title: Experimental designs for small randomised clinical trials: an algorithm for choice.
abstract: BACKGROUND
  Small clinical trials are necessary when there are difficulties in recruiting enough patients for conventional frequentist statistical analyses to provide an appropriate answer. These trials are often necessary for the study of rare diseases as well as specific study populations e.g. children. It has been estimated that there are between 6,000 and 8,000 rare diseases that cover a broad range of diseases and patients. In the European Union these diseases affect up to 30 million people, with about 50% of those affected being children. Therapies for treating these rare diseases need their efficacy and safety evaluated but due to the small number of potential trial participants, a standard randomised controlled trial is often not feasible. There are a number of alternative trial designs to the usual parallel group design, each of which offers specific advantages, but they also have specific limitations. Thus the choice of the most appropriate design is not simple.
  
  
  METHODS
  PubMed was searched to identify publications about the characteristics of different trial designs that can be used in randomised, comparative small clinical trials. In addition, the contents tables from 11 journals were hand-searched. An algorithm was developed using decision nodes based on the characteristics of the identified trial designs.
  
  
  RESULTS
  We identified 75 publications that reported the characteristics of 12 randomised, comparative trial designs that can be used in for the evaluation of therapies in orphan diseases. The main characteristics and the advantages and limitations of these designs were summarised and used to develop an algorithm that may be used to help select an appropriate design for a given clinical situation. We used examples from publications of given disease-treatment-outcome situations, in which the investigators had used a particular trial design, to illustrate the use of the algorithm for the identification of possible alternative designs.
  
  
  CONCLUSIONS
  The algorithm that we propose could be a useful tool for the choice of an appropriate trial design in the development of orphan drugs for a given disease-treatment-outcome situation.
authors.affiliation: Hôpital Louis Pradel, Centre d'Investigation Clinique, INSERM CIC201/UMR5558, 28, Avenue du Doyen Lépine, Bron 69677 cedex, France. catherine.cornu@chu-lyon.fr.
authors.forename: Catherine
authors.initials: C
authors.lastname: Cornu
authors.forename: Behrouz
authors.initials: B
authors.lastname: Kassai
authors.forename: Roland
authors.initials: R
authors.lastname: Fisch
authors.forename: Catherine
authors.initials: C
authors.lastname: Chiron
authors.forename: Corinne
authors.initials: C
authors.lastname: Alberti
authors.forename: Renzo
authors.initials: R
authors.lastname: Guerrini
authors.forename: Anna
authors.initials: A
authors.lastname: Rosati
authors.forename: Gerard
authors.initials: G
authors.lastname: Pons
authors.forename: Harm
authors.initials: H
authors.lastname: Tiddens
authors.forename: Sylvie
authors.initials: S
authors.lastname: Chabaud
authors.forename: Daan
authors.initials: D
authors.lastname: Caudri
authors.forename: Clément
authors.initials: C
authors.lastname: Ballot
authors.forename: Polina
authors.initials: P
authors.lastname: Kurbatova
authors.forename: Anne-Charlotte
authors.initials: AC
authors.lastname: Castellan
authors.forename: Agathe
authors.initials: A
authors.lastname: Bajard
authors.forename: Patrice
authors.initials: P
authors.lastname: Nony
authors.forename: Leon
authors.initials: L
authors.lastname: Aarons
authors.forename: Agathe
authors.initials: A
authors.lastname: Bajard
authors.forename: Clément
authors.initials: C
authors.lastname: Ballot
authors.forename: Yves
authors.initials: Y
authors.lastname: Bertrand
authors.forename: Frank
authors.initials: F
authors.lastname: Bretz
authors.forename: Daan
authors.initials: D
authors.lastname: Caudri
authors.forename: Charlotte
authors.initials: C
authors.lastname: Castellan
authors.forename: Sylvie
authors.initials: S
authors.lastname: Chabaud
authors.forename: Catherine
authors.initials: C
authors.lastname: Cornu
authors.forename: Frank
authors.initials: F
authors.lastname: Dufour
authors.forename: Cornelia
authors.initials: C
authors.lastname: Dunger-Baldauf
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Dupont
authors.forename: Roland
authors.initials: R
authors.lastname: Fisch
authors.forename: Renzo
authors.initials: R
authors.lastname: Guerrini
authors.forename: Vincent
authors.initials: V
authors.lastname: Jullien
authors.forename: Behrouz
authors.initials: B
authors.lastname: Kassaï
authors.forename: Patrice
authors.initials: P
authors.lastname: Nony
authors.forename: Kayode
authors.initials: K
authors.lastname: Ogungbenro
authors.forename: David
authors.initials: D
authors.lastname: Pérol
authors.forename: Gérard
authors.initials: G
authors.lastname: Pons
authors.forename: Harm
authors.initials: H
authors.lastname: Tiddens
authors.forename: Anna
authors.initials: A
authors.lastname: Rosati
authors.forename: Corinne
authors.initials: C
authors.lastname: Alberti
authors.forename: Catherine
authors.initials: C
authors.lastname: Chiron
authors.forename: Polina
authors.initials: P
authors.lastname: Kurbatova
authors.forename: Rima
authors.initials: R
authors.lastname: Nabbout
mesh_terms: D000465:Algorithms; D018592:Cross-Over Studies; D005062:European Union; D006801:Humans; D016032:Randomized Controlled Trials as Topic; D012107:Research Design