Parametric time-to-onset models were developed to improve causality assessment of adverse drug reactions from antidiabetic drugs

Abstract

ObjectivesThe aim of this study was to investigate whether the time to onset (TTO) of common adverse drug reactions (ADRs) of antidiabetic drugs could be modeled using parametric distributions and whether these TTO distributions were dependent on patient characteristics. Furthermore, information relevant for daily clinical practice was to be obtained. Study Design and SettingWe performed an exploratory TTO modeling study, using a cohort of diabetes mellitus patients. Four parametric distributions (exponential, lognormal, gamma, and Weibull) were compared in terms of their goodness of fit. Covariates that could influence the TTO were investigated. In addition, TTO mean and median values were summarized for use in clinical practice. ResultsOverall, the gamma distribution provided the best goodness of fit, although differences with the Weibull distribution were negligible in some instances. No differences in TTO distributions between different antidiabetic drugs for a given ADR were found. The TTO was influenced by suspected concomitant medication for metformin-associated diarrhea. Mean and median TTO values were similar for different drug–ADR combinations. ConclusionOur study shows that the TTO of common ADRs associated with antidiabetic drugs can be modeled using the gamma or Weibull distribution. Furthermore, clinically relevant information about these ADRs can be obtained.