Econometric Issues in Prospective Economic Evaluations Alongside Clinical Trials: Combining the Nonparametric...

Area of Science:

• Health Economics
• Biostatistics
• Clinical Trials

Background:

• Prospective economic evaluations alongside clinical trials enhance cost-effectiveness analysis accuracy.
• Missing data and sampling uncertainty are key challenges in econometric analysis of trials.
• Substance use disorder intervention trials are particularly affected by missing data.

Approach:

• Reviewed statistical methods in 29 economic evaluations of substance use disorder interventions.
• Examined approaches to address missing data bias and sampling uncertainty.
• Assessed the combination of multiple imputation, inverse probability weighting, and nonparametric bootstrap.

Key Points:

• Multiple imputation and inverse probability weighting are recommended for missing data bias.
• Nonparametric bootstrap is recommended for uncertainty in cost and effectiveness.
• Limited understanding exists on combining these methods effectively.

Conclusions:

• Further research is needed on optimal combination strategies for addressing missing data and uncertainty.
• Clearer guidelines are required for robust economic evaluations in clinical trials.
• Improved methods will enhance the reliability of cost-effectiveness findings for interventions.