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1000 Titel
  • Directions for new developments on statistical design and analysis of small population group trials
1000 Autor/in
  1. Hilgers, Ralf-Dieter |
  2. Roes, Kit |
  3. Stallard, Nigel |
1000 Erscheinungsjahr 2016
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2016-06-14
1000 Erschienen in
1000 Quellenangabe
  • 11:78
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2016
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13023-016-0464-5 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908723/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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. RESULT: 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.
1000 Sacherschließung
lokal Statistical analysis
lokal Small population clinical trials
lokal Rare disease
lokal EMA/CHMP Guideline on clinical trials in small populations
lokal Statistical design
lokal Statistical methods
1000 Fachgruppe
  1. Medizin |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. http://orcid.org/0000-0002-5945-1119|https://frl.publisso.de/adhoc/creator/Um9lcywgS2l0|https://frl.publisso.de/adhoc/creator/U3RhbGxhcmQsIE5pZ2Vs
1000 Label
1000 Förderer
  1. European Union
1000 Fördernummer
  1. FP7 2007–2013; Health-F5-2013-603160; 602552; 602144
1000 Förderprogramm
  1. Seventh Framework Programme; Asterix project; IDEAL project; InSpiRe project
1000 Dateien
  1. Directions for new developments on statistical design and analysis of small population group trials
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6407631.rdf
1000 Erstellt am 2018-04-16T11:08:52.706+0200
1000 Erstellt von 281
1000 beschreibt frl:6407631
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet 2020-01-30T18:53:54.303+0100
1000 Objekt bearb. Wed Apr 18 10:42:22 CEST 2018
1000 Vgl. frl:6407631
1000 Oai Id
  1. oai:frl.publisso.de:frl:6407631 |
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1000 Sichtbarkeit Daten public
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