Clinical Epidemiology | 2019

Randomized clinical trials with run-in periods: frequency, characteristics and reporting

 
 
 

Abstract


Background Run-in periods are occasionally used in randomized clinical trials to exclude patients after inclusion, but before randomization. In theory, run-in periods increase the probability of detecting a potential treatment effect, at the cost of possibly affecting external and internal validity. Adequate reporting of exclusions during the run-in period is a prerequisite for judging the risk of compromised validity. Our study aims were to assess the proportion of randomized clinical trials with run-in periods, to characterize such trials and the types of run-in periods and to assess their reporting. Materials and methods This was an observational study of 470 PubMed-indexed randomized controlled trial publications from 2014. We compared trials with and without run-in periods, described the types of run-in periods and evaluated the completeness of their reporting by noting whether publications stated the number of excluded patients, reasons for exclusion and baseline characteristics of the excluded patients. Results Twenty-five trials reported a run-in period (5%). These were larger than other trials (median number of randomized patients 217 vs 90, P=0.01) and more commonly industry trials (11% vs 3%, P<0.01). The run-in procedures varied in design and purpose. In 23 out of 25 trials (88%), the run-in period was incompletely reported, mostly due to missing baseline characteristics. Conclusion Approximately 1 in 20 trials used run-in periods, though much more frequently in industry trials. Reporting of the run-in period was often incomplete, precluding a meaningful assessment of the impact of the run-in period on the validity of trial results. We suggest that current trials with run-in periods are interpreted with caution and that updates of reporting guidelines for randomized trials address the issue.

Volume 11
Pages 169 - 184
DOI 10.2147/CLEP.S188752
Language English
Journal Clinical Epidemiology

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