Reflections on meta-analyses involving trials stopped early for benefit: Is there a problem and if so, what is it?

Dirk Bassler, Victor M. Montori, Matthias Briel, Paul Glasziou, Stephen D. Walter, Tim Ramsay, Gordon Guyatt

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

We review controversies associated with randomized controlled trials (RCTs) stopped early for apparent benefit (truncated RCTs or tRCTs) and present our groups' perspective. Long-established theory, simulations and recent empirical evidence demonstrate that tRCTs will on average overestimate treatment effects, and this overestimation may be large, particularly when tRCTs have small number of events. Theoretical considerations and simulations demonstrate that on average, meta-analyses of RCTs with appropriate stopping rules will lead to only trivial overestimation of treatment effects. However, tRCTs will disproportionally contribute to meta-analytic estimates when tRCTs occur early in the sequence of trials with few subsequent studies, publication of nontruncated RCTs is delayed, there is publication bias, or tRCTs result in a 'freezing' effect in which 'correcting' trials are never undertaken. To avoid applying overestimates of effect to clinical decision-making, clinicians should view the results of individual tRCTs with small sample sizes and small number of events with skepticism. Pooled effects from meta-analyses including tRCTs are likely to overestimate effect when there is a substantial difference in effect estimates between the tRCTs and the nontruncated RCTs, and in which the tRCTs have a substantial weight in the meta-analysis despite themselves having a relatively small number of events. Such circumstances call for sensitivity analyses omitting tRCTs.

Original languageEnglish (US)
Pages (from-to)159-168
Number of pages10
JournalStatistical Methods in Medical Research
Volume22
Issue number2
DOIs
StatePublished - Apr 2013

Keywords

  • Clinical trial methodology
  • overestimation of treatment effects
  • stopping rules
  • systematic reviews and meta-analyses
  • truncation of studies

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

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