Multiplicity of inferences in clinical trials: adjustment methods, clinical interpretation issues

Multiplicity of inferences is present in a large majority of clinical trials and conducts to false analyses or interpretation issues. The main risk consists in false positive conclusions. A large number of statistical methods is available for controlling the rate of false positive conclusions. But formal adjustment is not necessary in all cases and depends on the aims of the study.     

Confirmatory clinical trials with an adaptive design

Adaptive designs are one of the most promising developments in statistics with applications to clinical trials. Obviously, knowledge at the beginning of a clinical trial will always be limited. Thus it may seem logical that the knowledge from accumulating information should be used to optimize the design of the trial. This paper discusses conditions under which this may be possible in phase III clinical trials where the principal aim is confirmation of hypotheses that have been developed in earlier stages of drug development.     

Endpoints in the design of clinical trials for primary sclerosing cholangitis

Primary sclerosing cholangitis is an enigmatic disease affecting the bile ducts, eventually leading to liver failure necessitating liver transplantation in many cases. There is currently no therapy that has proven to halt disease progression. One of the reasons for this is the lack of proper endpoints to measure the effect of medical intervention on the course of the disease. Relevant clinical endpoints such as death or liver transplantation occur too infrequently in this orphan disease to be used as endpoints in phase 2 or 3 trials. It is therefore of utmost importance to identify appropriate surrogate endpoints that are reasonably likely to measure true clinical benefit. This article will discuss a number of surrogate endpoints that are likely candidates to serve this role. This article is part of a Special Issue entitled: Cholangiocytes in Health and Diseaseedited by Jesus Banales, Marco Marzioni, Nicholas LaRusso and Peter Jansen.