Overview of methods for comparing the efficacies of drugs in the absence of head-to-head clinical trial data - PubMed (original) (raw)

Review

Overview of methods for comparing the efficacies of drugs in the absence of head-to-head clinical trial data

Hansoo Kim et al. Br J Clin Pharmacol. 2014 Jan.

Abstract

In most therapeutic areas, multiple drug options are increasingly becoming available, but there is often a lack of evidence from head-to-head clinical trials that allows for direct comparison of the efficacy and/or safety of one drug vs. another. This review provides an introduction to, and overview of, common methods used for comparing drugs in the absence of head-to-head clinical trial evidence. Naïve direct comparisons are in most instances inappropriate and should only be used for exploratory purposes and when no other options are possible. Adjusted indirect comparisons are currently the most commonly accepted method and use links through one or more common comparators. Mixed treatment comparisons (MTCs) use Bayesian statistical models to incorporate all available data for a drug, even data that are not relevant to the comparator drug. MTCs reduce uncertainty but have not yet been widely accepted by researchers, nor drug regulatory and reimbursement authorities. All indirect analyses are based on the same underlying assumption as meta-analyses, namely that the study populations in the trials being compared are similar.

Keywords: adjusted indirect comparison; mixed treatment comparison; naïve direct comparison.

© 2013 The British Pharmacological Society.

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Figures

Figure 1

Figure 1

Conceptualization of the methods to compare the relative efficacies of drugs (or other interventions)

Figure 2

Figure 2

Illustration of uncertainty in a hypothetical adjusted indirect comparison. Two hypoglycaemic drugs, A and B, have been assessed with respect to reduction in blood glucose. Drug A was compared with drug C in a head-to-head clinical trial and drug B with drug C in another. Point estimates and uncertainty ranges of the differences in blood glucose change are illustrated. In the adjusted indirect comparison of A vs. B using C as a common comparator, the uncertainties in the pairwise comparisons of A vs. C and B vs. C are additive on the mmol l−1 scale

Figure 3

Figure 3

Conceptualization of a mixed treatment comparison undertaken by Ribeiro et al. [11], who investigated the impact of various statin doses (high, intermediate or low) and placebo on major cardiovascular events using evidence from 47 trials. Lines indicate the intervention groups that had been directly compared in the trials

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