Statistical consideration of the strategy for demonstrating clinical evidence of effectiveness--one larger vs two smaller pivotal studies.
As a regulatory strategy, it is nowadays not uncommon to conduct one confirmatory pivotal clinical trial, instead of two, to demonstrate efficacy and safety in drug development. This paper is intended to investigate the statistical foundation of such an approach. The one-study approach is compared with the conventional two-study approach in terms of power, type-I error, and fundamental statistical assumptions. Necessary requirements for a single-study model is provided in order to maintain equivalent evidence as that from a two-study model. In general, one-study model is valid only under a 'one population' assumption. In addition, higher data quality and more convincing and robust results need to be demonstrated in such cases. However, when 'one-population' assumption is valid and appropriate methods are selected, a one-study model can have a better power using the same sample size. The paper also investigates statistical assumptions and methods for making an overall inference when a two-study model has been used. The methods for integrated analysis are evaluated. It is important for statisticians to select correct pooling strategy based on the project objective and statistical hypothesis.
Shun
Zhenming
Z
Biometrics and Data Management, Aventis Pharma, 200 Crossing, Bridgewater, NJ 08807, USA. zhenming.shun@aventis.com
Chi
Eric
E
Durrleman
Sylvain
S
Fisher
Lloyd
L
D017326:Clinical Trials, Phase III as Topic / Q000379:methods*; D017277:Drug Approval / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D014481:United States; D014486:United States Food and Drug Administration