Avoiding future controversies in the Alzheimer's disease space through understanding the aducanumab data and FDA review

• Published in: Alzheimer's research & therapy 2023-05, Vol.15 (1), p.98-98, Article 98
• Main Authors: Dickson, Samuel P, Hennessey, Sean, Nicodemus Johnson, Jessie, Knowlton, Newman, Hendrix, Suzanne B
• Format: Article
• Language: English
• Subjects: Alzheimer Disease - drug therapy; Alzheimer's disease; Amyloid beta-Peptides; Antibodies, Monoclonal, Humanized - therapeutic use; Clinical trials; Drug approval; Drug therapy; Errors, Scientific; Ethical aspects; Evaluation; FDA approval; Humans; Monoclonal antibodies; Review; Statistical methods
• ISSN: 1758-9193; 1758-9193
• DOI: 10.1186/s13195-023-01238-1

Key points of disagreement between the aducanumab FDA statistical review, which had primarily negative conclusions, and the clinical review, which had primarily positive conclusions, were investigated. Results from secondary endpoints in positive Study 302 were significant and these endpoints provided meaningful additional information. Findings indicate the statistical review of the aducanumab data was incorrect in a number of key areas. Greater placebo decline was not responsible for the significant results in Study 302. Correlations did exist between reduction in β-amyloid and clinical outcomes. Missing data and functional unblinding did not likely bias results. In contrast, the clinical review went too far in saying the negative results in Study 301 did not detract from the positive results in Study 302, as all clinical data should be considered in the evaluation, and the clinical review accepted the company's explanation for divergence of the results between the studies although much of the divergence remained unexplained. Interestingly, both the statistical review and the clinical review considered the available efficacy evidence despite both studies being terminated early. Implications of these findings include that the divergence in results seen in the two phase 3 aducanumab studies can be expected in other studies with similar design and analysis. Therefore, further research is needed to determine if analysis methods other than MMRM and/or optimized outcomes will provide more consistent results across studies.