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Open Access Review

Sample size calculations in pediatric clinical trials conducted in an ICU: a systematic review

Stavros Nikolakopoulos1*, Kit C B Roes1, Johanna H van der Lee2 and Ingeborg van der Tweel1

Author Affiliations

1 Department of Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Str. 6.131, PO Box 85500, 3508 Utrecht, GA, The Netherlands

2 Clinical Research Unit, Woman-Child Center, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

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Trials 2014, 15:274  doi:10.1186/1745-6215-15-274

Published: 8 July 2014


At the design stage of a clinical trial, several assumptions have to be made. These usually include guesses about parameters that are not of direct interest but must be accounted for in the analysis of the treatment effect and also in the sample size calculation (nuisance parameters, e.g. the standard deviation or the control group event rate). We conducted a systematic review to investigate the impact of misspecification of nuisance parameters in pediatric randomized controlled trials conducted in intensive care units. We searched MEDLINE through PubMed. We included all publications concerning two-arm RCTs where efficacy assessment was the main objective. We included trials with pharmacological interventions. Only trials with a dichotomous or a continuous outcome were included. This led to the inclusion of 70 articles describing 71 trials. In 49 trial reports a sample size calculation was reported. Relative misspecification could be calculated for 28 trials, 22 with a dichotomous and 6 with a continuous primary outcome. The median [inter-quartile range (IQR)] overestimation was 6.9 [-12.1, 57.8]% for the control group event rate in trials with dichotomous outcomes and -1.5 [-15.3, 5.1]% for the standard deviation in trials with continuous outcomes. Our results show that there is room for improvement in the clear reporting of sample size calculations in pediatric clinical trials conducted in ICUs. Researchers should be aware of the importance of nuisance parameters in study design and in the interpretation of the results.

clinical trials; sample size; power; standard deviation; event rate; study design