Reporting of sample size calculations in analgesic clinical trials: ACTTION systematic review.

UNLABELLED: Sample size calculations determine the number of participants required to have sufficiently high power to detect a given treatment effect. In this review, we examined the reporting quality of sample size calculations in 172 publications of double-blind randomized controlled trials of noninvasive pharmacologic or interventional (ie, invasive) pain treatments published in European Journal of Pain, Journal of Pain, and Pain from January 2006 through June 2013. Sixty-five percent of publications reported a sample size calculation but only 38% provided all elements required to replicate the calculated sample size. In publications reporting at least 1 element, 54% provided a justification for the treatment effect used to calculate sample size, and 24% of studies with continuous outcome variables justified the variability estimate. Publications of clinical pain condition trials reported a sample size calculation more frequently than experimental pain model trials (77% vs 33%, P < .001) but did not differ in the frequency of reporting all required elements. No significant differences in reporting of any or all elements were detected between publications of trials with industry and nonindustry sponsorship. Twenty-eight percent included a discrepancy between the reported number of planned and randomized participants. This study suggests that sample size calculation reporting in analgesic trial publications is usually incomplete. Investigators should provide detailed accounts of sample size calculations in publications of clinical trials of pain treatments, which is necessary for reporting transparency and communication of pre-trial design decisions.

PERSPECTIVE: In this systematic review of analgesic clinical trials, sample size calculations and the required elements (eg, treatment effect to be detected; power level) were incompletely reported. A lack of transparency regarding sample size calculations may raise questions about the appropriateness of the calculated sample size.