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Regarding: Webster-Clark M., et al. Alternative analytic and matching approaches for the prevalent new-user design: a simulation study. Pharmacoepidemiol Drug Saf, 31, pp. 796-803; 2022.
Pharmacoepidemiol Drug Saf
December 2022
Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Québec, Canada.
Alternative analytic and matching approaches for the prevalent new-user design: A simulation study.
Pharmacoepidemiol Drug Saf
July 2022
CERobs Consulting, LLC, Wrightsville Beach, North Carolina, USA.
Purpose: To describe the creation of prevalent new user (PNU) cohorts and compare the relative bias and computational efficiency of several alternative analytic and matching approaches in PNU studies.
Methods: In a simulated cohort, we estimated the effect of a treatment of interest vs a comparator among those who switched to the treatment of interest using the originally proposed time-conditional propensity score (TCPS) matching, standardized morbidity ratio weighting (SMRW), disease risk scores (DRS), and several alternative propensity score matching approaches. For each analytic method, we compared the average RR (across 2000 replicates) to the known risk ratio (RR) of 1.
To extend previous simulations on the performance of propensity score (PS) weighting and trimming methods to settings without and with unmeasured confounding, Poisson outcomes, and various strengths of treatment prediction (PS c statistic), we simulated studies with a binary intended treatment T as a function of 4 measured covariates. We mimicked treatment withheld and last-resort treatment by adding 2 "unmeasured" dichotomous factors that directed treatment to change for some patients in both tails of the PS distribution. The number of outcomes Y was simulated as a Poisson function of T and confounders.
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