Advertisement

Digoxin Benefit Varies by Risk of Heart Failure Hospitalization: Applying the Tufts MC HF Risk Model

Published:December 25, 2017DOI:https://doi.org/10.1016/j.amjmed.2017.12.010

      Abstract

      Background

      Digoxin has been shown to reduce heart failure hospitalizations with a neutral effect on mortality. It is unknown whether there is heterogeneity of treatment effect for digitalis therapy according to predicted risk of heart failure hospitalization.

      Methods and Results

      We conducted a post hoc analysis of the Digitalis Investigator Group (DIG) studies, randomized controlled trials of digoxin vs placebo in participants with heart failure and left ventricular ejection fraction ≤45% (main DIG study, n = 6800) or >45% (ancillary DIG study, n = 988). Using a previously derived multistate model to risk-stratify DIG study participants, we determined the differential treatment effect on hospitalization and mortality outcomes. There was a 13% absolute reduction in the risk of any heart failure hospitalizations (39% vs 52%; odds ratio 0.58; 95% confidence interval 0.47-0.71) in the digoxin vs placebo arms in the highest-risk quartile, compared with a 3% absolute risk reduction for any heart failure hospitalization (17% vs 20%; odds ratio 0.84; 95% confidence interval, 0.66-1.08) in the lowest-risk quartile. There were 12 fewer total all-cause hospitalizations per 100 person-years in the highest-risk quartile compared with an increase of 8 hospitalizations per 100 person-years in the lowest-risk quartile. There was neutral effect of digoxin on mortality in all risk quartiles and no interaction between baseline risk and the effect of digoxin on mortality (P = .94).

      Conclusions

      Participants in the DIG study at higher risk of hospitalization as identified by a multistate model were considerably more likely to benefit from digoxin therapy to reduce heart failure hospitalization.

