gms | German Medical Science

53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

15. bis 18.09.2008, Stuttgart

Simpson's paradox visualized: The example of the Rosiglitazone meta-analysis

Meeting Abstract

Suche in Medline nach

  • Gerta Rücker - Institut für Medizinische Biometrie und Medizinische Informatik, Freiburg, Deutschland
  • Martin Schumacher - Institut für Medizinische Biometrie und Medizinische Informatik, Freiburg, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Stuttgart, 15.-19.09.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocMBIO1-1

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/meetings/gmds2008/08gmds048.shtml

Veröffentlicht: 10. September 2008

© 2008 Rücker et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Background

Simpson's paradox is sometimes referred to in the areas of epidemiology and clinical research. It can also be found in meta-analysis of randomized clinical trials. However, though readers are able to recalculate examples from hypothetical as well as real data, they may have problems to easily figure where it emerges from.

Methods

First, two kinds of plots are proposed to illustrate the phenomenon graphically, a scatter plot and a line graph. Subsequently, these can be overlaid, resulting in a overlay plot. The plots are applied to the recent large meta-analysis of adverse effects of rosiglitazone on myocardial infarction and to an example from the literature. A large set of meta-analyses is screened for further examples.

Results

As noted earlier by others, occurrence of Simpson's paradox in the meta-analytic setting, if present, is associated with imbalance of treatment arm size. This is well illustrated by the proposed plots. The rosiglitazone meta-analysis shows an effect reversion if all trials are pooled. In a sample of 157 meta-analyses, nine showed an effect reversion after pooling, though non-significant in all cases.

Conclusion

The plots give insight on how the imbalance of trial arm size works as a confounder, thus producing Simpson's paradox. Readers can see why meta-analytic methods must be used and what is wrong with simple pooling.


References

1.
Hanley JA, Theriault G. Simpson's paradox in meta-analysis. Epidemiology 2000;11(5):613.
2.
Cates CJ. Simpson's paradox and calculation of number needed to treat from meta-analysis. BMC Medical Research Methodology 2002; (2):1. Available at: http://www.biomedcentral.com/1471-2288/2/1 Externer Link
3.
Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular diseases. NEJM 2007;356:2457-71.