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.

Plos One
|March 18, 2015
PubMed

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.