B. Propensity score regression In the second analysis the investigators will construct a sample of patients balanced on covariates and risk factors using a propensity score. The investigators will construct propensity scores using a logistic regression of the actual treatment received on the covariates described above. Therefore, each participant's propensity score will be their conditional probability (odds) of receiving varenicline versus nicotine replacement therapy. The investigators will match each patient receiving varenicline to another patient receiving nicotine replacement therapy with the closest propensity score on a ratio of 1:1 using a nearest neighbour algorithm with no replacement, and matching will be restricted to the common support region. Patients outside the common support region are those prescribed varenicline with propensity scores higher than any patient prescribed nicotine replacement therapy and vice versa. The investigators will estimate hazard ratios of the outcomes using the propensity score matched sample using Cox-regressions using the same entry and exit information as the conventional Cox-regression analysis described above.