The Dutch list of essential drugs for undergraduate medical education: A modified Delphi study.

Aims: Prescribing errors among junior doctors are common in clinical practice because many lack prescribing competence after graduation. This is in part due to inadequate education in clinical pharmacology and therapeutics (CP&T) in the undergraduate medical curriculum. To support CP&T education, it is important to determine which drugs medical undergraduates should be able to prescribe safely and effectively without direct supervision by the time they graduate.

The Development of Practice Recommendations for Drug-Disease Interactions by Literature Review and Expert Opinion.

Background: Drug-disease interactions negatively affect the benefit/risk ratio of drugs for specific populations. In these conditions drugs should be avoided, adjusted, or accompanied by extra monitoring. The motivation for many drug-disease interactions in the Summary of Product Characteristics (SmPC) is sometimes insufficiently supported by (accessible) evidence.

Handling categories properly: a novel objective of clinical research.

A major objective of clinical research is to study outcome effects in subgroups. Such effects generally have stepping functions that are not strictly linear. Analyzing stepping functions in linear models thus raises the risk of underestimating the effects.

Cardiovascular research: data dispersion issues.

Biological processes are full of variations and so are responses to therapy as measured in clinical research. Estimators of clinical efficacy are, therefore, usually reported with a measure of uncertainty, otherwise called dispersion. This study aimed to review both the flaws of data reports without measure of dispersion and those with over-dispersion.

Time-dependent predictors in clinical research, performance of a novel method.

Individual patients' predictors of survival may change across time, because people may change their lifestyles. Standard statistical methods do not allow adjustments for time-dependent predictors. In the past decade, time-dependent factor analysis has been introduced as a novel approach adequate for the purpose.