Estimating the Lifetime Benefits of Treatments for Heart Failure

João Pedro Ferreira, MD, PHD; Kieran F. Docherty, MBCHB; Susan Stienen, MD, PHD; Pardeep S. Jhund, MBBCH, PHD; Brian L. Claggett, PHD; Scott D. Solomon, MD; Mark C. Petrie, MBCHB; John Gregson, PHD; Stuart J. Pocock, PHD; Faiez Zannad, MD, PHD; John J.V. McMurray, MD

Disclosures

JACC Heart Fail. 2020;8(12):984-995. 

In This Article

Abstract and Introduction

Abstract

Objectives: This study compared ways of describing treatment effects. The objective was to better explain to clinicians and patients what they might expect from a given treatment, not only in terms of relative and absolute risk reduction, but also in projections of long-term survival.

Background: The restricted mean survival time (RMST) can be used to estimate of long-term survival, providing a complementary approach to more conventional metrics (e.g., absolute and relative risk), which may suggest greater benefits of therapy in high-risk patients compared with low-risk patients.

Methods: Relative and absolute risk, as well as the RMST, were calculated in heart failure with reduced ejection fraction (HFrEF) trials.

Results: As examples, in the RALES trial (more severe HFrEF), the treatment effect metrics for spironolactone versus placebo on heart failure hospitalization and/or cardiovascular death were a hazard ratio (HR) of 0.67 (95% confidence interval [CI]: 0.5 to 0.77), number needed to treat = 9 (7 to 14), and age extension of event-free survival +1.1 years (−0.1 to + 2.3 years). The corresponding metrics for EMPHASIS-HF (eplerenone vs. placebo in less severe HFrEF) were 0.64 (0.54 to 0.75), 14 (1 to 22), and +2.9 (1.2 to 4.5). In patients in PARADIGM-HF aged younger than 65 years, the metrics for sacubitril/valsartan versus enalapril were 0.77 (95% CI: 0.68 to 0.88), 23 (15 to 44), and +1.7 (0.6 to 2.8) years; for those aged 65 years or older, the metrics were 0.83 (95% CI: 0.73 to 0.94), 29 (17 to 83), and +0.9 (0.2 to 1.6) years, which provided evidence of a greater potential life extension in younger patients. Similar observations were found for lower risk patients.

Conclusions: RMST event-free (and overall) survival estimates provided a complementary means of evaluating the effect of therapy in relation to age and risk. They also provided a clinically useful metric that should be routinely reported and used to explain the potential long-term benefits of a given treatment, especially to younger and less symptomatic patients.

Introduction

In randomized controlled trials, the effect of treatment is usually estimated using a time-to-first-event survival model that compares the hazard rate of the experimental treatment group (or groups) and the control group, which produces a hazard ratio (HR) and corresponding 95% confidence interval (CI).[1] By convention, if the upper 95% CI does not cross unity, the effect of treatment is considered statistically significant. Although this is the standard way of reporting the effect of treatment at medical presentations and in publications, it may exaggerate the effect of therapy (e.g., if the absolute risk reduction is small) and may not be readily interpretable by patients in terms of understanding their survival free of adverse clinical events, including death.[2] Reporting the absolute treatment effect, as a percent reduction, reduction in event rate, or number needed to treat (NNT), overcomes the first of these criticisms (although NNT should be standardized for duration of follow-up). However, metrics of absolute benefit will generally look better in a high-risk than in a low-risk population, assuming the proportional risk reduction with the treatment is similar, at least in the relatively short follow-up that typifies most trials. Conversely, treatments started earlier in the course of a disease when patients are at lower risk (or even in younger patients) may have the potential to lead to greater prolongation of life. Another assessment of treatment effect that complements HR and absolute risk reduction or NNT, is the restricted mean survival time (RMST).[3,4] The RMST can be interpreted as the mean event-free survival time up to a pre-specified time point and is equivalent to the area under the Kaplan-Meier curve from the start of the study up to that point. Using age at randomization instead of time, the RMST approach allows for estimation of long-term, event-free survival that can be obtained with a specific intervention compared with a control group, across different age groups.[5] The RMST provides an estimate of the effect of treatment in terms of time "free of an event," years of life gained, or both. Such measures may be more readily interpretable and quantifiable for patients and clinicians. To better understand the use of RMST and how it compares with other conventional measures of treatment effect, we analyzed HR, NNT, and RMST in several large cardiovascular outcome trials. We also analyzed these metrics in low-risk versus high-risk subgroups to illustrate how the RMST could provide relevant information that is less dependent on the risk of patients, providing a clinically relevant long-term outlook.

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