Data-dependent interim analyses are a useful tool in confirmatory Phase III or N clinical research. In particular, redesigning the sample size in an interim analysis based on the results observed to date considerably improves the power of the trial since the best available information at the time is used for the sample size adjustment. In recent years, several methods were proposed that enable a flexible design through the use of adaptive interim analyses while maintaining the type I error rate. In this article, these methods are briefly reviewed. We recommend a strategy that copes well with the demands of practice. Examples illustrate the use of multistage adaptive designs that make it possible to calculate confidence intervals and bias adjusted point estimates.
The effects in clinical studies of UDCA on the endpoints "death" or "pre-transplantation survival" can only be shown when UDCA therapy is started in an early disease phase, preferably in stage I but no later than stage II, and is then continued into stages III/IV, or preferably stage IV. The reasons for this lie in the observation that, in stages I/II, no patient suffers from progressive disease that irrevocably leads to death or transplantation, while a measurable effect of UDCA, as is true for other drugs and other hepatic diseases, continues to dwindle and finally disappears as patients progress through the fibrotic and cirrhotic stages III and IV. Hence, administration of UDCA must begin in the phase of progressive inflammation (stages I and II) and the outcome documented after many years of long-term therapy. This requires very large, probably unattainable, patient collectives. Whether it is justified to administer placebo to one-half of these patients over such an extended period of time represents a profound ethical dilemma. Because these arguments were not considered in the two meta-analyses cited above or in any other study, they do not allow a definitive statement on the life expectancy of patients on UDCA therapy. On the other hand, it is possible using generally accepted, independent prognostic variables and mathematical models, whose limitations are well-known and must be considered, to predict with a high degree of accuracy the disease course of treated and untreated patients and calculate their life expectancy and/or pre-transplantation survival. Because UDCA exerts a significant positive effect on the most important prognostic markers for PBC, such as serum bilirubin, piecemeal necroses, histological disease progression, ascites and edema, and apparently the scores for pruritus and fatigue, this permits us to demonstrate not only a decrease in the incidence of transplantation but also to calculate a prolongation in life expectancy.
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