Publicaties

Standardization and harmonization of data collection in studies on traumatic brain injury (TBI) is of paramount importance for meta-analyses across studies. Nearly 10 years ago, the first set of Common Data Elements for TBI (TBI-CDEs v1) were introduced to achieve these goals. The TBI-CDEs version 2 were developed in 2012 to broaden the approach to all ages, injury severity, and phases of recovery. We aimed to quantify the degree of ...

Critical Data Studies (CDS) explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact ...

Introduction: Hydroxyethyl starch (HES) is a commonly used colloid in critically ill patients. However, its safety has been questioned in recent studies and meta-analyses. Methods: We re-evaluated prospective randomised controlled trials (RCT) from four meta-analyses published in 2013 that compared the effect of HES with crystalloids in critically ill patients, focusing on the adherence to 'presumably correct indication'. Regarding the ...

Early, accurate diagnosis of disease can dramatically improve prognosis. Clinical diagnostic model research attempts to optimize early diagnosis by designing diagnostic models based on variables obtained by the least invasive means. Diagnostic model research currently involves a complex, multidisciplinary workflow involving data collection by clinicians on the one hand, and data preprocessing and machine-learning by machine-learning experts on ...

INTRODUCTION: At tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL. Thus, better understanding the large interindividual variability in tamoxifen pharmacokinetics (PK) is crucial. By applying non-linear mixed-effects (NLME) modeling to a pooled 'real-world' clinical PK database, we aimed to (i) dissect several levels of variability and identify factors predictive for ...

The purpose of this work is to describe the effect of duloxetine on functioning as measured by the Sheehan disability scale (SDS) compared with placebo in patients with major depressive disorder (MDD). Pooled data from six randomized, parallel, double-blind, placebo-controlled duloxetine studies in adult MDD patients were analyzed at the short-term (7-13 weeks) and the long-term (>24 weeks) endpoint. The primary variable was the SDS total ...

In this thesis, we introduced and explored different modeling techniques for incomplete and/or clustered data. In part I of the thesis, models to handle incomplete data are explored, while in part II of the thesis a dataset concerning pneumococcal disease in a health economic context was analyzed. In the following sections, some concluding remarks are presented.

Chronic use of inhaled anticholinergics by patients with chronic obstructive pulmonary disease (COPD) has raised long-term safety concerns, particularly cardiovascular. Glycopyrronium is a once-daily anticholinergic with greater receptor selectivity than previously available agents.

Statistical analysis often extends beyond the data available. This is especially true when data are incompletely recorded because ad hoc as well as model-based approaches are rooted not only in the observed data and the mechanism governing missingness, but also in the unobserved given the observed data. Other instances of this phenomenon include but are not limited to censored time-to-event data, random effects models, and latent class ...