Participant withdrawals were unusually distributed in randomized trials with integrity concerns: a statistical investigation

Mark J Bolland, Greg D Gamble, Alison Avenell* (Corresponding Author), David Cooper, Andrew Grey

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Objectives: Comparing observed and expected distributions of categorical outcome variables in randomized controlled trials (RCTs) has been previously used to assess publication integrity. We applied this technique to withdrawals from RCTs. Study Design and Setting: We compared the observed distribution of withdrawals with the expected binomial distribution in six sets of RCTs: four control sets and two sets with concerns about their publication integrity. Results: In the control data sets (n = 13, 115, 71, and 36 trials, respectively), the observed distributions of withdrawals were consistent with the expected distributions, both for the numbers of withdrawals per trial arm and for the differences in withdrawals between trial arms in two-arm RCTs. In contrast, in both sets of RCTs with concerns regarding publication integrity (n = 151 and 35 trials, respectively), there were striking differences between the observed and expected distributions of trial withdrawals. Two-arm RCTs from the two sets with publication integrity concerns were 2.6 (95% confidence interval 2.0–3.3) times more likely to have a difference of 0 or 1 withdrawals between trial arms than control RCTs (P < 0.001). Simulating a 50% higher rate of withdrawals in active treatment arms in the largest set of control RCTs still produced an observed distribution of withdrawals per trial arm consistent with the expected distribution. Conclusion: Comparing the observed and expected distribution of trial withdrawals may be a useful technique when considering publication integrity of a body of RCTs.

Original languageEnglish
Pages (from-to)22-29
Number of pages8
JournalJournal of Clinical Epidemiology
Early online date21 Nov 2020
Publication statusPublished - Mar 2021


  • Adverse events
  • Data integrity
  • Fabricated data
  • Research integrity
  • Statistical methods
  • Withdrawals


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