If it would reflect subGDC-0199 clinical disease and identify patients susceptible for arterial injury and cardiovascular events it would clearly improve individualized long-term management of patients at risk. The present study has been performed in in-patients. Despite of this pre-selection bias the prevalence of cardiovascular events in the study population is similar to the reported data in outpatient cohorts. In order to improve the disease activity score as a predictive tool we will have to explore which variables change early in the course of arteriosclerosis, particularly in its asymptomatic stage. All these hypotheses and the deduced mathematical models have to be tested in prospective clinical trials and need to be confirmed in a population based cohort. Finally, the individual empiric data-based disease profile could be used to test the efficacy of preventive or therapeutic Fulvestrant interventions to treat arteriosclerosis. For example, any successful intervention leading to weight loss and reduced abdominal obesity may lead to quite obvious changes in a patient��s phenotype and may even affect associated risk factors as shown by others. The color coded disease profile may serve as a surrogate marker for the intuitive visualization of early responses to therapy. Conditions that prevent or precipitate the development of symptomatic arteriosclerosis evolve with time and may also be different in various regions of the world. Therefore, this databased, empiric clinical disease profile may differ in ten or twenty years from now and it may be different in medical centers in Asia, America or Africa. For the same reason, the reference range that defines this disease profile for symptomatic arteriosclerosis cannot be simply adopted by another institution. It should first be established on site. The quartile distribution of the different variables may represent a common ground for standardized comparisons of the disease phenotype and the activity score determined in different institutions. The optimal set of data, the size of the patient cohort and the time window for reference range calculations needs to be determined in future studies. Novel biomarkers will be tested for their capacity to improve the diagnostic accuracy of the clinical disease activity score presented herein. In conclusion, affordable, available and accessible clinical data collected in a standardized manner and analyzed according to the rules of differential display result in an accurate description of the phenotype of patients with a complex disease, e.g. symptomatic arteriosclerosis. Data-based empiric clinical profiling visualizes an individual patient��s disease phenotype quantitatively and it may form the basis of personalized risk assessments and interventions. Several human specific pathogens are able to engage CEACAM family members to colonize mucosal surfaces.