Is the FDA Too Conservative or Too Aggressive?: A Bayesian Decision Analysis of Clinical Trial Design

Vahid Montazerhodjat and Andrew Lo ()

No 21499, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Implicit in the drug-approval process is a trade-off between Type I and Type II error. We explore the application of Bayesian decision analysis (BDA) to minimize the expected cost of drug approval, where relative costs are calibrated using U.S. Burden of Disease Study 2010 data. The results for conventional fixed-sample randomized clinical-trial designs suggest that for terminal illnesses with no existing therapies such as pancreatic cancer, the standard threshold of 2.5% is substantially more conservative than the BDA-optimal threshold of 27.9%. However, for relatively less deadly conditions such as prostate cancer, 2.5% is more risk-tolerant or aggressive than the BDA-optimal threshold of 1.2%. We compute BDA-optimal sizes for 25 of the most lethal diseases and show how a BDA-informed approval process can incorporate all stakeholders’ views in a systematic, transparent, internally consistent, and repeatable manner.

JEL-codes: C11 C12 C44 I10 I12 I13 I18 (search for similar items in EconPapers)
Date: 2015-08
Note: EH
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Published as Isakov, Leah & Lo, Andrew W. & Montazerhodjat, Vahid, 2019. "Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design," Journal of Econometrics, Elsevier, vol. 211(1), pages 117-136.

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Journal Article: Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design (2019)
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