Abstract
A living systematic review (LSR) should keep the review current as new research evidence
emerges. Any meta-analyses included in the review will also need updating as new material
is identified. If the aim of the review is solely to present the best current evidence
standard meta-analysis may be sufficient, provided reviewers are aware that results
may change at later updates. If the review is used in a decision-making context, more
caution may be needed. When using standard meta-analysis methods, the chance of incorrectly
concluding that any updated meta-analysis is statistically significant when there
is no effect (the type I error) increases rapidly as more updates are performed. Inaccurate
estimation of any heterogeneity across studies may also lead to inappropriate conclusions.
This paper considers four methods to avoid some of these statistical problems when
updating meta-analyses: two methods, that is, law of the iterated logarithm and the
Shuster method control primarily for inflation of type I error and two other methods,
that is, trial sequential analysis and sequential meta-analysis control for type I
and II errors (failing to detect a genuine effect) and take account of heterogeneity.
This paper compares the methods and considers how they could be applied to LSRs.
Keywords
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Article info
Publication history
Published online: September 10, 2017
Accepted:
August 18,
2017
Footnotes
Funding: All the authors of this paper were funded to produce this research by a grant from the Cochrane Methods Innovation Fund. The Living Systematic Review Network is supported by funding from Cochrane and the Australian National Health and Medical Research Council (Partnership Project grant APP1114605). Georgia Salanti is supported by a Marie Skłodowska-Curie fellowship (MSCA-IF-703254).
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© 2017 Elsevier Inc. All rights reserved.
