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Introduction
Heart failure (HF) is an increasing health problem worldwide [1-3]. Despite recent progress in pharmacologic and implantable cardiac device treatment, the mortality of patients with HF remains substantially high [2-6]. There is increasing interest in the use of many biological markers, including natriuretic peptides, to more accurately determine patient prognosis, such as mortality and HF hospitalization.
Neurohormonal deterioration plays a key role in the development of HF. Numerous biomarkers and therapeutic approaches have been established to elucidate this pathophysiological mechanism. Natriuretic peptide has become a reliable biomarker for the diagnosis and estimation of prognosis in patients with HF. Additionally, the use of novel biomarkers may guarantee a more accurate estimation of the prognosis of HF and can be valuable for understanding the pathophysiology of HF. Chromogranin A (CgA) is a prohormone produced in many tissues, including neuroendocrine and myocardial tissues. The level of CgA is closely correlated with sympathetic activity in the adrenal gland and peripheral nervous system, suggesting that it might be a marker of sympathetic activity in humans [7]. In addition, it has been known as a biomarker for neuroendocrine tumors [8] and has recently been found to be associated with prognosis in patients with cardiovascular disease [9-12]. Recent studies have shown that CgA is an independent predictor of long-term mortality and HF hospitalization in patients with acute coronary syndromes [9]. In patients with HF, circulating CgA levels are associated with functional status, HF hospitalization, and mortality [10].
The present study aimed to investigate (1) the prognostic value of CgA in patients with acute HF and (2) the additive prognostic impact of CgA when measured together with N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients with acute HF.
Materials and methods
1. Study population
We retrospectively evaluated patients who underwent CgA testing during the acute stage of HF hospitalization between June 2017 and June 2018. A total of 272 patients were enrolled, and the median follow-up duration was 348 days.
The diagnosis of HF was established based on current guidelines, taking into account symptoms, laboratory findings, and radiographic and echocardiographic findings.
Data on demographic characteristics, medications, laboratory tests, and prognosis were collected from the patients’ medical charts. Initial transthoracic echocardiographic findings were collected from the images and reports from the database. NT-proBNP (The Dimension Vista PBNP Flex reagent cartridge; Erlangen, Germany) and CgA (Cisbio CgA ELISA kit; Codolet, France) were tested in venous blood and within 24 hours of hospital admission. Patients were followed up for 12 months after the index hospitalization. The primary endpoint was a composite event of 1-year death and hospitalization for HF. The death certificates and National Health Insurance data were reviewed to determine survival or death.
2. Statistics
Data are presented as percentages for baseline characteristics and categorical variables, and comparisons between them were assessed using the chi-square test. The distribution of continuous variables is expressed as the mean±standard deviation or median (interquartile range), and the differences were compared using the independent t-test.
A receiver-operating characteristic (ROC) curve was used to identify the optimal cutoff points for the CgA and NT-proBNP levels to determine the potential relationship between CgA and prognosis. Delong’s method was used to compare the area under the curves (AUCs) between CgA and NT-proBNP. All patients were classified into four groups according to the cutoff levels for NT-proBNP and CgA obtained from the ROC curve analysis. Kaplan-Meier survival analysis was performed based on these four groups. Bonferroni correction was used in the subgroup analysis that tested the prognostic value of CgA in patients with high and low NT-proBNP levels. All analyses were two-tailed, and p-values of <0.05 were considered statistically significant.
The relationship between the two biomarkers and prognosis (composite outcome of 1-year death and hospitalization for HF) of the patients were investigated.
Results
1. Baseline characteristics
Patients who underwent CgA and NT-proBNP testing between June 2017 and June 2018 in the acute stage of HF hospitalization were enrolled retrospectively. A total of 272 patients (mean age, 68.5±15.6 years; 62.9% male) were enrolled, and the median follow-up duration was 348 days. Nearly half of the patients had New York Heart Association (NYHA) class III–IV symptoms (45.2%). Of the total patients, 133 (48.9%) had hypertension, 86 (31.6%) had diabetes mellitus, 54 (19.9%) had atrial fibrillation, and 108 (39.7%) had ischemic heart disease. The mean left ventricular ejection fraction (LVEF) was 42.6%±16.1%, the mean NT-proBNP level was 10,650.1±26,302.4 pg/mL, and the mean CgA level was 279.8±392.6 pmol/L (Table 1). The CgA level increased with a decrease in LVEF and an increase in NYHA class (Supplementary Figs. 1, 2).
Patients in both the high NT-proBNP and high CgA groups were more likely to be older and to be prescribed a loop diuretic in their discharge medications than those in the low NT-proBNP and low CgA groups. The high CgA group had higher NT-proBNP levels than the low CgA group. In addition, higher CgA levels were observed in the high NT-proBNP group than in the low NT-proBNP group. In the high CgA group, de novo HF was observed less frequently than in the low CgA group. Atrial fibrillation, ischemic heart disease, medication before admission, and estimated glomerular filtration rate were not different between the two groups regardless of NT-proBNP and CgA levels (Table 1, Supplementary Table 1).
