Évaluation de la performance du score de propension à hautes dimensions dans le cadre d’études observationnelles québécoises
Propensity scores (PS) are frequently used to adjust for confounders leading to indication bias. However, PS are limited by the fact that they can only adjust for measured and known confounders. High-dimensional propensity scores (hdPS), a specific type of PS, select which variables they adjust for by means of a standardized selection algorithm. Thanks to the use of this selection algorithm, hdPS could potentially adjust for all type of confounders. This thesis aims to evaluate the hdPS’s performance in the adjustment for indication bias in the context of an observational study focussing on the potential diabetogenic effect of statins. The first article’s aim was to identify if the exposure to statins was associated with the risk of diabetes. Results of this article suggest that exposure to statins is associated with an increase in the risk of diabetes and that this association is dose-dependent and reversible in nature. After having identified this association, we examined if the hdPS outperforms the PS in the adjustment for indication bias. Both methods’ performance were compared by means of the obtained adjusted measures of associations and by means of the standardized differences regarding 19 characteristics following the creation of two matched sub-cohorts (each matched on either patients’ PS or patients’ hdPS). Results of this second article identify that the performance of either method could not be differentiated by means of the first approach but that, based on the second approach, the hdPS outperforms the PS in its adjustment for indication bias. The last article aimed to evaluate if the hdPS could adjust for known confounders which were hidden to the selection algorithm. Results of this third article suggest that the hdPS method can adjust for at least some hidden confounders and that it could potentially adjust for some unmeasured confounders. As a whole, this thesis suggests that the hdPS method could be superior to the PS method in its ability to adjust for indication bias and supports its use in future observational studies using medico-administrative databases.
Score de propension Propensity scores High-dimensional propensity scores Indication bias Statins Diabetes