In this prospective Chinese cohort of 506 maintenance HD patients followed for up to 60 months, we found that elevated galectin-3 concentrations were associated with increased risks for CV mortality instead of all-cause mortality. Multivariable analysis results persisted even after following a 10% change-in-estimate principle. Galectin-3 may be a promising marker for CV risk stratification in maintenance HD patients.

Galectin-3 is expressed predominantly by activated macrophages and involved in multiple pathological processes, including fibrosis, inflammation, and tumor growth [13]. Accumulating evidence indicates that galectin-3 plays a key role in fibrogenesis in different organ systems, including liver, kidney, lung, and myocardial [22]. Increased serum galectin-3 levels activate a variety of profibrotic factors and induce cardiac fibroblasts to proliferate and transform, contributing to myocardial fibrosis and adverse remodeling [13]. In addition to acting as a direct profibrotic agent, galectin-3 also mediates aldosterone-induced cardiac, vascular, and renal fibrosis [23]. Since progressive cardiac fibrosis is an essential aspect in the evolution of cardiac dysfunction and a substrate for lethal arrhythmias and sudden death, [24] it is intuitive that a blood marker of cardiac fibrosis would be a prognostic factor for survival and CV events [25].

A recent meta-analysis [26] of four epidemiologic studies [1, 15,16,17] found no association between higher serum levels of galectin-3 and the risk of all-cause death in maintenance HD patients (HR = 1.17, 95% CI 0.96–1.42). This is consistent with our findings that galectin-3 is not a sensitive biomarker for all-cause mortality in maintenance HD patients. In addition, the meta-analysis of two studies [15, 17] also supports our results based on the secondary endpoint and suggests that galectin-3 may be a reliable predictor of CV mortality in maintenance HD patients (HR = 1.06, 95% CI 1.00–1.13). Among patients with ESRD, 40 to 50% of deaths have been attributed to CV disease [27,28,29]. Several studies have shown that CV mortality is the leading cause of death in patients receiving hemodialysis or peritoneal dialysis and is 10 to 20 times higher in this population than in the general population [30, 31]. Some biomarkers, such as serum triglyceride to high-density lipoprotein cholesterol ratio, [32] N-terminal pro-B-type natriuretic peptide, [33] and uric acid, [34] have been found to have predictive values for CV mortality in maintenance HD patients. In a study involving 423 HD patients, [1] there were 78 composite outcomes (a composite of all-cause death or cerebrocardiovascular events) during a mean follow-up of 2.1 ± 0.4 years. The results showed that galectin-3 was significantly associated with the composite outcome [1]. To date, only two prior studies [15, 17] with inconsistent results have examined the association of galectin-3 with CV mortality in maintenance HD patients. In a prospective cohort study of 86 adults on HD in Taiwan province, China, Ko et al. did not find an association between CV mortality and galectin-3 levels (HR = 1.04, 95% CI 0.99–1.10) after adjusting for age, C-reactive protein, albumin, normalized protein catabolic rate, vascular cell adhesion molecule 1, and smoking [15]. Although the HD population (taking into account age, gender composition, and ethnicity) was homogeneous with our study, sample size, adjustment factors, and determination method of the optimal cutoff point of galectin-3 could account for inconsistent findings to some extent. Notably, the galectin-3 level cutoff points were produced using the X-tile program in our study, which identified the cutoff with the minimum P values from log-rank χ2 statistics for the categorical galectin-3 level in terms of survival [19]. However, in Ko et al.’s study, [15] the cutoff point was simply determined based on the mean galectin-3 level of the whole study population. In a post hoc analysis of the 4D Study (Die Deutsche Diabetes Dialyse Studie), Drechsler et.al focused on 1168 dialysis patients with type 2 diabetes mellitus followed for 4 years and found that log-transformed galectin-3 level was associated with CV events defined as a composite of cardiac death in both unadjusted (HR = 1.13, 95% CI 1.03–1.24) and fully adjusted (HR = 1.12, 95% CI 1.01–1.24) models [17]. Patients suffering from type 2 diabetes mellitus undergoing dialysis were enrolled in this cohort; as a result, the findings may not be generalizable to the overall HD population. In the present study, participants had multiple causes of ESRD, making our findings generalizable to the overall maintenance HD population at large.

Our study has several strengths. A main advantage is the relatively large sample size, which allows us to explore the associations between galectin-3 level and all-cause and CV mortality in maintenance HD patients in a more statistically precise manner. Second, in our study, predefined outcomes including both all-cause and CV mortality were prospectively observed over a relatively long-term follow-up (60 months). Third, as mentioned earlier, we used the method described by Camp et al. to determine the optimal cutoff point for galectin-3. In addition, the RMST difference was used to detect a true treatment effect when there was a crossing-curves problem [35, 36]. Finally, according to a 10% change-in-estimate principle, our analyses were adjusted for a large number of potential confounders.

There are several study limitations to be considered in the interpretation of our study findings. First, in our study, only baseline galectin-3 levels were obtained and we did not have serial measurement of galectin-3 over time. Single-point measurement may not reflect substantial intra-individual variability over time and may increase the probability of random measurement error. On the other hand, incomplete adjudication of cause of death may have led to misattribution of CV deaths as noncardiovascular. Second, our HD patients were all from the same Hospital in China and whether the findings of the present study can be extrapolated to patients of other countries is unclear. In addition, all maintenance HD patients were Asian in the present study, thus the generalizability of the study findings across ethnicities remains unclear. Third, due to the unavailability of data, several traditional and non-traditional risk factors for CV death, such as serum high sensitivity C-reactive protein, smoking, nutritional parameters and residual renal function or urine volume [37], were not adjusted in multivariable models. Therefore, as with other studies, our study may be limited by residual confounding. However, the E-value sensitivity analysis suggested that the observed HR of 2.13 for CV mortality could only be explained by an unmeasured confounder that was associated with both galectin-3 and risk of CV death by a risk ratio of more than 2.76 above and beyond that of the confounders that were measured in the present study. Therefore, it is implausible that an unmeasured confounder exists than can negate the effect of galectin-3 observed in the current analysis study. Fourth, because we did not have data on other cardiac biomarkers, such as N-terminal pro-B-type natriuretic peptide and troponin etc., combined analyses were not possible in our study. Finally, considering the observational nature of study design, our findings cannot show causality between galectin-3 and CV death in patients on maintenance HD. However, we add new epidemiological evidence that galectin-3 may be a novel biomarker for CV risk stratification in patients receiving HD treatment.

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