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Outcome reporting bias in clinical trials

Published online by Cambridge University Press:  11 April 2011

Eleonora Esposito ,
Andrea Cipriani  and
Corrado Barbui
Eleonora Esposito*
Affiliation:
Department of Medicine and public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Verona (Italy)
Andrea Cipriani
Affiliation:
Department of Medicine and public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Verona (Italy)
Corrado Barbui
Affiliation:
Department of Medicine and public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Verona (Italy)
*
Address for correspondence: Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Verona (Italy) Fax: +39-045-8027498 E-mail: eleonora.esposito@univr.it
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Extract

Randomised controlled trials (RCTs) are designed and powered to measure one single outcome, called primary outcome (Sibbald & Roland, 1998; Barbui et al., 2007). The primary outcome is the pre-specified outcome of greatest clinical importance and is usually the one used in the sample size calculation (Accordini, 2007). In addition to the primary outcome, RCTs may have several other outcomes, called secondary outcomes. In contrast with the analysis of the primary outcome, the analysis of secondary outcomes and its interpretation may be complicated by at least two factors:

  1. 1) the trial may not have enough statistical power to detect differences (so it is possible to incur in a type II error, that is failing to see a difference that is present);

  2. 2) increasing the number of secondary outcomes generates the problem of multiplicity of analyses, that is the proliferation of possible comparisons in a trial (and increasing the number of comparisons increases the possibility to incur in a type I error, that is detecting significant differences by chance). For all these reasons, the results of the analysis of primary outcomes is considered less susceptible to bias than the analysis of secondary outcomes.

Keywords

clinical trialsoutcomesmethodsstatistics
Type
ABC of Methodology
Information
Epidemiology and Psychiatric Sciences , Volume 18 , Issue 1 , March 2009 , pp. 17 - 18
Copyright
Copyright © Cambridge University Press 2009

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References

Accordini, S. (2007). An introduction to sample size calculations in clinical trials. Epidemiologia e Psichiatria Sociale 16, 299–301.CrossRefGoogle ScholarPubMed
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