Strategy for intention to treat analysis in randomised trials with missing outcome data

Ian R White, Nicholas J Horton, James Carpenter, Stuart J Pocock, Ian R White, Nicholas J Horton, James Carpenter, Stuart J Pocock

Abstract

Loss to follow-up is often hard to avoid in randomised trials. This article suggests a framework for intention to treat analysis that depends on making plausible assumptions about the missing data and including all participants in sensitivity analyses

Conflict of interest statement

Competing interests All authors have completed the unified competing interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare no support from any organisation for the submitted work; JC has undertaken paid consultancy for various drug companies; and no other relationships or activities that could appear to have influenced the submitted work.

Figures

https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4788306/bin/whii799700.f1_default.jpg
Fig 1 Possible ways to impute outcome measures at visit 9 for a hypothetical participant in the obesity trial who drops out after visit 4: main analysis (last value brought forward) and three sensitivity analyses (1 assumes participants lost to follow-up return to baseline weight; 2 assumes 50% of weight regained, and 3 assumes intervention group regains a greater proportion of weight than controls)

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Source: PubMed

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