PCSK9 levels positively associated with outcomes in patients with worsening HF

The PCSK9-LDL Receptor Axis and Outcomes in Heart Failure BIOSTAT-CHF Subanalysis

Literature - Bayes-Genis A, Núñez J, Zannad F, et al. - J Am Coll Cardiol 2017;70:2128–36


Targeting pathways activated in HF, like the RAAS and the sympathetic nervous system, has led to improvements in the management of the disease [1]. Nevertheless, morbidity and mortality rates remain high in HF, in addition to high health care costs and poor quality of life. Another pathway to target is atherosclerosis progression. Administration of statins in HF, however, has led to debatable results, and the potential of PCSK9 as a target in HF is not known [2].

In this analysis of the multicenter, prospective, observational BIOSTAT-CHF cohort [3], the value of the PCSK9-LDLR axis for predicting risk in patients with HF was evaluated. BIOSTAT-CHF included 2,516 patients with worsening signs and/or symptoms of HF (WHF) with a median follow-up of 21 months. The primary outcomes of interest were time to all-cause mortality and time to a composite of death or unscheduled hospitalization for HF.

Predictive value of the BIOSTAT-CHF risk score, PCSK9 and LDLR levels and use of statin was assessed in patients with WHF. Measures of performance were Delta C-statistics, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) (%). The BIOSTAT-CHF risk score for each endpoint was calculated as the probability of achieving an endpoint at a 2-year follow-up. The BIOSTAT-CHF risk score for mortality included age, blood urea nitrogen, NT-proBNP, serum hemoglobin, and the use of a beta-blocker. The BIOSTAT-CHF risk score for the composite endpoint included age, previous HF-related hospitalization, presence of edema, SBP, and the estimated glomerular filtration rate [4].

Main results

  • Out of 2,174 patients included in this analysis, 53.2% had history of ischemic heart disease (IHD), 88.8% had an LVEF ≤40%, 4.5% had LVEF in the mid-range and 6.7% had preserved LVEF.
  • During a median follow-up of 1.78 years (IQR: 1.29-2.25 years), 569 deaths (26.2%) were registered, and at a median follow-up of 1.53 years (IQR: 0.67-2.15 years), 896 (41.2%) composite endpoints (death or HF-related hospitalization) were noted.
  • The median (IQR) levels of PCSK9, LDLR, and NT-proBNP were 1.81 U/ml (1.45-2.18), 2.98 U/ml (2.45-3.53), and 4,148 pg/ml (2,330-8,136), respectively.
  • Multivariable analyses showed a positive linear association between soluble PCSK9 and the risk of mortality (HR: 1.24; 95%CI: 1.04-1.49, P=0.020), and a negative linear association between LDLR and mortality (HR: 0.86; 95%CI: 0.76-0.98; P=0.025).
  • Moreover, PCSK9 showed a linear and positive association with the risk of the combined endpoint (HR: 1.21; 95%CI: 1.05-1.40; P=0.011), independent of the effect of BIOSTAT-CHF risk score for the composite endpoint, LDLR, and statin treatment. LDLR did not show a significant association with the primary composite endpoint (HR: 0.92; 95% CI: 0.83-1.01, P=0.087).
  • At baseline, patients in the higher PCSK9 quartiles displayed significantly higher prevalence of IHD and higher serum creatinine.
  • The added value in performance for PCSK9 and LDLR levels, and statin treatment over the BIOSTAT risk score was confirmed for the endpoint of mortality (Delta C-statistic: 0.0120; 0.002-0.022; P=0.019; IDI: 0.3; 0.0-1.1; NRI: 6.0; 0.0-11.9), and for the composite endpoint (Delta C-statistic: 0.014; 0.006-0.022; P<0.001; IDI: 0.8; 0.2-1.8; NRI: 10.8; 2.9-15.0).
  • PCSK9 levels showed a better risk reclassification over LDLR, statin treatment, and the BIOSTAT-CHF risk score, both for the endpoint of mortality and the composite endpoint.


In the BIOSTAT-CHF cohort, risk of death or hospitalization for HF was positively associated with circulating PCSK9 and negatively associated with LDLR in patients with WHF. Circulating PCSK9 levels may contribute to risk prediction in HF patients. These data suggest that PCSK9 inhibition might lead to better outcomes in HF.

Editorial comment

In his editorial article [5], Francis emphasizes that patients in the BIOSTAT-CHF cohort had WHF, as opposed to chronic stable HF, in which the prognostic role of the PCSK9-LDLR axis is unclear. Moreover, he suggests that two important questions should be investigated:

  • whether there is a cause and effect relationship between the PCSK9-LDLR axis and long-term outcomes
  • whether PCSK9 inhibition in patients with WHF will lead to improved outcomes

The current data add to our understanding of the interaction between lipid abnormalities and WHF, which has long received little attention. Brief treatment with novel HF therapy regimes has not resulted in reductions of important endpoints in clinical trials of patients with WHF; it is interesting to study whether PCSK9 plays a role in the worsening of HF and in the context of acute, decompensated HF.

The author concludes: ‘Last, there is the issue of the cost of PCSK9 inhibitors.’ (…) ‘Current restrictions on access to expensive drugs send a strong message to physicians and patients, as well as to innovators, that the benefits must be substantial if such drugs are going to be widely used. Nevertheless, these investigators have uncovered an interesting finding that may warrant further study, particularly if it can successfully be applied in a therapeutic manner to patients with acute, worsening heart failure.’


1. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129–200.

2. Gastelurrutia P, Lupón J, de Antonio M, et al. Statins in heart failure: the paradox between large randomized clinical trials and real life. Mayo Clin Proc 2012;87:555–60.

3. Voors AA, Anker SD, Cleland JG, et al. A systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure: rationale, design, and baseline characteristics of BIOSTAT-CHF. Eur J Heart Fail 2016;18:716–26.

4. Voors AA, Ouwerkerk W, Zannad F, et al. Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure. Eur J Heart Fail 2017; 19:627–34.

5. Francis, G. S. Cholesterol and Heart Failure: Is There an Important Connection? J Am Coll Cardiol 2017;70:2137-38.

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