Directions for new developments on statistical design and analysis of small population group trials

Ralf-Dieter Hilgers, Kit Roes, Nigel Stallard, IDeAl, Asterix and InSPiRe project groups, Corinne Alberti, Caroline van Baal, Norbert Benda, Egbert Biesheuvel, CarlFredrik Burmann, Malgorzata Bogdan, Emmanuelle Comets, Simon Day, Holger Dette, Alex Dmitrienko, Tim Friede, Alexandra Graf, Mats Karlsson, Armin Koch, Franz König, JohannaH van der Lee, Frederike Lentz, Jason Madan, Christoph Male, France Mentré, Frank Miller, Geert Molenberghs, Beat Neuenschwander, Martin Posch, Cor Oosterwijk, Christian Röver, Stephen Senn, Ferran Torres, Sarah Zohar, Ralf-Dieter Hilgers, Kit Roes, Nigel Stallard, IDeAl, Asterix and InSPiRe project groups, Corinne Alberti, Caroline van Baal, Norbert Benda, Egbert Biesheuvel, CarlFredrik Burmann, Malgorzata Bogdan, Emmanuelle Comets, Simon Day, Holger Dette, Alex Dmitrienko, Tim Friede, Alexandra Graf, Mats Karlsson, Armin Koch, Franz König, JohannaH van der Lee, Frederike Lentz, Jason Madan, Christoph Male, France Mentré, Frank Miller, Geert Molenberghs, Beat Neuenschwander, Martin Posch, Cor Oosterwijk, Christian Röver, Stephen Senn, Ferran Torres, Sarah Zohar

Abstract

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.

Keywords: EMA/CHMP Guideline on clinical trials in small populations; Rare disease; Small population clinical trials; Statistical analysis; Statistical design; Statistical methods.

Figures

Fig. 1
Fig. 1
Asterix approach to advance trial design in small populations
Fig. 2
Fig. 2
Exhibit of the IDeAl project broken down in the workpackages
Fig. 3
Fig. 3
Exhibit of the InSpiRe project broken down in the work packages

