Cost-Effectiveness Analyses for Sequential Multiple Assignment Randomized Trials

Area of Science:

• Biostatistics
• Health Economics
• Clinical Trial Design

Background:

• Sequential Multiple Assignment Randomized Trials (SMARTs) are increasingly used in clinical research.
• Cost-effectiveness analysis (CEA) is often proposed for adaptive strategies within SMARTs.
• Incremental Cost-Effectiveness Ratios (ICERs) are commonly used to assess cost-effectiveness.

Purpose of the Study:

• To present an estimation and inference procedure for cost-effectiveness measures of embedded dynamic treatment regimes in SMART designs.
• To introduce a targeted maximum likelihood estimator (TMLE) for ICERs in SMARTs.
• To demonstrate the application of these methods using a real-world HIV care adherence trial.

Main Methods:

• Development of a targeted maximum likelihood estimator (TMLE) for ICERs.
• Utilization of influence curve-based inference for statistical analysis.
• Simulation studies to evaluate the performance of the proposed methods.
• Application to the Adaptive Strategies for Preventing and Treating Lapses of Retention in HIV Care (ADAPT-R) trial.

Main Results:

• The study presents an estimation and inference procedure for ICERs in SMARTs.
• The proposed TMLE with influence curve-based inference is illustrated through simulations.
• Estimated ICERs with inference are presented for embedded regimes in the ADAPT-R trial.
• This work contributes novel cost-effectiveness analysis results from a SMART.

Conclusions:

• The developed methods provide a robust framework for cost-effectiveness analysis in SMARTs.
• This research facilitates better decision-making regarding adaptive treatment strategies.
• The findings are particularly relevant for optimizing interventions in HIV care adherence programs.