Background: In December 2019, in light of additional blinded data, Biogen claimed efficacy of the drug Aducanumab (ADU). Objective: We conducted a reanalysis of the phase III ADU summary statistics, focusing in particular on the Clinical Dementia Rating-Sum of Boxes. Methods: We used a Bayesian framework to mitigate the problems of the null-hypothesis significance testing framework. In particular, we used Bayes Factor (BF) to analyze the summary statistics. The BF is the comparison of how well two hypotheses predict the data. Results: Our results showed that the evidence for ADU efficacy is very low. The results show that the only data with a BF value in favor of the alternative hypothesis (i.e., drug efficacy) is the high-dose condition in the EMERGE trial. However, the obtained BF falls within the range of values considered anecdotal, meaning a low level of evidence. Conclusion: We provide a clearer interpretation of the results of the clinical trials based on the Bayesian framework, as this may be useful for future development and research in the field.

A Bayesian Reanalysis of the Phase III Aducanumab (ADU) Trial

Tommaso Costa
First
;
Franco Cauda
Last
2022

Abstract

Background: In December 2019, in light of additional blinded data, Biogen claimed efficacy of the drug Aducanumab (ADU). Objective: We conducted a reanalysis of the phase III ADU summary statistics, focusing in particular on the Clinical Dementia Rating-Sum of Boxes. Methods: We used a Bayesian framework to mitigate the problems of the null-hypothesis significance testing framework. In particular, we used Bayes Factor (BF) to analyze the summary statistics. The BF is the comparison of how well two hypotheses predict the data. Results: Our results showed that the evidence for ADU efficacy is very low. The results show that the only data with a BF value in favor of the alternative hypothesis (i.e., drug efficacy) is the high-dose condition in the EMERGE trial. However, the obtained BF falls within the range of values considered anecdotal, meaning a low level of evidence. Conclusion: We provide a clearer interpretation of the results of the clinical trials based on the Bayesian framework, as this may be useful for future development and research in the field.
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https://arxiv.org/ftp/arxiv/papers/2107/2107.03686.pdf
bayesian analysis, alzheimer, clinical tirals
Tommaso Costa; Franco Cauda
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1873278
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