MEB-seminarium: "Cumulative effects of time-varying exposures: new methods and applications in pharmaco-epidemiology"
Talare: Michal Abrahamovicz, McGill University, Montreal
Sammanfattning: An accurate assessment of the safety or effectiveness of drugs in longitudinal cohort studies requires defining an etiologically correct time-varying exposure model, which specifies how previous drug use affects the hazard of the event of interest. To account for the dosage, duration and timing of past exposures, we proposed a flexible weighed cumulative exposure (WCE) model : WCE(τ|x(t), t<τ) = ∑w(τ–t)[x(t)] where τ is the current time when the hazard is evaluated; x(t) represents the vector of past drug doses, at times t< τ; and the function w(τ–t) assigns importance weights to past doses, depending on the time elapsed since the dose was taken (τ–t). The function w(τ–t) is modeled using cubic regression B-splines. The estimated WCE(τ) is then included as a time-dependent covariate in the Cox’s PH model. Likelihood ratio tests are used to compare w(τ–t) against the standard un-weighted cumulative dose model, and to test the Ho of no association . Recently, the WCE model was extended to flexible Marginal Structural modeling (MSM) with IPT weights . The accuracy of the estimates and tests is assessed in simulations. The applications are illustrated by re-assessing the associations of (a) glucocorticoids and infections, (b) benzodiazepines and fall-related injuries, and (c) didanosine and cardiovascular risks in HIV (MSM analysis).Contact person: Marie Reilly