4.6 Review

A dose-effect network meta-analysis model with application in antidepressants using restricted cubic splines

Journal

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/09622802211070256

Keywords

Evidence synthesis; multiple treatments; splines; dose-response; meta-regression

Funding

  1. European Union [825162]
  2. National Institute for Health Research (NIHR) Oxford Cognitive Health Clinical Research Facility
  3. NIHR Research Professorship [RP-2017-08-ST2-006]
  4. NIHR Oxford and Thames Valley Applied Research Collaboration
  5. NIHR Oxford Health Biomedical Research Centre [BRC-1215-20005]

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In this paper, the authors propose a suite of network meta-analysis models that incorporate the dose-effect relationship using restricted cubic splines. They apply these models to a network of aggregate data about the efficacy of antidepressants and placebo for depression. The results show that all antidepressants are more efficacious than placebo after a certain dose, and the authors also identify the dose level at which each antidepressant's effect exceeds that of placebo and estimate the dose beyond which the effect of antidepressants no longer increases. The authors also find that studies with small sample size tend to exaggerate antidepressant efficacy for several drugs.
Network meta-analysis has been used to answer a range of clinical questions about the preferred intervention for a given condition. Although the effectiveness and safety of pharmacological agents depend on the dose administered, network meta-analysis applications typically ignore the role that drugs dosage plays in the results. This leads to more heterogeneity in the network. In this paper, we present a suite of network meta-analysis models that incorporate the dose-effect relationship using restricted cubic splines. We extend existing models into a dose-effect network meta-regression to account for study-level covariates and for groups of agents in a class-effect dose-effect network meta-analysis model. We apply our models to a network of aggregate data about the efficacy of 21 antidepressants and placebo for depression. We find that all antidepressants are more efficacious than placebo after a certain dose. Also, we identify the dose level at which each antidepressant's effect exceeds that of placebo and estimate the dose beyond which the effect of antidepressants no longer increases. When covariates were introduced to the model, we find that studies with small sample size tend to exaggerate antidepressants efficacy for several of the drugs. Our dose-effect network meta-analysis model with restricted cubic splines provides a flexible approach to modelling the dose-effect relationship in multiple interventions. Decision-makers can use our model to inform treatment choice.

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