The BIOSTAT-CHF study successfully recruited 4,254 patients with worsening heart failure to develop a systems biology model predicting individualized response to guideline-recommended therapies.
Observational (n=4,254)
Yes
Can a systems biology approach predict response to therapy in patients with worsening heart failure on suboptimal medical treatment?
The BIOSTAT-CHF study aims to use a systems biology approach to develop a model predicting response to heart failure therapy in patients with worsening symptoms on suboptimal treatment.
AIMS: Despite major improvements in pharmacological and device treatments, heart failure remains a syndrome with high morbidity and mortality, poor quality of life, and high health-care costs. Given the extensive heterogeneity among patients with heart failure, substantial differences in the response to therapy can be expected. We hypothesize that individualized therapy is an essential next step to improve outcomes in patients with heart failure. METHODS: The BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) included 2516 patients with worsening signs and/or symptoms of heart failure from 11 European countries, who were considered to be on suboptimal medical treatment. Another 1738 patients from Scotland were included in a validation cohort. Overall, both patient cohorts were well matched. The majority of patients were hospitalized for acute heart failure, and the remainder presented with worsening signs and/or symptoms of heart failure at outpatient clinics. Approximately half of the patients were in New York Heart Association class III, and 7% vs 34% of patients of the index vs validation cohort had heart failure with preserved ejection fraction. According to study design, all patients used diuretics, but owing to the inclusion criteria of both cohorts, patients were not on optimal, evidence-based medical therapy. In the follow-up phase, uptitration to guideline-recommended doses was encouraged. CONCLUSION: By using a novel systems biology approach, incorporating demographics, biomarkers, genome-wide analysis, and proteomics, a model that predicts response to therapy will be developed, which should be instrumental in developing alternative therapies for patients with suboptimal response to currently recommended therapies and thus further improve care for patients with heart failure.
Voors et al. (2016) conducted an observational in Chronic Heart Failure (n=4,254). Guideline-recommended pharmacological therapy (ACE inhibitors/ARBs and beta-blockers) was evaluated on Time to a composite of death or unscheduled hospitalizations for heart failure. The BIOSTAT-CHF study successfully recruited 4,254 patients with worsening heart failure to develop a systems biology model predicting individualized response to guideline-recommended therapies.