Experimental designs for small randomised clinical trials: an algorithm for choice

Abstract

BackgroundSmall clinical trials are necessary when there are difficulties in recruiting enough patients for conventional frequentist statistical analyses to provide an appropriate answer. These trials are often necessary for the study of rare diseases as well as specific study populations e.g. children. It has been estimated that there are between 6,000 and 8,000 rare diseases that cover a broad range of diseases and patients. In the European Union these diseases affect up to 30 million people, with about 50% of those affected being children. Therapies for treating these rare diseases need their efficacy and safety evaluated but due to the small number of potential trial participants, a standard randomised controlled trial is often not feasible. There are a number of alternative trial designs to the usual parallel group design, each of which offers specific advantages, but they also have specific limitations. Thus the choice of the most appropriate design is not simple.MethodsPubMed was searched to identify publications about the characteristics of different trial designs that can be used in randomised, comparative small clinical trials. In addition, the contents tables from 11 journals were hand-searched. An algorithm was developed using decision nodes based on the characteristics of the identified trial designs.ResultsWe identified 75 publications that reported the characteristics of 12 randomised, comparative trial designs that can be used in for the evaluation of therapies in orphan diseases. The main characteristics and the advantages and limitations of these designs were summarised and used to develop an algorithm that may be used to help select an appropriate design for a given clinical situation. We used examples from publications of given disease-treatment-outcome situations, in which the investigators had used a particular trial design, to illustrate the use of the algorithm for the identification of possible alternative designs.ConclusionsThe algorithm that we propose could be a useful tool for the choice of an appropriate trial design in the development of orphan drugs for a given disease-treatment-outcome situation.

Orphan Drugs: Getting Arms around Rare Diseases

“…Biased assessment of the outcome attrition bias, which is the biased occurrence and handling of deviations from protocol and loss-to-follow-up Outcome evaluation in a blinded manner Table 2: Major systematic bias types and used prevention methods, (adapted from published articles of Cornu in 2013 [4] and Griggs in 2009 [13].…”

“…• Whether the outcome is reversible, • Whether the treatment response is likely to be rapid and • Whether investigators seek to minimize the time participants are receiving placebo [4].…”

“…There is no "one size fits all" design for rare diseases. There are a number of trial designs that can be employed, each with its specific advantages and specific limitations [4]. Often the regulatory agencies can be engaged as partners throughout the development process to best leverage the various incentives and designations [48,49].…”

“…Nonetheless, these trials are necessary for the rare diseases studies, as well as specific pediatric, geriatric, individually tailored therapies, regional subpopulations [4].…”

Coping with small populations of patients in clinical trials

“…There are no special methods for coping with small populations of patients in clinical trials, as acknowledged in the Committee for Medicinal Products for Human Use (CHMP) guideline [1]. There are, however, many different types of clinical study designs and approaches to increase the efficiency of clinical trials where patient numbers are limited [2][3][4][5].…”