Etelcalcetide Inhibits the Progression of Left Atrial Volume Index Compared to Alfacalcidol in Hemodialysis Patients

The enlargement of the left atrium (LA) is an important potential indicator of cardiovascular (CV) complications because it performs three crucial physiological functions that impact the filling and performance of the left ventricle (LV) [1‒4]. These functions include acting as a contractile chamber, collecting pulmonary venous return during LV systole, and as a conduit for the passage of blood from the LA to the LV during early diastole [5, 6]. LA dilation occurs as a result of increased pressure and volume overload and can happen in the setting of both systolic and diastolic dysfunction [7‒9].

Fluid overload and changes in left ventricular mass (LVM) are frequent observed in the dialysis population. These factors significantly contribute to the enlargement of left atrial volume (LAV) [10]. A study conducted by Tripepi et al. [1] revealed that a progressive increase in LAV predicts CV events in dialysis patients, independent of the baseline measurement of LAV and LVM. Similarly, Patel et al. [11, 12] conducted a cardiac magnetic resonance (CMR) imaging study, which demonstrated a link between pretransplant LAV and mortality after transplantation. Furthermore, Kainz et al. [13] showed that LAV independently contributes to the risk of CV death in patients with end-stage kidney disease (ESKD) who undergo kidney transplantation. Moreover, a decrease in LAV following transplantation was associated with a reduced risk of both CV-related mortality and overall mortality [14]. Studies have indicated that the relationship between CV diseases and LA size is more robust when considering LA volume rather than the LA linear dimension [15]. The American Society of Echocardiography recommends utilizing LAV indexed by body surface area (LAVI) to assess the LA size [10, 16].

In our randomized-controlled clinical trial, named “Effect of etelcalcetide on cardiac hypertrophy in hemodialysis patients” (EtECAR-HD), we successfully demonstrated that the calcimimetic etelcalcetide (ETL) has the ability to impede the progression of LVM index (LVMI) when compared to treatment with active vitamin D using alfacalcidol (ALFA) in hemodialysis patients [17, 18]. Although there was a positive correlation observed between LAVI and LVMI, it was found that LAVI exhibited a stronger predictive value for both all-cause and CV mortality in patients undergoing peritoneal dialysis [19]. The objective of this trial was to investigate whether the use of ETL compared to ALFA in patients on maintenance hemodialysis has an effect on LAVI progression within 1 year of treatment.

In this post hoc analysis, we examined data from the ETECAR-HD trial, which was a prospective, randomized, controlled, single-blinded trial. It included 62 subjects diagnosed with secondary hyperparathyroidism (sHPT) who were randomly assigned to receive either intravenous ETL or ALFA treatment for a duration of 1 year. The study design specific have been previously published [17, 18]. All participants provided written informed consent, and the trial received approval from the Ethics Committee of the Medical University of Vienna (MUV; EK # 1127/2017) as well as the national regulatory authorities (AGES # 10087746). The study was conducted in accordance with the principles outlined in the Declaration of Helsinki.

The primary aim of the study was to evaluate whether ETL medication prevented the progression of LAVI when compared with ALFA in addition to its previously reported inhibitory effect on LVMI in hemodialysis patients [17]. Additionally, as the circulatory overload has a direct association with LAV, a secondary analysis was performed to examine whether different methods of assessing the volume status of hemodialysis patients, such as body composition monitoring (BCM), lung comet tail score (LCTS) through lung ultrasound, and NT-pro-brain-natriuretic peptide (NT-proBNP) measurements, were linked to the progression of LAVI.

CMR was conducted at the initiation of the study and after 1 year of treatment, specifically on a nondialysis day during the middle of the week. The calculation of body surface area, which was utilized for determining LAVI, involved using the patients’ body weight on the day the imaging took place.

Bioimpedance spectroscopy-based BCM was carried out during the screening phase, and subsequent measurements were taken at 2-month intervals throughout the study prior to the initiation of hemodialysis treatment [20]. Patients who were unable to achieve their target dry weight were excluded from participating in the trial [21].

During the screening and end phase of the study, lung ultrasound was employed to visualize lung edema. This ultrasonographic visualization, known as the LCTS, is a straightforward and noninvasive method for measuring extravascular lung water. The examination can be conveniently conducted at the patient’s bedside and provides a semiquantitative assessment of lung edema [22‒24]. The LCTS is derived by summing the comet tails observed in four lung segments (mid-clavicular and mid-axillary regions of the left and right hemithorax).

