Publication bias and small-study effects magnified effectiveness of antipsychotics but their relative ranking remained invariant

Abstract

Objectives: Publication bias (PB) may seriously compromise inferences from meta-analyses. The aim of this article was to assess the potential effect of small-study effects and PB on the recently estimated relative effectiveness and ranking of pharmacological treatments for schizophrenia.

Study design and setting: We used a recently published network of 167 trials involving 36,871 patients and comparing the effectiveness of 15 antipsychotics and placebo. We used novel visual and statistical methods to explore if smaller trials are associated with larger treatment effects and a selection model to explore if the probability of trial publication is associated with the magnitude of effect. We conducted a network meta-analysis of the published evidence as our primary analysis and used a sensitivity analysis considering low, moderate, and severe selection bias (that corresponds to the number of unpublished trials) with an aim to evaluate robustness of point estimates and ranking. We explored whether placebo-controlled and head-to-head trials are associated with different levels of PB.

Results: We found that small placebo-controlled trials exaggerated slightly the efficacy of antipsychotics, and PB was not unlikely in the evidence based on placebo-controlled trials; however, ranking of antipsychotics remained robust.

Conclusion: The total evidence comprises many head-to-head trials that do not appear to be prone to small-study effects or PB, and indirect evidence appears to "wash out" some of the biases in the placebo-controlled trials.

Keywords: Bayesian hierarchical model; Indirect comparison; Network meta-analysis; Publication bias; Selection model; Small study effect.