Abstract
Whenever possible, standard methodological approaches should be applied in the design and analysis of a clinical trial that warrant adequate informative value. However, there are circumstances when the number of experimental subjects is unavoidably small. In such circumstances it is justified to consider abandoning standard statistical methodology in place of alternative approaches. Performing a small clinical trial however it should be pointed out, that a such trial can never be as meaningful and provide as much evidence as a larger trial. In the present text, basic concepts are presented, that apply to small clinical trials in general. Moreover, several specific methodological approaches are presented, that either enhance the efficiency of standard statistical procedures or evolve from the idea of abandoning classical paradigms in the design and analysis of clinical trials. Within the scope of the former approach, (Bayesian) adaptive randomisation, group sequential (adaptive) designs, repeated measurement designs for longitudinal data, and meta-analyses are illustrated and discussed. The latter approach comprises alternative strategies such as (non-randomised) risk-based allocation designs, statistical prediction designs, ranking and selection designs, as well as the application of Bayesian statistics.
References
Chow S-C, Chang M (2006) Adaptive design methods in clinical trials. Chapman & Hall/CRC, Boca Raton
Committee for Medicinal Products for Human Use (CHMP) (2006) Guideline on clinical trials in small populations (CHMP/EWP/83561/2005). European Medicines Agency, London
Cook TD, DeMets DL (2008) Introduction to statistical methods for clinical trials. Chapman & Hall/CRC, Boca Raton
Cytel Inc. (2005) StatXact® 7 PROCs For SAS® Users. Statistical Software for Exact Nonparametric Inference, User Manual. Cytel Statistical Software & Services, Cambridge
Dahmen G, Ziegler A (2004) Generalized estimating equations in controlled clinical trials: hypotheses testing. Biometr J 46(2):214–232
Evans CH Jr, Ildstad ST (eds) (2001) Small clinical trials: issues and challenges. National Academy Press, Washington, DC
Fayers PM, Ashby D, Parmar MKB (1997) Tutorial in biostatistics: Bayesian data monitoring in clinical trials. Stat Med 16(12):1413–1430
Finkelstein MO, Levin B, Robbins H (1996) Clinical and prophylactic trials with assured new treatment for those at greater risk. Part I. Introduction. Am J Public Health 86:691–695
Finkelstein MO, Levin B, Robbins H (1996) Clinical and prophylactic trials with assured new treatment for those at greater risk. Part II. Examples. Am J Public Health 86:696–705
Giles FJ, Kantarjian HM, Cortes JE et al (2003) Adaptive randomized study of idarubicin and cytarabine versus troxacitabine and cytarabine versus troxacitabine and idarubicin in untreated patients 50 years or older with adverse karyotype acute myeloid leukemia. J Clin Oncol 21(9):1722–1727
Hart A (2001) Making sense of statistics in healthcare. Radcliffe Medical Press, Abingdon
Jennison C, Turnbull BW (2000) Group sequential methods: applications to clinical trials. Chapman & Hall/CRC, Boca Raton
Molenberghs G, Verbeke G (2005) Models for discrete longitudinal data. Springer, New York
Rochon J (1998) Application of GEE procedures for sample size calculations in repeated measures experiments. Stat Med 17(14):1643–1658
Schulze R (2004) Meta-analysis: a comparison of approaches. Hogrefe & Huber, Göttingen
Spiegelhalter DJ, Abrams KR, Myles JP (2004) Bayesian approaches to clinical trials and health-care evaluation. Wiley, New York
Verbeke G, Molenberghs G (2000) Linear mixed models for longitudinal data. Springer, New York
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Gerß, J.W.O., Köpcke, W. (2010). Clinical Trials and Rare Diseases. In: Posada de la Paz, M., Groft, S. (eds) Rare Diseases Epidemiology. Advances in Experimental Medicine and Biology, vol 686. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9485-8_11
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DOI: https://doi.org/10.1007/978-90-481-9485-8_11
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