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, 326 (7387), 472

Validity of Indirect Comparison for Estimating Efficacy of Competing Interventions: Empirical Evidence From Published Meta-Analyses


Validity of Indirect Comparison for Estimating Efficacy of Competing Interventions: Empirical Evidence From Published Meta-Analyses

Fujian Song et al. BMJ.


Objective: To determine the validity of adjusted indirect comparisons by using data from published meta-analyses of randomised trials.

Design: Direct comparison of different interventions in randomised trials and adjusted indirect comparison in which two interventions were compared through their relative effect versus a common comparator. The discrepancy between the direct and adjusted indirect comparison was measured by the difference between the two estimates.

Data sources: Database of abstracts of reviews of effectiveness (1994-8), the Cochrane database of systematic reviews, Medline, and references of retrieved articles.

Results: 44 published meta-analyses (from 28 systematic reviews) provided sufficient data. In most cases, results of adjusted indirect comparisons were not significantly different from those of direct comparisons. A significant discrepancy (P<0.05) was observed in three of the 44 comparisons between the direct and the adjusted indirect estimates. There was a moderate agreement between the statistical conclusions from the direct and adjusted indirect comparisons (kappa 0.51). The direction of discrepancy between the two estimates was inconsistent.

Conclusions: Adjusted indirect comparisons usually but not always agree with the results of head to head randomised trials. When there is no or insufficient direct evidence from randomised trials, the adjusted indirect comparison may provide useful or supplementary information on the relative efficacy of competing interventions. The validity of the adjusted indirect comparisons depends on the internal validity and similarity of the included trials.


Figure 1
Figure 1
Discrepancy between direct and adjusted indirect comparison defined as difference in estimated log relative risk (meta-analyses 1-39) or difference in estimated standardised mean difference (meta-analysis 40) or difference in estimated mean difference (meta-analyses 41-44): empirical evidence from 44 published meta-analyses (see webextra table A)
Figure 2
Figure 2
Statistical discrepancy (z value, calculated by dividing difference between direct and indirect estimates by its standard error (z=Δ/SE(Δ)) and number of trials used in indirect comparison
Figure 3
Figure 3
Combination of direct and adjusted indirect estimates in two meta-analyses

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