To evaluate the effect of medication exposure, we estimated conditional logistic regression models stratified by subject and modeled the risk of poisoning as a function of drug exposure by day. We first built a crude model containing benzodiazepine prescription status as the only predictor variable. We then built additional models that included predictor variables for both benzodiazepine and buprenorphine prescription status. Simultaneous inclusion of benzodiazepine and buprenorphine permitted us to model additive and/or interactive effects of benzodiazepines and buprenorphine in association with drug-related poisonings. SSRIs were included in our models as an active comparator analysis. Subgroup analyses were conducted to assess the effect of buprenorphine treatment days, in comparison to days without treatment, on drug-related poisoning among those who received benzodiazepine prescriptions and those who did not. Controls for both calendar time and time from index poisoning were included using cubic spline methods described further in the eMethods 3. Several sensitivity analyses were conducted to evaluate the possibility of persistent user bias and assess the robustness of our findings to alternative time samplings (eFigure 1, eMethods 3–4, eTable 5).
