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Direct comparisons of the efficacy of competing interventions are not always available in the literature. This situation leads to the presence of clinically relevant "orphan comparisons" of therapeutic interventions which have never been compared head-to-head. To overcome this limitation, simple methods for indirect meta-analysis have been suggested. Nevertheless, their results are prone to bias when more than 1 indirect comparison is tested because of the likely duplication of data for some comparisons. In contrast, general linear models can be used to extend simple indirect meta-analysis beyond 1 indirect comparison by fitting to incomplete data using maximum likelihood within the framework of multitreatment comparisons. This study presents a tutorial application of general linear models to the comparative efficacy of several antidepressants in dysthymia (tricyclic antidepressants, selective serotonin reuptake inhibitors, and monoamine oxidase inhibitors. Working with previously published data comparing the efficacy of antidepressants with placebo, it is shown that tricyclic antidepressants and selective serotonin reuptake inhibitors present similar efficacy (odds ratio = 1.19, P = 0.37; relative risk = 1.10, P = 0.24; risk difference = 0.03, P = 0.53), whereas monoamine oxidase inhibitors outperform both tricyclic antidepressants and selective serotonin reuptake inhibitors, at least for some effect scales (odds ratio = 1.57, P = 0.05; relative risk = 1.25, P = 0.05; risk difference = 0.09, P = 0.08). This finding, which is an instance of a relevant orphan comparison and could not be obtained otherwise, could motivate the conduct of clinical trials or focused systematic reviews to support or refute its importance through appropriate head-to-head comparisons.