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A novel approach to delayed-start analyses for demonstrating disease-modifying effects in Alzheimer's disease
Hong Liu-Seifert1, Scott W Andersen1, Ilya Lipkovich1
1Eli Lilly and Company, Indianapolis, Indiana, United States of America.
Abstract:
One method for demonstrating disease modification is a delayed-start design, consisting of a placebo-controlled period followed by a delayed-start period wherein all patients receive active treatment. To address methodological issues in previous delayed-start approaches, we propose a new method that is robust across conditions of drug effect, discontinuation rates, and missing data mechanisms. We propose a modeling approach and test procedure to test the hypothesis of noninferiority, comparing the treatment difference at the end of the delayed-start period with that at the end of the placebo-controlled period. We conducted simulations to identify the optimal noninferiority testing procedure to ensure the method was robust across scenarios and assumptions, and to evaluate the appropriate modeling approach for analyzing the delayed-start period. We then applied this methodology to Phase 3 solanezumab clinical trial data for mild Alzheimer's disease patients. Simulation results showed a testing procedure using a proportional noninferiority margin was robust for detecting disease-modifying effects; conditions of high and moderate discontinuations; and with various missing data mechanisms. Using all data from all randomized patients in a single model over both the placebo-controlled and delayed-start study periods demonstrated good statistical performance. In analysis of solanezumab data using this methodology, the noninferiority criterion was met, indicating the treatment difference at the end of the placebo-controlled studies was preserved at the end of the delayed-start period within a pre-defined margin. The proposed noninferiority method for delayed-start analysis controls Type I error rate well and addresses many challenges posed by previous approaches. Delayed-start studies employing the proposed analysis approach could be used to provide evidence of a disease-modifying effect. This method has been communicated with FDA and has been successfully applied to actual clinical trial data accrued from the Phase 3 clinical trials of solanezumab.
Insights
This study introduces a robust new method for delayed-start trial analysis to demonstrate disease modification. The approach successfully preserved treatment differences in Alzheimer's disease trial data, indicating potential for disease-modifying effects.
Area of Science:
- Clinical Trials Methodology
- Neurodegenerative Disease Research
- Biostatistics
Background:
- Delayed-start designs are used to demonstrate disease modification in clinical trials.
- Previous methods faced methodological challenges with drug effects, discontinuations, and missing data.
- Alzheimer's disease (AD) research requires robust methods to assess disease-modifying therapies.
Purpose of the Study:
- To propose and validate a novel, robust methodology for analyzing delayed-start clinical trial data.
- To develop a noninferiority testing procedure suitable for delayed-start designs.
- To apply the methodology to Phase 3 solanezumab trial data for mild Alzheimer's disease.
Main Methods:
- Developed a modeling approach and noninferiority test for delayed-start designs.
- Conducted simulations to optimize the testing procedure and modeling approach.
- Applied the validated methodology to Phase 3 solanezumab clinical trial data.
Main Results:
- The proposed noninferiority testing procedure, using a proportional margin, proved robust across various conditions (drug effect, discontinuation, missing data).
- Analyzing all data within a single model across both placebo-controlled and delayed-start periods showed good statistical performance.
- The methodology met noninferiority criteria in the solanezumab data analysis, preserving treatment differences.
Conclusions:
- The novel noninferiority method for delayed-start analysis effectively controls Type I error and addresses prior methodological limitations.
- This approach offers a reliable way to provide evidence of disease-modifying effects in clinical trials.
- The method has been communicated with the FDA and successfully applied to solanezumab Phase 3 trial data.
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