ABSTRACT
Evaluating a surrogate endpoint typically requires a large amount of data, and this is particularly so when the contemporary multiple-trial surrogate endpoint evaluation methods are used. The need for a large sample size is an issue in all clinical trials (e.g., an increased study duration and cost, a higher probability of missing values due to study drop-out, and so on), and it is particularly problematic in clinical trials in rare diseases (or in clinical trials in small patient subgroups that are identified within the context of a common disease). Indeed, in rare diseases the number of patients that are available for study participation is typically substantially smaller compared to what is the case in non-rare disease clinical trials. Yet, surrogate endpoints may be particularly useful in rare disease clinical trials (Korn et al., 2013). Indeed, the use of a surrogate endpoint may result in a smaller sample size that is needed to show the effectiveness of a new treatment, because (i) the
with
surrogate endpoint may be an event that occurs more frequently than the true endpoint, and/or because (ii) the treatment effect on the surrogate endpoint may be larger compared to the treatment effect on the true endpoint (in particular when the surrogate endpoint is closer to the treatment in terms of time and the biological mechanism that is being targeted (Korn et al., 2013).