The serum level of NT-proBNP serves as an indicator of myocardial cell distension in response to circulating volume overload [25]. It is primarily stimulated by the stretch of the LA and pressure overload in the LV, leading to the secretion of cardiac peptides [10]. NT-proBNP levels were measured at nine different timepoints throughout the duration of the trial.

We summarized demographic variables and laboratory measurements at study begin in the two study groups ETL and ALFA, using median (IQR) for continuous variables and count (frequency) for categorical variables. To assess if the medication was associated with the change in LAVI throughout the study period, we fitted an ANCOVA model for the delta of LAVI per subject (i.e., LAVI at study end minus LAVI at baseline) with medication as the covariate of interest, adjusted for LAVI at baseline. We conducted this primary analysis for the intention-to-treat (ITT) and the per-protocol (PP) study cohorts. For sensitivity analyses of the primary results, we fitted an ANCOVA model (using ITT data) with additional adjustments for the randomization factors of the original trail (dialysis center and residual kidney function). To check the effect of highly influential data points, we refitted the ITT model with winsorized data, i.e., the clipping of data points below and above predefined quantiles to the quantile values, which we set to the 0.5%/99.5% and 2.5% and 97.5% quantiles in two distinct models.

For the secondary analysis, we included additional covariates for the study deltas (i.e., study end minus study baseline) of LVMI, lung ultrasound, BCM, and NT-proBNP to the main ITT model in four distinct ANCOVA models and compared the regression coefficients and adjusted R² values of the new models to the primary model. We further depicted scatter plots and reported Pearson correlations between the study delta of LAVI and the four potential mediators. Due to skew distributions, BCM and NT-proBNP entered the models on the log₂ scale. Furthermore, for these two markers repeated measurements throughout the study were available. In addition to the adjustments for BCM and NT-proBNP delta – which only used the first and last measurements – we derived estimates for the change of these markers over time per study participants. This was achieved via linear mixed-effects regression models with a fixed effect for time since baseline and a random intercept and slope per subject. We defined the change of BCM and NT-proBNP as the sum of the fixed and random slope effect. These estimates of parameter change over time were then used as an adjustment in two ANCOVA models, which were again compared to the primary model.

For all regression models, we checked the model assumptions via visual assessments of outcome distributions and residual analyses (histograms, qq-plots). We reported regression coefficients with 95% confidence intervals and respective p values at a significance level of 95%. For the ANCOVA models, we further calculated adjusted R² in order to compare models. All p values are of exploratory nature; hence, we did not correct them for multiple testing. Since this is a post hoc subanalysis, the sample size was determined by the sample size of the original trial.

This post hoc analysis comprised 62 ITT patients included in the original study, of which 32 were treated with ETL and 30 with ALFA. When reduced to participants where the study protocol was followed (PP), 10 patients had to be excluded, five in each treatment group (6 patients received a kidney transplant, 3 patients died, and 1 patient discontinued hemodialysis due to renal recovery).

Table 1 shows the baseline characteristics of patients in the two medication groups, ETL and ALFA, using the ITT cohort. The study cohort was well balanced regarding all considered parameters, which included demographics, randomization factors, comorbidities, CMR parameters, and volume status assessments.

Figure 1 depicts the absolute LAVI levels at baseline and study end in the two treatment arms (Fig. 1a) and compares the LAVI deltas, i.e., the difference in LAVI between baseline and study end, by medication (Fig. 1b). The boxplots indicate that LAVI tended to increase throughout the study in patients treated with ALFA, but not when treated with ETL. Table 2 summarizes ITT and PP ANCOVA models for the LAVI delta by medication, with adjustment for baseline LAVI. In line with Figure 1, we observed a trend toward an effect of ETL versus ALFA treatment on LAVI delta (β = −5.0 [95% CI: −10, 0.04], p = 0.052) in the ITT population. This effect became numerically/statistically significant in the PP cohort (β = −5.8 [95% CI: −11, −0.36], p = 0.037). The adjusted R² in the ITT model was $Radj2$ = 0.259, which is increased to $Radj2$ = 0.302 using PP data. These results were very similar in the conducted sensitivity analyses (additional adjustments for randomization factors, winsorized data). At baseline, the percentage of cases with LAVI values below the mean was similar between the two treatment groups. At the follow-up, the disparity increased, with the ETL group demonstrating an 11% higher proportion of patients presenting LAVI values below the mean compared to the ALFA group.

