TY - JOUR
T1 - Reflections on meta-analyses involving trials stopped early for benefit
T2 - Is there a problem and if so, what is it?
AU - Bassler, Dirk
AU - Montori, Victor M.
AU - Briel, Matthias
AU - Glasziou, Paul
AU - Walter, Stephen D.
AU - Ramsay, Tim
AU - Guyatt, Gordon
PY - 2013/4
Y1 - 2013/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84876720420&partnerID=8YFLogxK
U2 - 10.1177/0962280211432211
DO - 10.1177/0962280211432211
M3 - Article
C2 - 22170891
AN - SCOPUS:84876720420
SN - 0962-2802
VL - 22
SP - 159
EP - 168
JO - Statistical Methods in Medical Research
JF - Statistical Methods in Medical Research
IS - 2
ER -