Causal Inference in Precision Medicine: Past, Current, and Future

Abstract

With recent advancement in basic science and technology, precision medicine has been advocated in medical community and influenced policymaking. Precision medicine aims to tailor medical treatments
according to patient characteristics, and it has gained a lot  of attention in modern biomedical research. The success of precision medicine crucially depends on the development of accurate and reliable statistical tools for making causal inference about the optimal treatment regime given the data collected from clinical trials or observational studies.  In this talk, I will review some  past and current statistical methodology for making causal inference in precision, particularly, using the covariate-specific treatment effect  (CSTE) curve, and discuss some future research directions.

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