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2016 ; 11
(1
): 78
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Directions for new developments on statistical design and analysis of small
population group trials
#MMPMID27301273
Hilgers RD
; Roes K
; Stallard N
Orphanet J Rare Dis
2016[Jun]; 11
(1
): 78
PMID27301273
show ga
BACKGROUND: 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. METHOD: 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. RESULTS: 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. CONCLUSION: 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.
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