CAMO project start meeting

In healthcare, the approval of new treatments is based on systematically collected data regarding the effectiveness and safety of medical interventions (e.g., drugs). Typically, a single measurement is defined in a clinical study as the “primary endpoint”—the measurement that is of primary importance in assessing effectiveness (e.g., weight loss within a specific period during a nutrition-related treatment). However, often multiple measurements are of interest in order to capture the full range of (positive) effects of an intervention simultaneously (e.g., quality of life, pain, etc.). Suitable methods for such statistical analyses already exist – however, they have the disadvantage that they cannot account for imbalanced distributions of certain characteristics (e.g., age, gender, disease features) between groups of patients in a clinical study.

The project “CAMO – Covariate adjustment for multivariate outcomes” (https://www.fwf.ac.at/forschungsradar/10.55776/PIN9834224) has the aim of tackling this challenge by developing novel methods for data analysis. At a project kick-off meeting organized by Georg Zimmermann (LINK), the cooperation partners from the universities of Hasselt, Leuven, and Salzburg met in Vienna on October 10/11 to define the next steps and set goals, particularly regarding the relevance for related EU projects in the field of “Rare Diseases” https://erdera.org/ https://realised-ihi.eu/), where Dr. Zimmermann’s team also plays a key role in methodological research.