Sample size slippages in randomised trials: exclusions and the lost and wayward

Lancet. 2002 Mar 2;359(9308):781-5. doi: 10.1016/S0140-6736(02)07882-0.

Abstract

Proper randomisation means little if investigators cannot include all randomised participants in the primary analysis. Participants might ignore follow-up, leave town, or take aspartame when instructed to take aspirin. Exclusions before randomisation do not bias the treatment comparison, but they can hurt generalisability. Eligibility criteria for a trial should be clear, specific, and applied before randomisation. Readers should assess whether any of the criteria make the trial sample atypical or unrepresentative of the people in which they are interested. In principle, assessment of exclusions after randomisation is simple: none are allowed. For the primary analysis, all participants enrolled should be included and analysed as part of the original group assigned (an intent-to-treat analysis). In reality, however, losses frequently occur. Investigators should, therefore, commit adequate resources to develop and implement procedures to maximise retention of participants. Moreover, researchers should provide clear, explicit information on the progress of all randomised participants through the trial by use of, for instance, a trial profile. Investigators can also do secondary analyses on, for instance, per-protocol or as-treated participants. Such analyses should be described as secondary and non-randomised comparisons. Mishandling of exclusions causes serious methodological difficulties. Unfortunately, some explanations for mishandling exclusions intuitively appeal to readers, disguising the seriousness of the issues. Creative mismanagement of exclusions can undermine trial validity.

MeSH terms

  • Bias
  • Follow-Up Studies
  • Humans
  • Outcome Assessment, Health Care / statistics & numerical data
  • Patient Dropouts / statistics & numerical data*
  • Randomized Controlled Trials as Topic / statistics & numerical data*
  • Sample Size