The impact of different strategies for modeling associations between medications at low doses and health outcomes: a simulation study and practical application to postpartum opioid use

Abstract

Pharmacoepidemiological studies commonly examine the association between drug dose and adverse health outcomes. In situations where no safe dose exists, the choice of modeling strategy can lead to identification of an apparent safe low dose range in the presence of a non-linear relationship or due to the modeling strategy forcing a linear relationship through a dose of 0. We conducted a simulation study to assess the performance of several regression approaches to model the drug dose-response curve at low doses in a setting where no safe range exists, including the use of a (1) linear dose term, (2) categorical dose term, and (3) natural cubic spline terms. Additionally, we introduce and apply an expansion of prior work related to modeling dose-response curves at low and infrequently used doses in the setting of no safe dose (“spike-at-zero” and “slab-and-spline”). Furthermore, we demonstrate and empirically assess the use of these regression strategies in a practical scenario examining the association between the dose of the initial postpartum opioid prescribed after vaginal delivery and the subsequent total dose of opioids prescribed in the entire postpartum period among a cohort of opioid-naïve women with a vaginal delivery enrolled in a State Medicaid program (2007-2014).