Multicriteria benefit-risk assessment using network meta-analysis
Objective: To enable multicriteria benefit-risk (BR) assessment of any number of alternative treatments using all available evidence from a network of clinical trials. Study Design and Setting: We design a general method for multicriteria decision aiding with criteria measurements from Mixed Treatment Comparison (MTC) analyses. To evaluate the method, we apply it to BR assessment of four second-generation antidepressants and placebo in the setting of a published peer-reviewed systematic review. Results: The analysis without preference information shows that placebo is supported by a wide range of possible preferences. Preference information provided by a clinical expert showed that although treatment with antidepressants is warranted for severely depressed patients, for mildly depressed patients placebo is likely to be the best option. It is difficult to choose between the four antidepressants, and the results of the model indicate a high degree of uncertainty. Conclusions: The designed method enables quantitative BR analysis of alternative treatments using all available evidence from a network of clinical trials. The preference-free analysis can be useful in presenting the results of an MTC considering multiple outcomes.
- Benefit-risk analysis
- Mixed treatment comparison
- Network meta-analysis
- Stochastic multi-criteria acceptability analysis
- Multi-criteria decision aiding
- Second-generation antidepressants