title: Advantages of a wholly Bayesian approach to assessing efficacy in early drug development: a case study.
abstract: This paper illustrates how the design and statistical analysis of the primary endpoint of a proof-of-concept study can be formulated within a Bayesian framework and is motivated by and illustrated with a Pfizer case study in chronic kidney disease. It is shown how decision criteria for success can be formulated, and how the study design can be assessed in relation to these, both using the traditional approach of probability of success conditional on the true treatment difference and also using Bayesian assurance and pre-posterior probabilities. The case study illustrates how an informative prior on placebo response can have a dramatic effect in reducing sample size, saving time and resource, and we argue that in some cases, it can be considered unethical not to include relevant literature data in this way.
authors: UCB Pharma, 208 Bath Road, Slough, SL1 3WE, UK.
authors: Rosalind J
authors: RJ
authors: Walley
authors: Eli Lilly and Company Limited, Erl Wood Manor, Windlesham, GU20 6PH, UK.
authors: Claire L
authors: CL
authors: Smith
authors: Pfizer, 610 Main Street, Cambridge, 02139, MA, USA.
authors: Jeremy D
authors: JD
authors: Gale
authors: Pfizer, Neusentis, The Portway Building, Granta Park, Cambridge, CB21 6GS, UK.
authors: Phil
authors: P
authors: Woodward
mesh_terms: D000419:Albuminuria / Q000097:blood; D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic / Q000379:methods* / Q000592:standards; D003404:Creatinine / Q000097:blood; D006801:Humans; D015233:Models, Statistical; D015990:Placebo Effect; D011336:Probability; D051436:Renal Insufficiency, Chronic / Q000188:drug therapy; D012107:Research Design; D013223:Statistics as Topic; D016896:Treatment Outcome
chemical_list: D003404:Creatinine
keywords: Bayesian inference; assurance; interim analysis; operating characteristics; pre-posterior distribution