NCT07470554

BIOmarker Based Diagnostic TOOLkit to Personalize Pharmacological Approaches in Congestive Heart Failure

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 4,254 (actual)
• Sponsor: IRCCS Azienda Ospedaliero-Universitaria di Bologna · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This retrospective study will take advantage of an existing EU-funded dataset, the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF), which was designed to identify biomarkers related to the response to guideline directed medical therapy, and coordinated by UMCG. The availability of this comprehensive dataset of patients with severe HFrEF, prospectively and consistently collected, with the possibility to access a biobank to re-assay samples with novel biomarkers, provides a unique opportunity to derive preliminary data about the interaction between biomarkers of congestion and diuretic doses, that were prescribed based on clinical judgement, and therefore derive a machine learning-based algorithm than could be tested to guide the management of diuretic therapy

Detailed description

This is a retrospective study based on the index and the validation cohorts of the BIOSTAT-CHF project. The index cohort consists of a prospectively enrolled series of 2516 patients from 69 centres in 11 European countries recruited between December 2010 and December 2012 and with a median follow-up of 21 months \[interquartile range (IQR) 15 - 27 months\]. Validation cohort was designed as well as a multicentre, prospective, observational study, which included 1738 patients from six centres in Scotland, United Kingdom. BIOSTAT-CHF data will be re-analysed to include additional congestion biomarkers and derive a predictive model for congestion-related adverse events at 9 months after study entry, priming the design of a prospective randomized study. Predictive models based on the analysis of the BIOSTAT-CHF cohort had already been reported. When considering only standard clinical and biological predictive variables, the full prediction models for mortality, hospitalisation owing to HF, and the combined outcome, yielded c-statistic values of 0.73, 0.69, and 0.71, respectively. The five strongest predictors of mortality were more advanced age, higher blood urea nitrogen and N-terminal pro-B-type natriuretic peptide (NT-proBNP), lower haemoglobin, and failure to prescribe a beta-blocker. The five strongest predictors of hospitalisation due to decompensated HF were more advanced age, previous hospitalisation owing to HF, presence of oedema, lower systolic blood pressure and lower estimated glomerular filtration rate. We hypothesize that by including a more granular biomarkers analysis and different statistical models, the BIOSTAT-DISCO may provide a multi-parametric score that can be tested to guide therapy management.

Conditions

• Heart Failure With Reduced Ejection Fraction (HFrEF)
• Congestive Heart Failure(CHF)

Timeline

• Start date: 2010-12-01
• Primary completion: 2012-12-01
• Completion: 2012-12-01
• First posted: 2026-03-13
• Last updated: 2026-03-13