Effect of smoking on lung cancer: A causal inference approach

Abstract

Smoking is associated with an increased chance of developing lung cancer. Three causal inference methods, backdoor adjustment, front-door adjustment, and counterfactual are used to analyze observational data on smoking, lung cancer, and related risks factors. Backdoor adjustment fails to allow for possible presence of unobserved confounders, which is merited by front-door adjustment. Counterfactual harnesses individual patient statistics to establish causal relationships between smoking and cancer on the individual level, so as to evaluate lung cancer risks after changes in individual smoking habits. Results by different methodology are in good agreement and showcase a strong causation between smoking and lung cancer at both group and individual level.