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A Dose–effect Network Meta-analysis Model with Application in Antidepressants Using Restricted Cubic Splines by Tasnim Hamza; Toshi A Furukawa; Nicola Orsini; Andrea Cipriani; Cynthia P Iglesias; Georgia Salanti is a Mathematics article available to read on EtoBox.
What is A Dose–effect Network Meta-analysis Model with Application in Antidepressants Using Restricted Cubic Splines about?
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 t
Who reads A Dose–effect Network Meta-analysis Model with Application in Antidepressants Using Restricted Cubic Splines?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- Tasnim Hamza; Toshi A Furukawa; Nicola Orsini; Andrea Cipriani; Cynthia P Iglesias; Georgia Salanti
- Publisher
- SAGE Publications
- Published
- 2022
- Language
- EN
- Field
- Mathematics (Physical Sciences)