      Keywords

      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 The American Journal of Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Heidenreich P.A.
        • Albert N.M.
        • Allen L.A.
        • et al.
        Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association.
        Circ Heart Fail. 2013; 6: 606-619
        • Jencks S.F.
        • Williams M.V.
        • Coleman E.A.
        Rehospitalizations among patients in the Medicare fee-for-service program.
        N Engl J Med. 2009; 360: 1418-1428
        • Digitalis Investigation Group
        The effect of digoxin on mortality and morbidity in patients with heart failure.
        N Engl J Med. 1997; 336: 525-533
        • Ziff O.J.
        • Lane D.A.
        • Samra M.
        • et al.
        Safety and efficacy of digoxin: systematic review and meta-analysis of observational and controlled trial data.
        BMJ. 2015; 351: h4451
        • Packer M.
        • Gheorghiade M.
        • Young J.B.
        • et al.
        Withdrawal of digoxin from patients with chronic heart failure treated with angiotensin-converting-enzyme inhibitors. RADIANCE Study.
        N Engl J Med. 1993; 329: 1-7
        • Lee D.C.
        • Johnson R.A.
        • Bingham J.B.
        • et al.
        Heart failure in outpatients: a randomized trial of digoxin versus placebo.
        N Engl J Med. 1982; 306: 699-705
        • Hood Jr, W.B.
        • Dans A.L.
        • Guyatt G.H.
        • Jaeschke R.
        • McMurray J.J.
        Digitalis for treatment of congestive heart failure in patients in sinus rhythm: a systematic review and meta-analysis.
        J Card Fail. 2004; 10: 155-164
        • Rathore S.S.
        • Curtis J.P.
        • Wang Y.
        • Bristow M.R.
        • Krumholz H.M.
        Association of serum digoxin concentration and outcomes in patients with heart failure.
        JAMA. 2003; 289: 871-878
        • Adams Jr, K.F.
        • Gheorghiade M.
        • Uretsky B.F.
        • Patterson J.H.
        • Schwartz T.A.
        • Young J.B.
        Clinical benefits of low serum digoxin concentrations in heart failure.
        J Am Coll Cardiol. 2002; 39: 946-953
        • Upshaw J.N.
        • Konstam M.A.
        • Klaveren D.
        • Noubary F.
        • Huggins G.S.
        • Kent D.M.
        Multistate model to predict heart failure hospitalizations and all-cause mortality in outpatients with heart failure with reduced ejection fraction: model derivation and external validation.
        Circ Heart Fail. 2016; 9https://doi.org/10.1161/CIRCHEARTFAILURE.116.003146
        • Ahmed A.
        • Rich M.W.
        • Fleg J.L.
        • et al.
        Effects of digoxin on morbidity and mortality in diastolic heart failure: the ancillary digitalis investigation group trial.
        Circulation. 2006; 114: 397-403
      1. Rationale, design, implementation, and baseline characteristics of patients in the DIG trial: a large, simple, long-term trial to evaluate the effect of digitalis on mortality in heart failure.
        Control Clin Trials. 1996; 17: 77-97
        • Konstam M.A.
        • Neaton J.D.
        • Dickstein K.
        • et al.
        Effects of high-dose versus low-dose losartan on clinical outcomes in patients with heart failure (HEAAL study): a randomised, double-blind trial.
        Lancet. 2009; 374: 1840-1848
        • de Wreede L.C.
        • Fiocco M.
        • Putter H.
        The mstate package for estimation and prediction in non- and semi-parametric multi-state and competing risks models.
        Comput Methods Programs Biomed. 2010; 99: 261-274
        • Harrell Jr, F.E.
        • Califf R.M.
        • Pryor D.B.
        • Lee K.L.
        • Rosati R.A.
        Evaluating the yield of medical tests.
        JAMA. 1982; 247: 2543-2546
        • Ioannidis J.P.
        • Lau J.
        Heterogeneity of the baseline risk within patient populations of clinical trials: a proposed evaluation algorithm.
        Am J Epidemiol. 1998; 148: 1117-1126
        • Kent D.M.
        • Nelson J.
        • Dahabreh I.J.
        • Rothwell P.M.
        • Altman D.G.
        • Hayward R.A.
        Risk and treatment effect heterogeneity: re-analysis of individual participant data from 32 large clinical trials.
        Int J Epidemiol. 2016; 45: 2078-2088
        • Mozaffarian D.
        • Benjamin E.J.
        • Go A.S.
        • et al.
        Heart disease and stroke statistics–2015 update: a report from the American Heart Association.
        Circulation. 2015; 131: e29-e322
        • Gheorghiade M.
        • Patel K.
        • Filippatos G.
        • et al.
        Effect of oral digoxin in high-risk heart failure patients: a pre-specified subgroup analysis of the DIG trial.
        Eur J Heart Fail. 2013; 15: 551-559
        • Kent D.M.
        • Lindenauer P.K.
        Aggregating and disaggregating patients in clinical trials and their subgroup analyses.
        Ann Intern Med. 2010; 153: 51-52
        • Kent D.M.
        • Rothwell P.M.
        • Ioannidis J.P.
        • Altman D.G.
        • Hayward R.A.
        Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal.
        Trials. 2010; 11: 85
        • Dorresteijn J.A.
        • Visseren F.L.
        • Ridker P.M.
        • et al.
        Estimating treatment effects for individual patients based on the results of randomised clinical trials.
        BMJ. 2011; 343: d5888
        • Sussman J.B.
        • Kent D.M.
        • Nelson J.P.
        • Hayward R.A.
        Improving diabetes prevention with benefit based tailored treatment: risk based reanalysis of Diabetes Prevention Program.
        BMJ. 2015; 350: h454
        • Kent D.M.
        • Hayward R.A.
        • Griffith J.L.
        • et al.
        An independently derived and validated predictive model for selecting patients with myocardial infarction who are likely to benefit from tissue plasminogen activator compared with streptokinase.
        Am J Med. 2002; 113: 104-111