Introduction

Any study exploring specific research questions requires to test well-defined hypotheses that efficiently translate these questions into measurable quantities. To attribute differences in outcomes between two or more groups to their respective different exposure levels, the flagship comparative approach is the randomised clinical trial (RCT).

An RCT is not always feasible, as is the case if the exposure of interest cannot be reasonably randomised, such as smoking, age, family or personal history of a disease. A cohort study is the next most rigorous approach to answer cause and effect questions, sharing with an RCT the advantage of prospective follow-up. In addition, observational studies are more suitable to answer certain important questions for an intervention such as detecting rare or late adverse effects of treatments.1

A comparative study that lacks the randomisation component should not also lag behind in other rigorous requirements that are customarily expected of randomised studies. The value of the scientific evidence produced by an observational study lies equally heavily on how explicit its design characteristics are in the protocol, and how faithfully the study implementation followed the study protocol design. Guidelines to that effect are available and should be respected.2

One of the most crucial parameters in a study is the choice of the end point that would best translate the objective and capture the effect of interest. It is often the case that several relevant end points are of comparable importance and it might be difficult to select the most appropriate one. In those situations, the union of several end points, a composite end point (CE), is used as the primary end point (PE) of interest. A key advantage of a CE is that it provides a better description of a disease process.3 For example, in the cardiovascular literature, efficacy of interventions is …