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Letter: potential selection bias in the real‐world comparison of ustekinumab versus vedolizumab as a second‐line treatment for Crohn’s disease

Editors, A recently published article authored by Lenti et al. puts forward the findings from a propensity scorematched comparison of ustekinumab versus vedolizumab as a secondline treatment for Crohn’s disease based on realworld data.1 Ustekinumab was found to have more clinical effectiveness at 14 weeks and no statistically significant difference at 52 weeks compared with vedolizumab. We think that addressing some of the following issues would enhance the scientific contribution of the study. The authors applied propensity scorematched analysis to control for measured confounding and properly presented the plot of frequency distribution of the propensity scores within each treatment group. The authors also assessed the balance of covariates after propensity scores matching using standardised mean differences. However, there is a potential problem of selection bias and inappropriate use of propensity scores in the study design. In this study, the ustekinumab cohort comprised individuals who initiated the treatment between January 2017 and January 2020, whereas patients in the vedolizumab cohort initiated it between August 2014 and June 2017. Considering ustekinumab was approved by the FDA in September 2016,2 some of the patients in the vedolizumab cohort had theoretically zero probability of using ustekinumab. Furthermore, because some individuals in the ustekinumab cohort had used vedolizumab before (28% of the cohort), these patients have zero probability of initiating vedolizumab. However, this was not accounted for in the analysis. Dealing with these points would allow us to get a more clear interpretation of the study. In the context of nonexperimental studies using realworld data such as pharmacoepidemiology, the active comparator, new user study design has been proposed to minimise the potential for bias.3 Regardless of the methodologic development, it is worth noting that use of propensity score methods alone does not correct the bias introduced by the study design or measurement error of variables, and one example of such bias is selection bias.4 In future studies for similar research questions, we suggest that authors recruit both treatment groups from patients without previous exposure to either medication and utilise the study design such as active comparator, new user design to achieve treatment equipoise.