Scatterplots of the study delta of LAVI versus the deltas of LVMI, LCTS, BCM, and NT-proBNP and pairwise Pearson correlations (Fig. 2) showed that from the four variables, only the delta in LVMI indicated a positive correlation (r = 0.387) with LAVI delta. Table 3 summarizes ANCOVA models incorporating additional adjustments for the study deltas of LVMI, LCTS, BCM, and NT-proBNP, in order to compare these models to the main ITT ANCOVA model from Table 2. In a close relationship with the correlations, out of the four variables we considered, only the inclusion of LVMI delta substantially changed the medication effect, which decreased from β = −5.0 [95% CI: −10, 0.04] to β = −3.3 [95% CI: −8.3, 1.7]. The increase in adjusted R² from 0.259 to 0.323 and the decreased significance (p = 0.052 vs. p = 0.2) when the LAVI delta is in included in the ANCOVA model, in addition to the positive correlation between LAVI delta and LVMI delta, suggest that the treatment effect on LAVI could be mediated by LVMI. For the other three variables, no such observation could be made, as correlations were close to zero and the effect estimates as well as adjusted R² values did not change substantially. With BCM and NT-proBNP, we also calculated models adjusting for variable change over time, derived from a linear mixed-effects model in order to facilitate all data available. However, the differences between the models with adjustment for the study delta and adjustment for the derived change parameter were very small.

The findings of this study indicate that the use of ETL in patients undergoing maintenance hemodialysis effectively halts the progression of LA enlargement when compared to the current standard therapy for sHPT, ALFA. This preventive effect on LA enlargement can be attributed to the impact of ETL on reducing left ventricular hypertrophy.

Elevated LAVI is recognized as an independent risk factor for all-cause mortality, both in the general population and among hemodialysis patients. There exists a notable inverse correlation between renal function and LAV, indicating that LAV tends to increase as the renal function declines [6]. Furthermore, LAV is considerably higher in dialysis patients compared to healthy individuals of similar age and gender [27]. LAVI exceeding 28 mL/m² is classified as an increased level, mild being 29–33 mL/m², moderate being 34–39 mL/m², and severe being ≥40 mL/m² [26]. In line with this classification, the hemodialysis population included in this trial exhibited significantly elevated LAVI levels at baseline, and these levels further increased under ALFA medication, but not with ETL.

In our previous findings, we demonstrated that ETL treatment effectively prevented the progression of LVMI in this specific study cohort. Furthermore, we suggested that fibroblast growth factor 23-mediated cardiac hypertrophy may be the underlying mechanism [17, 28]. In this subanalysis, we were able to establish a correlation between the impact of the study medication on LAVI and the changes observed in LVMI. These results align with the previous data, indicating a close relationship between LA size and LVM, with LV hypertrophy being a significant factor contributing to LAV, particularly among hemodialysis patients [29‒32]. Both LAVI and LVMI are critical parameters utilized in the diagnosis of heart failure, a highly prevalent CV condition across all stages of chronic kidney disease [33, 34].

Studies have demonstrated that reductions in LAVI can be achieved through improved blood pressure control and as a result of heart valve surgery. Notably, both interventions also lead to a decrease in LVMI [35‒38]. The association between reductions in LV hypertrophy achieved through blood pressure therapy and decreases in LAV was demonstrated, highlighting the interconnection between these two parameters [39]. Previous reports indicated that in the population of ESKD, LAV exhibits a comparable prognostic significance to LVMI. Importantly, LAV maintains an independent association with the occurrence of CV events [29]. The predictive value of both parameters is significantly influenced by the presence of confounding risk factors, such as hypertension or obesity, which can contribute to their complexity [4]. In individuals with ESKD, it has been shown that kidney transplantation can lead to improvements in LAVI, primarily due to alterations in hemodynamic conditions [40, 41]. However, there is a scarcity of data regarding the effectiveness of medication used for treating sHPT on LAV in individuals undergoing maintenance hemodialysis.

A post hoc analysis from the PRIMO study demonstrated that treatment with paricalcitol was associated with a decrease in LAVI [42]. This finding appears to contrast with our study results, considering that both paricalcitol and ALFA are active vitamin D medications used for treating sHPT in hemodialysis patients. However, it is important to note that the PRIMO trial included patients with a glomerular filtration rate between 15 and 60 mL/min/1.73 m², which differs from our study cohort consisting of ESKD patients [43].

