Directions for new developments on statistical design and analysis of small population group trials.
Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions.



Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible.



The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations.



The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.
Department of Medical Statistics, RWTH Aachen University, Pauwelsstr 30, D-52074, Aachen, Germany. rhilgers@ukaachen.de.
Ralf-Dieter
0000-0002-5945-1119
RD
Hilgers
Quality and Patient Safety, Biostatistics, UMC Utrecht, Utrecht, Netherlands.
Kit
K
Roes
Statistics and Epidemiology, Warwick Medical School, University of Warwick, Coventry, UK.
Nigel
N
Stallard
D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D006801:Humans; D044382:Population Groups; D035583:Rare Diseases
EMA/CHMP Guideline on clinical trials in small populations; Rare disease; Small population clinical trials; Statistical analysis; Statistical design; Statistical methods