Cost Effectiveness Analyses for Sequential Multiple Assignment Randomized Trials

TL;DR

This paper introduces a new statistical method for estimating cost effectiveness of adaptive treatment strategies within SMART trials, demonstrated through HIV care adherence analysis.

Contribution

It presents a targeted maximum likelihood estimator for ICERs in SMARTs, enabling more accurate cost effectiveness analysis of embedded regimes.

Findings

Proposed a new estimator for ICERs in SMARTs.

Validated the method with simulations.

Applied the method to HIV care adherence trial.

Abstract

Sequential multiple assignment randomized trials (SMARTs) have grown in popularity in recent years, and many of their study protocols propose conducting a cost effectiveness analysis of the adaptive strategies embedded within them. The cost effectiveness of these regimes is often proposed to be assessed using incremental cost effectiveness ratios (ICERs). In this paper, we present an estimation and inference procedure for such cost effectiveness measures for the embedded dynamic treatment regimes within a SMART design. In particular, we describe a targeted maximum likelihood estimator for the ICER of a SMART's embedded regimes with influence curve-based inference. We illustrate the performance of these methods using simulations. Throughout, we use as illustration a cost effectiveness analysis for the Adaptive Strategies for Preventing and Treating Lapses of Retention in HIV Care (ADAPT-R; NCT02338739) trial, presenting estimated ICERs (with inference) for embedded regimes aimed at increasing HIV care adherence. This manuscript is one of the first to present cost effectiveness analysis results from a SMART.