Gaining insights into the mechanistic distinctions between vitamin D and calcimimetic therapy is crucial, as the latter drug may exhibit pleiotropic effects. The decline in kidney function leads to alterations in vitamin D metabolism, resulting in decreased levels of calcitriol, which subsequently leads to lowered serum calcium levels and impaired phosphate excretion [44]. SHPT emerges as an adaptive process in response to these dysregulations. Vitamin D and calcimimetics are commonly employed treatment options for sHPT [45]. Vitamin D treatment aims to address the deficiency of calcitriol by enhancing the intestinal reabsorption of calcium and phosphate, consequently suppressing PTH synthesis [46]. However, calcimimetics interact with the calcium-sensing receptor in the parathyroid gland, heightening its sensitivity to circulating calcium levels, thereby reducing PTH and fibroblast growth factor 23 concentrations [47].

Volume overload is a significant contributing factor to the enlargement of the LA cavity, particularly in the context of hemodialysis [48]. However, in this study, commonly utilized methods for assessing volume status, such as BCM, lung ultrasound, and measurements of NT-proBNP, did not show an association with changes in LAVI. The primary focus of this trial was to detect the treatment effect on LVMI. To minimize confounding factors, the study population underwent careful screening for overhydration, and only patients who achieved and maintained their individual optimal dry weight at the end of dialysis were included [18]. This approach aimed to mitigate the impact of fluid overload, which is a significant risk factor for increased LVM. Moreover, the volume status was continuously evaluated during the trial, and if hypervolemia was detected, adjustments to the dry weight were made based on clinical judgment and standard of care practices.

The trial has certain limitations that should be acknowledged. These include a relatively short duration of treatment and observation to detect changes in cardiac remodeling. Another limitation is the small sample size that was originally designed to assess a different outcome parameter. The analysis revealed a more pronounced impact of the medication on LAVI in the PP analysis compared to the ITT analysis, indicating that a longer duration of treatment may potentially enhance the observed effect. Furthermore, enhancing the informative value of the study could be achieved by crossing the two treatment groups after the initial year and conducting a reevaluation at the end.

The trial possessed several notable strengths. These included its prospective and randomized design, the administration of intravenous medication rather than oral treatment, and the utilization of CMR as the imaging modality. CMR holds significant importance, as the previous studies have demonstrated that echocardiography tends to underestimate atrial volumes when compared to CMR imaging [49]. CMR is a well-established technique for evaluating cardiac deformation, as it provides excellent delineation of endocardial and epicardial borders [50, 51].

In conclusion, our findings suggest that ETL treatment in hemodialysis patients effectively halted the progression of LAVI when compared to ALFA. This effect may be attributed to the associated changes in LVMI resulting from the treatment. Considering that both LA size and LVM are well-known CV risk factors, it is reasonable to speculate that preventing cardiac dilation could potentially alleviate the substantial burden of CV mortality in this population.

We thank the nursing staff of the General Hospital of Vienna and Vienna Dialysis Center for their assistance in the blood sample collections from subjects. We also thank the medical assistants of the Department of Cardiovascular and Interventional Radiology (Medical University of Vienna) and the lab technicians of the Department of Laboratory Medicine (Medical University of Vienna) for their assistance in study procedures.

Subjects have given their written informed consent and the trial was approved by the Ethics Committee of the Medical University of Vienna (MUV; EK # 1127/2017) and the national regulatory authorities (AGES # 10087746) and conducted in accordance with the principles of the Declaration of Helsinki.

Dr. Dörr and Dr. Reindl-Schwaighofer have a patent “Methods of treating left ventricle hypertrophy” pending. The other authors have nothing to disclose.

The study was sponsored by the Medical University of Vienna and by an unrestricted investigator-initiated research grant from Amgen (IIP #20167811).

Katharina Dörr and Roman Reindl-Schwaighofer were responsible for the conceptualization and methodology of the trial. Katharina Dörr was tasked with the investigation, including data collection, with the support by Matthias Lorenz. Sebastian Hödlmoser was assigned with the formal analysis and software. Dietrich Beitzke was the blinded radiologist, performing the analysis of CMR data. Rodrig Marculescu was responsible for laboratory analysis. Writing of the original draft was performed by Katharina Dörr and reviewed and edited by the coauthors.

The trial registration URL: https://clinicaltrials.gov/ct2/show/NCT03182699. Unique identifier: NCT03182699.

The data underlying this article will be shared on reasonable request to the corresponding author.