Original ArticlesMaintenance Dialysis

Association of Parameters of Mineral Bone Disorder with Mortality in Patients on Hemodialysis according to Level of Residual Kidney Function

Mengjing Wang, Yoshitsugu Obi, Elani Streja, Connie M. Rhee, Wei Ling Lau, Jing Chen, Chuanming Hao, Takayuki Hamano, Csaba P. Kovesdy and Kamyar Kalantar-Zadeh
CJASN July 2017, 12 (7) 1118-1127; DOI: https://doi.org/10.2215/CJN.11931116

Abstract

Background and objectives The relationship between mineral and bone disorders and survival according to residual kidney function status has not been previously studied in patients on hemodialysis. We hypothesized that residual kidney function, defined by renal urea clearance, modifies the association between mineral and bone disorder parameters and mortality.

Design, setting, participants, & measurements The associations of serum phosphorus, albumin-corrected calcium, intact parathyroid hormone, and alkaline phosphatase with all-cause mortality were examined across three strata (<1.5, 1.5 to <3.0, and ≥3.0 ml/min per 1.73 m2) of baseline residual renal urea clearance using Cox models adjusted for clinical characteristics and laboratory measurements in 35,114 incident hemodialysis patients from a large United States dialysis organization over the period of 2007–2011.

Results A total of 8102 (23%) patients died during the median follow-up of 1.3 years (interquartile range, 0.6–2.3 years). There was an incremental mortality risk across higher serum phosphorus concentrations, which was pronounced among patients with higher residual renal urea clearance (Pinteraction=0.001). Lower concentrations of serum intact parathyroid hormone were associated with higher mortality among patients with low residual renal urea clearance (i.e., <1.5 ml/min per 1.73 m2), whereas higher concentrations showed a higher mortality risk among patients with greater residual renal urea clearance (i.e., ≥1.5 ml/min per 1.73 m2; Pinteraction<0.001). Higher serum corrected total calcium and higher alkaline phosphatase concentrations consistently showed higher mortality risk (Ptrend<0.001 for both) irrespective of residual renal urea clearance strata (Pinteraction=0.34 and Pinteraction=0.53, respectively).

Conclusions Residual kidney function modified the mortality risk associated with serum phosphorus and intact parathyroid hormone among incident hemodialysis patients. Future studies are needed to examine whether taking account for residual kidney function into the assessment of mortality risk associated with serum phosphorus and intact parathyroid hormone improves patient management and clinical outcomes in the hemodialysis population.

Introduction

Mineral and bone disorder (MBD), characterized by abnormal serum concentrations of calcium, phosphorus, intact parathyroid hormone (PTH), and alkaline phosphatase (ALP), are a common complication in patients with CKD, especially in those with ESRD (1). The above MBD abnormalities may lead to high mortality risk due to adverse cardiovascular or infection-related pathways (2–5). However, those abnormalities may be attenuated in patients on hemodialysis with substantial residual kidney function (RKF) who maintain greater solute clearance (6). Preserved RKF also offers other clinical benefits, including lower ultrafiltration volume, less intradialytic hypotension, and lower prevalence of anemia as well as decreased progression rate of malnutrition, inflammation, erythropoietin resistance, and ventricular hypertrophy (6–8). Therefore, the associations of such clinical parameters with mortality and the effect of interventions on patient survival may differ depending on RKF levels among patients on hemodialysis. Indeed, several studies have suggested that frequent hemodialysis is beneficial to those with little or no RKF but may be detrimental to those with substantial RKF (9–11).

However, few studies have taken RKF levels into account when evaluating associations between MBD markers and mortality in patients on hemodialysis, although up to 45% of patients in the United States initiate maintenance dialysis at eGFRs>10 ml/min per 1.73 m2 (12,13). Hence, we hypothesized that RKF levels modify the associations of serum phosphorus, calcium, intact PTH, and ALP with all-cause mortality in patients on hemodialysis.

Materials and Methods

Patients

We retrospectively extracted, refined, and examined data from all incident hemodialysis patients who initiated treatment between 2007 and 2011 and were treated for ≥60 consecutive days in facilities operated by a large dialysis organization in the United States. Patients were followed up from their first dialysis date to December 31, 2011. Of the 133,162 incident ESRD patients who were treated with in-center thrice-weekly hemodialysis as their initial dialysis modality, we excluded 21,125 patients who were ever treated with other modalities; 3012 who had missing data on MBD parameters, such as serum phosphorus, calcium, intact PTH, or ALP, at baseline (i.e., the first quarter or 91 days of dialysis); and 73,911 who had missing data on baseline residual renal urea clearance (rCLurea) (Supplemental Figures 1). Our final study population consisted of 35,114 incident hemodialysis patients. This study was approved by the University of California Irvine Medical Center and the University of Washington with the exemption of obtaining written consent given the large sample size, anonymity of the patients studied, and nonintrusive nature of the research.

Demographic, Clinical, and Laboratory Measures

Information on all-cause death, race/ethnicity, primary insurance, vascular access type, comorbidities, and laboratory variables were obtained from the electronic database of the dialysis provider.

