Statistical consideration about causal inference to obtain real-world evidence

Association is often observed in medical research, but causal inference is the ultimate goal of clinical study. The criteria for determining causality include association temporality, strength, consistency, specificity, coherence, dose-response relationship, biologic plausibility and experimental evidence. In order to obtain causality, there are many causal inference elements in clinical study design and analysis. This study analyzes the influence of confounders on causality, and discusses the causal inference elements in three important topics: randomization, analysis of data sets and subgroup analysis. Medical researches should be fully aware of the causal elements in clinical study, so as to currently understand the level of evidence that can be provided by study, and try to produce high-level medical evidence in practice work.