BOX 3-1

Evidence for Causal Relationships

  • Strength of association

  • Dose–response relationship

  • Plausibility: plausible biological mechanism

  • Consistency: replication in different settings using different methods

  • Elimination of alternative explanations for the observed association

SOURCE: Hill, 1965.

BENEFITS AND LIMITATIONS OF META-ANALYSES

The evidence presented by the FDA to support a black box warning for the use of antidepressants in children and adolescents has several limitations, Greenhouse said. In its meta-analysis, the FDA relied on 24 randomized placebo-controlled trials with roughly 4,600 children and adolescents. None of the individual trials found completed suicides. The trials were designed to determine the efficacy of drugs for treating various disorders such as depression, anxiety, and attention deficit hyperactivity disorder. Greenhouse pointed out that the study populations consisted of young people with different disorders. The efficacy endpoints were different, as were the antidepressant medications and classes of medications, he said. The outcome of greatest interest to the FDA was suicidality, which in this case included suicide behavior and ideation. There were 87 cases reporting suicide behavior or ideation, assessed retrospectively. The graphic depiction used in the FDA’s meta-analysis, the forest plot, revealed that only one study of antidepressants and suicidality found a significant relationship, the TADS (Treatment of Adolescents with Depression Study) (Figure 3-1). Nevertheless, the overall result of the meta-analysis was an odds ratio of about 2 (OR = 2.0, 95% CI 1.3–3.1) using a fixed-effect model. A random effects model generated a similar result.

The strength of using a meta-analysis is that it provides the means to pool data for study of a rare event. A randomized controlled trial (RCT) could never alone have enough subjects under study because of the rarity of suicidality, according to Greenhouse. Meta-analyses also provided an opportunity to look at heterogeneity across studies using study-level variables. That gave the FDA the opportunity to look at the relationship



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