2. Prognostic value of serum CgA and NT-proBNP
In-hospital mortality rate of the study population was 7.0% (n=19). During the follow-up period, the composite event of 1-year death and hospitalization for HF was observed in 12.1% of patients (n=33). In the ROC analysis to predict the composite event of 1-year death and hospitalization, the AUCs were 0.737 and 0.697 for NT-proBNP and CgA, respectively. The cutoff values for predicting the prognosis for CgA and NT-proBNP were 158 pmol/L and 3,429 pg/mL, respectively (Fig. 1). During the follow-up, patients with high CgA (>158 pmol/L) were more likely to have worse outcomes (85.2% vs. 58.6%, p<0.001) in the Kaplan-Meier analysis. Age, NYHA class, atrial fibrillation, de novo HF, NT-proBNP level, and CgA level were significantly associated with prognosis in the univariate analysis. In the multivariable analysis model, CgA was an independent factor associated with 1-year death and hospitalization for HF (hazard ratio [HR], 1.059/100 pmol/L; 95% confidence interval [CI], 1.007–1.115, p=0.027), as was age, NYHA class, and de novo HF (Table 2).
Based on the cutoff values for CgA (158 pmol/L) and NT-proBNP (3,429 pg/mL), the study cohort was divided into four groups: low NT-proBNP and low CgA (n=106), low NT-proBNP and high CgA (n=40), high NT-proBNP and low CgA (n=60), and high NT-proBNP and high CgA (n=66). The Kaplan-Meier survival analysis showed that the group with low levels of both NT-proBNP and CgA had the best 1-year survival rate (88.9%), followed by the group with low NT-proBNP and high CgA levels (86.6%), the group with high NT-proBNP and low CgA levels (78.6%), and the group with both high NT-proBNP and CgA levels (40.2%, p<0.001) (Fig. 2). In the subgroup of patients with high NT-proBNP levels, low CgA levels were associated with patient prognosis (40.2% vs. 78.6%, p<0.001), whereas there was no significant prognostic value in the subgroup of patients with low NT-proBNP levels (86.6% vs. 88.9%, p>0.999).
To investigate the predictive value of CgA, we created three models: (1) the baseline model including the risk factors of age, sex, NYHA class, atrial fibrillation, and de novo HF; (2) baseline model+NT-proBNP; and (3) baseline model+NT-proBNP+CgA. The addition of serum NT-proBNP and CgA to the established risk factors increased the provided incremental information for predicting the prognosis (global chi-square 42.4 to 47.2, p=0.030). Adding CgA to the second model, which comprised both the established risk factors and NT-proBNP, resulted in additional improvement of the prognostic power for 1-year adverse events (global chi-square from 47.2 to 51.4, p=0.039) (Fig. 3).
Discussion
In the present study, blood CgA levels in patients with acute HF were found to be an independent factor associated with 1-year death and hospitalization for HF. We divided the study cohort into four groups based on NT-proBNP and CgA blood concentrations. Those with low NT-proBNP and low CgA levels showed the lowest rates of 1-year death and hospitalization for HF. High NT-proBNP and high CgA levels were associated with the worst outcomes. Our findings demonstrate the advantage of adding CgA levels to a well-established biomarker, NT-proBNP, for better risk stratification. Simultaneous measurement of NT-proBNP and CgA can help predict death in patients with acute HF more accurately than the estimation of NT-proBNP alone. In particular, CgA has a low significance as a prognostic predictor of 1-year death and HF hospitalization in patients with low NT-proBNP levels and may be more helpful as a prognostic predictor in patients with high NT-proBNP levels. In our study, the high NT-proBNP group was older and consisted of a greater proportion of individuals with NYHA class III–IV, suggesting that CgA may be more helpful in predicting the prognosis of high-risk groups of patients with acute HF.
Ceconi et al. [10] suggested that CgA levels were increased in patients with chronic HF and were a predictor of mortality. Røsjø et al. [13] investigated the prognostic value of CgA in patients with stabilized HF from the GISSI-Heart Failure trial. In the univariable analysis, increased CgA plasma concentrations were associated with all-cause mortality, with hazard ratios between 1.58 (95% CI, 1.17–2.11) and 2.35 (95% CI, 1.78–3.10). However, after adjustment for clinically relevant risk factors, the association was not significant.
A recent study investigated the underlying mechanism of CgA increase in patients with acute HF, suggesting a role for CgA in patients with acute HF [11]. CgA is a member of the granin protein family, which plays a role in the endocrine and paracrine system and seems to play a role in cardiovascular disease. One of the mechanisms of increased CgA in patients with HF is thought to be the impaired processing of CgA to CgA fragment catestatin [11]. Ottesen et al. [11] revealed that the fragment catestatin may directly dysregulate cardiomyocyte Ca2+ handling, indicating that elevated CgA can be related to patient prognosis in the acute stage of HF.
NT-proBNP is a well-established biomarker in a variety of heart diseases, including HF, because of its correlation with clinical status, echocardiographic parameters, laboratory findings, and short-term and long-term prognosis [14-16]. NT-proBNP is a neurohormone released by the ventricles of the heart as a result of volume or pressure overload and has a different mechanism than CgA secretion. Our study indicates that when biomarkers from two different mechanisms are combined, they are synergistic in predicting the long-term prognosis of patients with acute HF. The simultaneous application of CgA and NT-proBNP allows a more accurate estimate of the prognosis of patients with acute HF in clinical practice.
Our study had some limitations to consider. First, this was a relatively small retrospective study conducted in a single center. Thus, the results of the present study need to be validated in larger trials. Second, although we included all patients available during the index period, there may have been some selection bias in [2,17] the study population.
CgA presented prognostic power comparable to that of the proven biomarker NT-proBNP in patients with acute HF. CgA combined with NT-proBNP levels demonstrated an additive prognostic value in these patients.
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