STATISTICAL APPLICATIONS IN PEDIATRIC ENDOCRINOLOGY: A SIMULATION ON METFORMIN EFFECT ON HBA1c IN HIGH-RISK ADOLESCENTS
Shi, W.
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AO_SCPLOWBSTRACTC_SCPLOWMetformin has been increasingly used off-label in adolescents with type 1 diabetes (T1D) or prediabetic conditions to improve glycemic control. Despite clinical trials suggesting modest improvements in HbA1c, evidence remains mixed and methodologically limited. This paper introduces a simulation framework to evaluate advanced causal inference estimators--including Targeted Maximum Likelihood Estimation (TMLE), Double Machine Learning (DML), and Bayesian Causal Forests (BCF)--for estimating the causal effect of metformin on HbA1c reduction in high-risk adolescents. The framework incorporates realistic confounding structures based on empirical data and provides theoretical derivations for estimator properties.
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