mark Lehmkuhle; Michael R Sperling; Patricia O Shafer Journal: Epilepsia Date: 2018-03-31 Impact factor: 5.864
Authors: Victor Ferastraoaru; Daniel M Goldenholz; Sharon Chiang; Robert Moss; William H Theodore; Sheryl R Haut Journal: Epilepsia Open Date: 2018-07-04
Authors: Sharon Chiang; Daniel M Goldenholz; Robert Moss; Vikram R Rao; Zulfi Haneef; William H Theodore; Jonathan K Kleen; Jay Gavvala; Marina Vannucci; John M Stern Journal: Epilepsia Date: 2019-12-02 Impact factor: 6.740