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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Statistics in Medici...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Statistics in Medicine
Article . 1987 . Peer-reviewed
License: Wiley Online Library User Agreement
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Problems in the medical interpretation of overviews

Authors: R E, Wittes;

Problems in the medical interpretation of overviews

Abstract

AbstractRecently, investigators have combined formally the results of all available randomized trials testing a particular therapy to get a better estimate of the effectiveness of that treatment than any single trial can provide in isolation. It seems intuitively clear, however, that formal overviews will yield medically meaningful results only under certain defined circumstances. First, the treatments that are pooled should be similar enough that any inferences about the effect of treatment will refer to something more specific than an idealized ‘average therapy’. Second, patient selection in the pooled trials should be uniform enough that the inferences will be applicable to some defined patient population. Third, although the potential biases of excluding trials from pooling are substantial, so are the problems of including trials whose execution might be flawed in a biased manner; it is not clear what can be done about this, since biased studies probably cannot be identified in an unambiguous manner. Finally, it would seem prudent to consider the medical context during which trials were performed; it is probably not reasonable to assume that quantitative measures of treatment effect obtained by pooling studies from different eras of treatment will be an accurate reflection of what current treatment can achieve, even if everything else is held constant. For these reasons the quantitative measures of treatment effect that derive from formal overviews may have little relevance to medical decision‐making. Overviews might still be useful in indicating the general direction of a treatment effect, provided that no qualitative interactions are present. Although such interactions may seem improbable, some recent examples from the cancer literature suggest that their presence cannot be ruled out a priori.

Related Organizations
Keywords

Clinical Trials as Topic, Random Allocation, Drug Therapy, Evaluation Studies as Topic, Research Design, Population, Humans

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Average
Top 1%
Top 10%
Related to Research communities
Cancer Research
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