Observational studyScientific reports2022
Dynamic personalized risk prediction in chronic heart failure patients: a longitudinal, clinical investigation of 92 biomarkers (Bio-SHiFT study).
Observational study in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01851538 (Serial Biomarker Measurements and New Echocardiographic Techniques in Chronic Heart Failure Patients Result in Tailored Prediction of Prognosis), which is not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Serial Biomarker Measurements and New Echocardiographic Techniques in Chronic Heart Failure Patients Result in Tailored Prediction of Prognosis
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Proteomics for heart failure risk stratification: a systematic review.BMC medicine · 2024Pooled it
- Risk Prediction Models for Cardiotoxicity of Chemotherapy Among Patients With Breast Cancer: A Systematic Review.JAMA network open · 2023Pooled it
- Pathophysiological analysis of serially measured plasma biomarkers, remote monitoring and clinical events, in symptomatic patients with moderate to severe chronic heart failure.International journal of cardiology. Heart & vasculature · 2026Article
- PIFA-N Multifactor Model to Predict Adverse Outcomes for Chronic Heart Failure Patients.Journal of clinical medicine research · 2026Article
- Advancing precision triage in strangulated small bowel obstruction: from static scores to dynamic multiparametric models.Frontiers in surgery · 2026Review
- Toward an integrated risk paradigm: personalizing antithrombotic therapy for coronary heart disease with gastrointestinal bleeding.Frontiers in cardiovascular medicine · 2026Article
- Pathologic Signaling and Disease Implications of Insulin-like Growth Factor Binding Proteins in Cancer, Cardiovascular Disease, and Fibrosis.International journal of molecular sciences · 2025Review
- Article
- Clinical Insights from Proteomics in Heart Failure.Current heart failure reports · 2025Review
- Machine Learning-Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study.JMIR medical informatics · 2025Article
- Insulin-like Growth Factor-Binding Protein-1 (IGFBP-1) as a Biomarker of Cardiovascular Disease.Biomolecules · 2024Review
- Article
- Identifying plasma proteomic signatures from health to heart failure, across the ejection fraction spectrum.Scientific reports · 2024Article
- The Association Between Oxidative Stress and the Progression of Heart Failure: A Systematic Review.Cureus · 2024Review
- Sex-specific cardiovascular protein levels and their link with clinical outcome in heart failure.ESC heart failure · 2024Article
- How to Select Patients for Left Ventricular Assist Devices? A Guide for Clinical Practice.Journal of clinical medicine · 2023Review
- Advanced Proteomics and Cluster Analysis for Identifying Novel Obstructive Sleep Apnea Subtypes before and after Continuous Positive Airway Pressure Therapy.Annals of the American Thoracic Society · 2023Article
- Inflammageing and Cardiovascular System: Focus on Cardiokines and Cardiac-Specific Biomarkers.International journal of molecular sciences · 2023Review
- Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight-loss intervention: A pilot study.Obesity (Silver Spring, Md.) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of our observational study was to derive a small set out of 92 repeatedly measured biomarkers with optimal predictive capacity for adverse clinical events in heart failure, which could be used for dynamic, individual risk assessment in clinical practice. In 250 chronic HFrEF (CHF) patients, we collected trimonthly blood samples during a median of 2.2 years. We selected 537 samples for repeated measurement of 92 biomarkers with the Cardiovascular Panel III (Olink Proteomics AB). We applied Least Absolute Shrinkage and Selection Operator (LASSO) penalization to select the optimal set of predictors of the primary endpoint (PE). The association between repeatedly measured levels of selected biomarkers and the PE was evaluated by multivariable joint models (mvJM) with stratified fivefold cross validation of the area under the curve (cvAUC). The PE occurred in 66(27%) patients. The optimal set of biomarkers selected by LASSO included 9 proteins: NT-proBNP, ST2, vWF, FABP4, IGFBP-1, PAI-1, PON-3, transferrin receptor protein-1, and chitotriosidase-1, that yielded a cvAUC of 0.88, outperforming the discriminative ability of models consisting of standard biomarkers (NT-proBNP, hs-TnT, eGFR clinically adjusted) - 0.82 and performing equally well as an extended literature-based set of acknowledged biomarkers (NT-proBNP, hs-TnT, hs-CRP, GDF-15, ST2, PAI-1, Galectin 3) - 0.88. Nine out of 92 serially measured circulating proteins provided a multivariable model for adverse clinical events in CHF patients with high discriminative ability. These proteins reflect wall stress, remodelling, endothelial dysfunction, iron deficiency, haemostasis/fibrinolysis and innate immunity activation. A panel containing these proteins could contribute to dynamic, personalized risk assessment.Clinical Trial Registration: 10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 .
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