Simulation-Guided Planning of a Target Trial Emulated Cluster Randomized Trial for Mass Small-Quantity Lipid Nutrient Supplementation Combined with Expanded Program on Immunization in Rural Niger

TL;DR

This study demonstrates how simulation-guided design within target trial emulation can effectively plan non-randomized cluster trials, ensuring robust statistical analysis for evaluating nutritional interventions in rural Niger.

Contribution

It introduces a simulation-based approach to inform the design and analysis of non-randomized cluster trials within the target trial emulation framework.

Findings

Beta-regression controlled type I error and had adequate power

IPTW had poor power despite controlling type I error

Simulation-guided design improved trial planning accuracy

Abstract

Background: Target trial emulation (TTE) that applies trial design principles to improve the analysis of non-randomized studies is increasingly being used. Applications of TTE to emulate cluster randomized trials (RCTs) have been limited. This study explored how to integrate simulation-guided design into the TTE framework to inform planning of a non-randomized cluster trial. Methods: We performed simulations to prospectively plan data collection of a non-randomized study emulating a village-level cluster RCT when cluster-randomization was infeasible. The planned study will assess the impact of mass distribution of nutritional supplements embedded within an existing immunization program to improve pentavalent vaccination rates among children 12-24 months old in Niger. The design included covariate-constrained random selection of villages for outcome ascertainment at follow-up. Simulations used baseline census data on pentavalent vaccination rates and cluster-level covariates to compare the type I error rate and power of four statistical methods: beta-regression; quasi-binomial regression; inverse probability of treatment weighting (IPTW); and naive Wald test. Results: Of the four analytic methods considered, only IPTW and beta-regression controlled the type I error rate at 0.05, but IPTW yielded poor statistical power. Beta-regression that showed adequate statistical power was chosen as our primary analysis. Conclusions: Adopting simulation-guided design principles within TTE can enable robust planning of a group-level non-randomized study emulating a cluster RCT. Lessons from this study also apply to TTE planning of individually-RCTs.