Effectiveness and cost-effectiveness of a nurse-delivered intervention to improve adherence to treatment for HIV : a pragmatic, multicentre, open-label, randomised clinical trial

This trial was funded from public money by the Netherlands Organisation for Health Research and Development (ZonMW; grant number 171002208). Aardex provided support on the development of the study website. We thank all the HIV nurses and physicians from the seven HIV clinics involved in the AIMS study for their input and collaboration (Academic Medical Centre, Slotervaart hospital, and St. Lucas-Andreas hospital, all in Amsterdam; the Leiden University Medical Centre, Leiden; HAGA hospital, The Hague; Erasmus Medical Centre, Rotterdam; and Isala clinic, Zwolle), the study participants, and the Stichting HIV Monitoring (SHM) for their support in accessing the SHM database for identifying patient inclusion criteria and developing the Markov model. Finally, we thank and remember Herman Schaalma (deceased) for his contribution to the study design and grant application.Peer reviewedPostprin

A semiparametric bivariate probit model for joint modeling of outcomes in STEMI patients

In this work we analyse the relationship among in-hospital mortality and a treatment effectiveness outcome in patients affected by ST-Elevation myocardial infarction. The main idea is to carry out a joint modeling of the two outcomes applying a Semiparametric Bivariate Probit Model to data arising from a clinical registry called STEMI Archive. A realistic quantification of the relationship between outcomes can be problematic for several reasons. First, latent factors associated with hospitals organization can affect the treatment efficacy and/or interact with patient’s condition at admission time. Moreover, they can also directly influence the mortality outcome. Such factors can be hardly measurable. Thus, the use of classical estimation methods will clearly result in inconsistent or biased parameter estimates. Secondly, covariate-outcomes relationships can exhibit nonlinear patterns. Provided that proper statistical methods for model fitting in such framework are available, it is possible to employ a simultaneous estimation approach to account for unobservable confounders. Such a framework can also provide flexible covariate structures and model the whole conditional distribution of the response