Skip Navigation


IJE Advance Access originally published online on September 29, 2008
International Journal of Epidemiology 2009 38(1):287-298; doi:10.1093/ije/dyn188
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
38/1/287    most recent
dyn188v2
dyn188v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Related articles in Int. J. Epidemiol.
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (2)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Brok, J.
Right arrow Articles by Gluud, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Brok, J.
Right arrow Articles by Gluud, C.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2008; all rights reserved.

Apparently conclusive meta-analyses may be inconclusive—Trial sequential analysis adjustment of random error risk due to repetitive testing of accumulating data in apparently conclusive neonatal meta-analyses

Jesper Brok*, Kristian Thorlund, Jørn Wetterslev and Christian Gluud

The Copenhagen Trial Unit, Center for Clinical Intervention Research, Department 3344, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

* Corresponding author: The Copenhagen Trial Unit, Center for Clinical Intervention Research, Department 3344, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark. E-mail: jbrok{at}ctu.rh.dk


  Abstract

Background Random error may cause misleading evidence in meta-analyses. The required number of participants in a meta-analysis (i.e. information size) should be at least as large as an adequately powered single trial. Trial sequential analysis (TSA) may reduce risk of random errors due to repetitive testing of accumulating data by evaluating meta-analyses not reaching the information size with monitoring boundaries. This is analogous to sequential monitoring boundaries in a single trial.

Methods We selected apparently conclusive (P ≤ 0.05) Cochrane neonatal meta-analyses. We applied heterogeneity-adjusted and unadjusted TSA on these meta-analyses by calculating the information size, the monitoring boundaries, and the cumulative Z-statistic after each trial. We identified the proportion of meta-analyses that did not reach the required information size and the proportion of these meta-analyses in which the Z-curve did not cross the monitoring boundaries.

Results Of 54 apparently conclusive meta-analyses, 39 (72%) did not reach the heterogeneity-adjusted information size required to accept or reject an intervention effect of 25% relative risk reduction. Of these 39, 19 meta-analyses (49%) were considered inconclusive, because the cumulative Z-curve did not cross the monitoring boundaries. The median number of participants required to reach the required information size was 1591 (range, 339–6149). TSA without heterogeneity adjustment largely confirmed these results.

Conclusions Many apparently conclusive Cochrane neonatal meta-analyses may become inconclusive when the statistical analyses take into account the risk of random error due to repetitive testing.

Keywords Meta-analysis, trial sequential analysis, random error, information size, sample size, heterogeneity

Accepted 13 August 2008


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?

Related articles in Int. J. Epidemiol.:

Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses?
Kristian Thorlund, P J Devereaux, Jørn Wetterslev, Gordon Guyatt, John P A Ioannidis, Lehana Thabane, Lise-Lotte Gluud, Bodil Als-Nielsen, and Christian Gluud
Int. J. Epidemiol. 2009 38: 276-286. [Abstract] [Full Text]  



This article has been cited by other articles:


Home page
 J Am Coll CardiolHome page
A. M. Clark, L. A. Savard, and D. R. Thompson
What is the strength of evidence for heart failure disease-management programs?
J. Am. Coll. Cardiol., July 28, 2009; 54(5): 397 - 401.
[Abstract] [Full Text] [PDF]

Home page
 Int J EpidemiolHome page
K. Thorlund, P J Devereaux, J. Wetterslev, G. Guyatt, J. P A Ioannidis, L. Thabane, L.-L. Gluud, B. Als-Nielsen, and C. Gluud
Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses?
Int. J. Epidemiol., February 1, 2009; 38(1): 276 - 286.
[Abstract] [Full Text] [PDF]

Home page
 Int J EpidemiolHome page
E. Nuesch and P. Juni
Commentary: Which meta-analyses are conclusive?
Int. J. Epidemiol., February 1, 2009; 38(1): 298 - 303.
[Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.