Improving the Efficiency of Subgroup Analysis in Randomized Controlled Trials with TMLE

TL;DR

This paper introduces two TMLE-based methods that enhance subgroup analysis in RCTs by borrowing information from non-subgroup participants, improving estimate precision without external data.

Contribution

The study develops and applies two novel TMLE estimators, TMLE-PR and A-TMLE, for more accurate subgroup effect estimation within trials, avoiding external bias.

Findings

A-TMLE provided significant risk reduction estimates for Black and Asian subgroups.

Both estimators improved the precision of subgroup treatment effect estimates.

The methods support regulatory decisions by enabling rigorous subgroup analysis without external data.

Abstract

Subgroup analyses within randomized controlled trials are often underpowered due to limited sample sizes. We address this challenge by leveraging trial participants outside the subgroup of interest to augment estimation within the subgroup. Specifically, we study two Targeted Maximum Likelihood Estimators (TMLEs) that borrow information from non-subgroup participants within the same trial: a TMLE with pooled regression (TMLE-PR) and an Adaptive Targeted Maximum Likelihood Estimator (A-TMLE). Both estimators enable information sharing without relying on any external real-world data, thereby capitalizing on key strengths of the trial: most importantly, the protection against bias afforded by the randomized treatment, but also harmonized data collection, and consistent treatment and outcome definitions. The general strategy proposed here directly advances the priorities of key regulatory agencies, including the FDA, by improving the precision of subgroup-specific treatment effect estimates without introducing external sources of bias, thereby facilitating rigorous inference to support equitable labeling, access, and post-market evaluation. In a case study based on analysis of data from a cardiovascular outcome trial (LEADER, NCT01179048), we estimate the risk reduction of major adverse cardiac events (MACE) under liraglutide treatment among Black and Asian subgroups -- each comprising less than 10\% of the trial population -- using the proposed estimators that borrow information from the remainder of the trial. Using A-TMLE, in particular, we find estimated absolute MACE risk reductions of 1.6, 1.5, and 1.5 percentage points among Asian participants and 2.1, 2.0, and 2.1 percentage points among Black participants at 365, 540, and 730 days, respectively, with 95\% confidence intervals excluding the null at each time point.