Heart failure is common in Europe and its prevalence is increasing as our population ages. Despite major improvements in care since the early 90s, it is still related to a poor prognosis, an impaired quality of life and high health care costs. Many new therapies have failed to improve outcome further. One obvious reason is that the response to treatment is not homogenous. Treatment may need to be tailored to the individual patient. BIOSTAT-CHF aims to identify patients with a poor outcome, despite currently recommended therapy using information on demographics, gender, existing biomarkers, genetics and proteomics. Both genomic and proteomic analyses recently underwent major technical improvements, resulting in genome-wide analyses and detection of low abundance proteins. In BIOSTAT-CHF an index cohort of 2500 patients hospitalized with acute decompensated heart failure, will be recruited after initial stabilization. Treatment will be optimized according to the heart failure guidelines of the European Society of Cardiology with diuretics, ACE-inhibitors, betablockers and aldosterone antagonists. When patients are optimally treated, any change in symptoms and exercise tolerance will be evaluated. Patients will then be followed up for a mean of 18 months, and mortality and heart failure hospitalizations will be recorded. By using a systems biology approach, incorporating information from demographic, biomarker, genomic, proteomic, and the initial response to therapy, a risk prediction model will be designed, identifying patients with a poor outcome on currently recommended therapy. This model will then be validated in a real-life cohort of 2500 chronic heart failure patients. BIOSTAT-CHF will therefore be a major step towards personalized medicine. Identifying patients with a poor outcome on currently recommended therapy might lead to further development of targeted therapies, eventually leading to improvements in outcome for patients with heart failure in Europe