Meta-analyses and antidepressant prescribing.

Further to your recent Editorial by Nutt (2009), we fully support the notion of using the best available evidence to improve the prescribing of antidepressants. However, we are concerned that the meta-analysis as conducted by Cipriani et al. (2009) is not sufficiently robust to allow a ranking of antidepressants in terms of efficacy and tolerability, in particular as suggested in Figure 1 of Nutt (2009). Cipriani et al. (2009) have performed a network meta-analysis based on 117 clinical trials of 12 antidepressants. From their analysis they draw conclusions about all possible pair-wise comparisons of treatments. We believe this meta-analysis should not be used as a foundation for conclusive prescribing guidance and a number of other authors have voiced similar opinions in their reply to Cipriani et al.’s original publication (Jefferson et al., 2009). Their warnings about the validity of this network meta-analysis were based on the limited representativeness, the heterogeneity, and the selectivity of the included data. They also emphasized the limitations of indirect comparisons in general and criticized the choice of the categorical parameters for efficacy ( 50% response rate) and tolerability (drop-out rate) and the restriction of the treatment duration (8 weeks). Since there is a clear risk of drawing false conclusions from this publication we would like to illustrate some key weaknesses by addressing the data on duloxetine as an example, although we feel that the issues raised herein are equally relevant to all of the other antidepressants included in the analysis by Cipriani et al. In this meta-analysis, direct within-study comparisons are included between duloxetine and only 3 of the other 11 antidepressants, and for 1 of these 3 there are very few patients. Most of the inferences about duloxetine are therefore being drawn from indirect comparisons across studies, more than for all of the other antidepressants. This is an issue if there is relevant ‘‘incoherence’’ in the network of 66 pair-wise comparisons, which remains uncertain. In clinical terms, the combination of some of these studies in the meta-analysis is questionable. Included are placebo-controlled and non-placebo-controlled studies, open-label studies and double-blind studies, studies of severely depressed hospitalized patients and studies of mild to moderately depressed outpatients, studies in the elderly and studies in all adults, and studies run up to 18 years apart, so confounding may be an issue. In particular, there was a larger proportion of the duloxetine studies that included a placebo arm (75%) than for most of the other treatments (30% overall). Results have not been provided separately for placebo-controlled and non-placebo-controlled studies, although this may be an important confounder because early drop-out rate is likely to be higher in placebo-controlled studies. On the other hand, treatment arms on doses below the therapeutic range were not excluded from the meta-analysis. Three of the eight duloxetine studies were early studies and included treatment arms on duloxetine 40mg/day, a dose below the defined therapeutic range. The use of indirect comparisons clearly has an advantage in that one can make comparisons for which head-to-head data are lacking, but it also has the risk of resulting in incorrect conclusions. For example, the Cipriani et al. analysis comes to a different conclusion in the comparison between duloxetine and venlafaxine compared with a head-to-head study (Perahia et al. (2008), available on-line at the time of the meta-analysis but not included): the odds ratio (OR) for the intention to treat (ITT) response rate from the head-to-head study was closer to 1 and not significant (OR 0.86 with 95% confidence interval (CI): 0.64–1.17), while the network analysis, based entirely on indirect comparisons,