Clinical trials and rare diseases: a way out of a conundrum

Abstract

Currently, clinical trials tend to be individually funded and applicants must include a power calculation in their grant request. However, conventional levels of statistical precision are unlikely to be obtainable prospectively if the trial is required to evaluate treatment of a rare disease. This means that clinicians treating such diseases remain in ignorance and must form their judgments solely on the basis of (potentially biased) observational studies, experience, and anecdote. Since some unbiased evidence is clearly better than none, this state of affairs should not continue. However, conventional (frequentist) confidence limits are unlikely to exclude a null result, even when treatments differ substantially. Bayesian methods utilise all available data to calculate probabilities that may be extrapolated directly to clinical practice. Funding bodies should therefore fund a repertoire of small trials, which need have no predetermined end, alongside standard larger studies. ### : the problem Randomised clinical trials have become the standard method to assess clinical effectiveness when benefits are modest but worth while. They are more reliable than other methods1 and have solved some clinical questions conclusively--for example, the effectiveness of adjuvant treatment in early breast cancer. Clinical questions are most easily answeredwhen a disease is fairly common and the outcome of interest has a high risk of occurring. It is not surprising that randomised controlled trials have provided fairly conclusive results about the treatment of such conditions as acute myocardial infarction and the common cancers and that these results have formed the basis of clinical guidelines and audit standards. When diseases are rare and benefits modest, however, clinical trials, as currently conceived, have little to contribute. This is because they cannot be expected to provide a “definitive” answer--that is, they cannot be expected to detect or exclude clinically worthwhile differences between treatments with standard levels of statistical confidence. Hence they are not …