References

    1. Joppi R, Bertele V, Garattini S. Orphan drug development is progressing too slowly. Br J Clin Pharmacol. 2006;61(3):355–60. doi: 10.1111/j.1365-2125.2006.02579.x.
    1. EU. FP7-HEALTH-2013-INNOVATION-1. [Online] 2013. [Cited: 23 03 2016.] . Accessed 8 June 2016.
    1. Molster C, et al. Key outcomes from stakeholder workshops at a symposium to inform the development of an Australian national plan for rare diseases. Orphanet J Rare Dis. 2012;7:50. doi: 10.1186/1750-1172-7-50.
    1. Orphanet. Orphanet Report Series - List of rare diseases - listed in alphabetical number. [Online] December 2012. [Cited: February 1, 2013.] . Accessed 8 June 2016.
    1. Eurordis. Fact Sheet. [Online] 2007. [Cited: February 1, 2013.] . Accessed 8 June 2016.
    1. Colledge VL, Solly J. The rare disease challenge and how to promote a productive rare disease community: Case study of Birt-Hogg-Dube Symposia. Orphanet J Rare Dis. 2012;7:63. doi: 10.1186/1750-1172-7-63.
    1. Breithaupt C. Contribution to the treatment of rare diseases: orphan drugs. J Eur Medical Writers Assoc Write Stuff. 2009;18(1):21–3.
    1. EMA. Orphan Medicines Figures 2000. Orphan Medicines Figures 2000/2014 Update 1/1/2015. [Online] 01 01 2015. [Cited: 26 02 2015.] . Accessed 8 June 2016.
    1. irdirc. Current Results of Research. Current Results of Research. [Online] 2016. [Cited: 25 05 2016.] . Accessed 8 June 2016.
    1. CHMP. Guideline on clinical trials in small populations. [Online] 2007. [Cited: February 1, 2013.] . Accessed 8 June 2016.
    1. EMA. Concept paper on extrapolation of efficacy and safety in medicine development. [Online] 2012. [Cited: 1 February 2013.] . Accessed 8 June 2016.
    1. FDA. Rare Diseases: Common Issues in Drug Development Guidance for Industry. . [Online] 08 2015. [Cited: 28 02 2016.]. Accessed 8 June 2016.
    1. Karlsson, K E. Benefits of pharmacometric model-based design and dnalysis of clinical trials. Acta Universitatis Upsaliensis. 2010;133. . Accessed 8 June 2016.
    1. Barrett J. Pharmacometrics: a multidisciplinary field to facilitate critical thinking in drug development and rranslational research settings. J Clin Pharmacol. 2008;48:632. doi: 10.1177/0091270008315318.
    1. Burzykowski T, Molenberghs G, Buyse M. The Evaluation of Surrogate Endpoints. New York: Springer; 2005.
    1. pcori. Patient-Centered Outcomes Research Institute. Patient-Centered Outcomes Research Institute. [Online] 2016. [Cited: 25 may 2016.] . Accessed 8 June 2016.
    1. Frank L, Basch E, Selby JV. The PCORI perspective on patient-centered outcomes research. J Am Med Assoc. 2014;312(15):1513–4. doi: 10.1001/jama.2014.11100.
    1. Gargon E, et al. Choosing important health outcomes for comparative effectiveness research: a systematic review. PLoS One. 2014;9:6. doi: 10.1371/journal.pone.0099111.
    1. Kiresuk TJ, Sherman RE. Goal attainment scaling: A general method for evaluating comprehensive community mental health programs. Community Ment Health J. 1968;4(6):443–53. doi: 10.1007/BF01530764.
    1. Pocock SJ, Geller NL, Tsiatis AA. The analysis of multiple endpoints in clinical trials. Biometrics. 1987;43(3):487–98. doi: 10.2307/2531989.
    1. Posch M, Futschik A. A uniform improvement of Bonferroni-type tests by sequential tests. J Am Stat Assoc. 2008;103(481):299–308. doi: 10.1198/016214508000000012.
    1. Bretz F, et al. A graphical approach to sequentially rejective multiple test procedures. Stat Med. 2009;28(4):586–604. doi: 10.1002/sim.3495.
    1. eurordis. European Organisation for Rare Diseases.[Online] [Cited: 23 03 206.] . Accessed 8 June 2016.
    1. Kennes LN, et al. The impact of selection bias on test decisions in randomized clinical trials. Stat Med. 2011;30(21):2573–81.
    1. Bretz F, et al. Adaptive designs for confirmatory clinical trials. Stat Med. 2009;28(8):1181–217. doi: 10.1002/sim.3538.
    1. Gerss JW, Köppke W. Clincal trials and rare diseases. Adv Exp Med Biol. 2010;686:173–90. doi: 10.1007/978-90-481-9485-8_11.
    1. FDA. Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials. [Online] 2010. . Accessed 8 June 2016.
    1. Wästfelt M, Fadeel B, Henter JI. A journey of hope: lessons learned from studies on rare diseases and orphan drugs. J Intern Med. 2006;260(1):1–10. doi: 10.1111/j.1365-2796.2006.01666.x.
    1. van der Graaf R, Roes KC, van Delden JJ. Adaptive trials in clinical research: scientific and ethical issues to consider. JAMA. 2012;307(22):2379–80.
    1. Emanuel EJ, Wendler D, Grady C. What makes clinical research ethical? JAMA. 2000;283(20):2701–11. doi: 10.1001/jama.283.20.2701.
    1. Gupta S, et al. A framework for applying unfamiliar trial designs in studies of rare diseases. J Clin Epidemiol. 2011;64(10):1085–94. doi: 10.1016/j.jclinepi.2010.12.019.
    1. Cornu C, et al. Experimental designs for small randomized clinical trials: an algorithm for choice. Orphanet J Rare Dis. 2013;8:48. doi: 10.1186/1750-1172-8-48.

Source: PubMed

Sponsorer och medarbetare

Medicinska tillstånd

Läkemedelsinterventioner

3
Prenumerera