Advertisement

What is the role of growth-differentiation factor-15 in biomarker-based prediction of mortality in patients with atrial fibrillation?

  • Alexander P. Benz
    Correspondence
    Corresponding authors.
    Affiliations
    Population Health Research Institute, Hamilton Health Sciences and McMaster University, 20 Copeland Avenue, Hamilton, ON L8L 2 × 2, Canada

    Department of Cardiology, Cardiology I, University Medical Center Mainz, Johannes Gutenberg-University, Mainz, Germany
    Search for articles by this author
  • John W. Eikelboom
    Correspondence
    Corresponding authors.
    Affiliations
    Population Health Research Institute, Hamilton Health Sciences and McMaster University, 20 Copeland Avenue, Hamilton, ON L8L 2 × 2, Canada
    Search for articles by this author
      Physicians often use risk prediction models to help guide diagnosis and inform patient management. Notable examples include the Framingham Risk Score, used to estimate the 10-year risk of coronary disease; the INTERHEART Modifiable Risk Score, used to predict myocardial infarction; and the CHADS2 score to assess stroke risk in patients with atrial fibrillation (AF). [
      • Wilson P.W.
      • D'Agostino R.B.
      • Levy D.
      • Belanger A.M.
      • Silbershatz H.
      • Kannel W.B.
      Prediction of coronary heart disease using risk factor categories.
      ,
      • McGorrian C.
      • Yusuf S.
      • Islam S.
      • et al.
      Estimating modifiable coronary heart disease risk in multiple regions of the world: the INTERHEART Modifiable Risk Score.
      ,
      • Gage B.F.
      • Waterman A.D.
      • Shannon W.
      • Boechler M.
      • Rich M.W.
      • Radford M.J.
      Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.
      ] Scores that are solely based on clinical variables are often preferred because the information required is readily available. [
      • Lip G.Y.
      • Nieuwlaat R.
      • Pisters R.
      • Lane D.A.
      • Crijns H.J.
      Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.
      ,
      • Hindricks G.
      • Potpara T.
      • Dagres N.
      • et al.
      2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).
      ,
      • January C.T.
      • Wann L.S.
      • Calkins H.
      • et al.
      2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines and the heart rhythm society in collaboration with the society of thoracic surgeons.
      ] However, many clinical scores dichotomize or otherwise categorize predictor variables which can reduce statistical power and compromise the accuracy of risk prediction. [
      • Gage B.F.
      • Waterman A.D.
      • Shannon W.
      • Boechler M.
      • Rich M.W.
      • Radford M.J.
      Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.
      ,
      • Lip G.Y.
      • Nieuwlaat R.
      • Pisters R.
      • Lane D.A.
      • Crijns H.J.
      Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.
      ]
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to European Journal of Internal Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Wilson P.W.
        • D'Agostino R.B.
        • Levy D.
        • Belanger A.M.
        • Silbershatz H.
        • Kannel W.B.
        Prediction of coronary heart disease using risk factor categories.
        Circulation. 1998; 97: 1837-1847
        • McGorrian C.
        • Yusuf S.
        • Islam S.
        • et al.
        Estimating modifiable coronary heart disease risk in multiple regions of the world: the INTERHEART Modifiable Risk Score.
        Eur Heart J. 2011; 32: 581-589
        • Gage B.F.
        • Waterman A.D.
        • Shannon W.
        • Boechler M.
        • Rich M.W.
        • Radford M.J.
        Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.
        JAMA. 2001; 285: 2864-2870
        • Lip G.Y.
        • Nieuwlaat R.
        • Pisters R.
        • Lane D.A.
        • Crijns H.J.
        Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.
        Chest. 2010; 137: 263-272
        • Hindricks G.
        • Potpara T.
        • Dagres N.
        • et al.
        2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).
        Eur Heart J. 2021; 42: 373-498
        • January C.T.
        • Wann L.S.
        • Calkins H.
        • et al.
        2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines and the heart rhythm society in collaboration with the society of thoracic surgeons.
        Circulation. 2019; 140: e125-e151
        • Wallentin L.
        • Hijazi Z.
        • Andersson U.
        • et al.
        Growth differentiation factor 15, a marker of oxidative stress and inflammation, for risk assessment in patients with atrial fibrillation: insights from the Apixaban for reduction in stroke and other thromboembolic events in atrial fibrillation (ARISTOTLE) trial.
        Circulation. 2014; 130: 1847-1858
        • Wollert K.C.
        • Kempf T.
        • Peter T.
        • et al.
        Prognostic value of growth-differentiation factor-15 in patients with non-ST-elevation acute coronary syndrome.
        Circulation. 2007; 115: 962-971
        • Hagström E.
        • James S.K.
        • Bertilsson M.
        • et al.
        Growth differentiation factor-15 level predicts major bleeding and cardiovascular events in patients with acute coronary syndromes: results from the PLATO study.
        Eur Heart J. 2016; 37: 1325-1333
        • Hijazi Z.
        • Oldgren J.
        • Andersson U.
        • et al.
        Growth-differentiation factor 15 and risk of major bleeding in atrial fibrillation: insights from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial.
        Am Heart J. 2017; 190: 94-103
        • Hijazi Z.
        • Lindbäck J.
        • Alexander J.H.
        • et al.
        The ABC (age, biomarkers, clinical history) stroke risk score: a biomarker-based risk score for predicting stroke in atrial fibrillation.
        Eur Heart J. 2016; 37: 1582-1590
        • Oldgren J.
        • Hijazi Z.
        • Lindbäck J.
        • et al.
        Performance and validation of a novel biomarker-based stroke risk score for atrial fibrillation.
        Circulation. 2016; 134: 1697-1707
        • Hijazi Z.
        • Oldgren J.
        • Lindbäck J.
        • et al.
        The novel biomarker-based ABC (age, biomarkers, clinical history)-bleeding risk score for patients with atrial fibrillation: a derivation and validation study.
        Lancet. 2016; 387: 2302-2311
        • Hijazi Z.
        • Oldgren J.
        • Lindbäck J.
        • et al.
        A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score.
        Eur Heart J. 2018; 39: 477-485
        • Berg D.D.
        • Ruff C.T.
        • Jarolim P.
        • et al.
        Performance of the ABC scores for assessing the risk of stroke or systemic embolism and bleeding in patients with atrial fibrillation in ENGAGE AF-TIMI 48.
        Circulation. 2019; 139: 760-771
        • Benz A.P.
        • Hijazi Z.
        • Lindbäck J.
        • et al.
        Biomarker-based risk prediction with the ABC-AF scores in patients with atrial fibrillation not receiving oral anticoagulation.
        Circulation. 2021; (In press)https://doi.org/10.1161/CIRCULATIONAHA.120.053100
        • Nopp S.
        • Königsbrügge O.
        • Kraemmer D.
        • Pabinger I.
        • Ay C.
        Growth differentiation factor-15 predicts major adverse cardiac events and all-cause mortality in patients with atrial fibrillation.
        Eur J Intern Med. 2021; https://doi.org/10.1016/j.ejim.2021.02.011
        • Peduzzi P.
        • Concato J.
        • Kemper E.
        • Holford T.R.
        • Feinstein A.R.
        A simulation study of the number of events per variable in logistic regression analysis.
        J Clin Epidemiol. 1996; 49: 1373-1379
        • Steyerberg E.W.
        • Vergouwe Y.
        Towards better clinical prediction models: seven steps for development and an ABCD for validation.
        Eur Heart J. 2014; 35: 1925-1931