Blood samples were drawn using uniform techniques in all dialysis clinics and transported to the central laboratory in Deland, Florida, typically within 24 hours. All laboratory values were measured by automated and standardized methods. Most laboratory values were measured monthly, including serum urea nitrogen, creatinine, albumin, calcium, phosphorus, and bicarbonate. Serum ferritin and intact PTH were measured at least quarterly. Hemoglobin was measured at least monthly in all patients and weekly to biweekly in most patients. Most blood samples were collected predialysis, with the exception of the postdialysis urea that was obtained to calculate urea kinetics.

We used rCLurea as the index of RKF in all analyses. The average serum urea concentrations during collection were assumed to be 90% of the predialysis concentrations according to the approach by Daugirdas et al. (14), and thus, rCLurea was calculated as follows:Embedded Imagewhere serum urea nitrogen was obtained on the closest day within ±28 days of urine collection. Urine collected time was reported as 1440 minutes in 98% of measurements, ranging from 720 to 2880 minutes. We then adjusted rCLurea for body surface area and expressed it as milliliter per minute per 1.73 m2 (15,16). Normalized protein catabolic rate (nPCR) was calculated accounting for rCLurea (17,18).

To minimize measurement variability, averaged values of laboratory variables, including rCLurea, during the first patient-quarter (or the first 91 days of dialysis) within each patient served as baseline data and were used in all models.

Statistical Analyses

Differences in baseline characteristics between included versus excluded patients were compared by standardized differences (19,20). Patients were categorized into three groups according to baseline rCLurea strata (<1.5, 1.5 to <3.0, and ≥3.0 ml/min per 1.73 m2), and associations of patient characteristics with rCLurea categories were evaluated by nonparametric trend tests. The cutoff value of 3.0 ml/min per 1.73 m2 was selected on the basis of the definition of substantial RKF in the previous studies and guidelines (11,21,22). To evaluate trends across rCLurea levels, we also used an additional cutoff point at 1.5 ml/min per 1.73 m2, so that all groups maintained reasonable sample sizes, even after being stratified by each MBD parameter. MBD parameters were treated as categorical variables, and their association with all-cause mortality was examined by Cox proportional hazard models.

For each analysis, we used hierarchical adjustment with three models as follows: (1) unadjusted models that included the a priori–defined categories of each one of the exposures (i.e., phosphorus, uncorrected or albumin-corrected calcium, intact PTH, or ALP); (2) case mix–adjusted models that included the above variables plus age, sex, race/ethnicity, primary insurance, central venous catheter use, hypertension, diabetes, history of cardiovascular disease (i.e., congestive heart failure, atherosclerotic heart disease, cerebrovascular disease, or other cardiovascular disease), rCLurea, and single-pool Kt/V; and (3) case mix– plus malnutrition-inflammation cachexia syndrome (MICS)–adjusted models that included all covariates in the case mix model plus body mass index, nPCR, hemoglobin, serum albumin, creatinine, ferritin, and the use of medications, including vitamin D receptor activators (i.e., calcitriol, paricalcitol, or doxercalciferol either oral or intravenous), calcium-containing phosphorus binders, and noncalcium-containing phosphorus binders (i.e., sevelamar and lanthanum), as well as MBD parameters other than the exposure of interest (i.e., phosphorus, uncorrected calcium, and natural log–transformed intact PTH and ALP).

We defined the fully adjusted model (i.e., case mix– plus MICS–adjusted models) as the primary model. Hazard proportionality was confirmed by Schoenfeld residuals. Associations of MBD markers with mortality were also evaluated across strata of rCLurea. Effect modification of the association between each MBD parameter and mortality by rCLurea was evaluated by creation of interaction terms and use of the Wald test. We also categorized patients into a total of 12 or 15 groups according to combined baseline levels of rCLurea and each MBD parameter and examined their associations with mortality. Consistent results were observed in sensitivity analyses using restricted cubic spline functions with four knots (Supplemental Figures 2–6) or excluding patients with rCLurea>15 ml/min per 1.73 m2 (data not shown).

The frequency of missing data was low (<1% for most laboratory tests, except for nPCR [6%] and creatinine [4%]), and multiple imputation methods with five datasets were used in all regression analyses. Analyses were conducted using STATA MP, version 13.1 (StataCorp, College Station, TX).

Results

Baseline Characteristics

The cohort included 35,114 incident hemodialysis patients, in whom the mean±SD age was 62±15 years old; there were 63% men, 55% non-Hispanic white, and 27% non-Hispanic black, and 59% of patients had diabetes. Mean or median serum baseline phosphorus, albumin-corrected calcium, intact PTH, and ALP levels were 5.0±1.1 mg/dl, 9.1±0.5 mg/dl, 312 (interquartile range [IQR], 201–477) pg/dl, and 84 (IQR, 67–110) U/L, respectively. The prevalence rates of patients with low (<1.5 ml/min per 1.73 m2), middle (1.5 to <3.0 ml/min per 1.73 m2), and high (≥3.0 ml/min per 1.73 m2) rCLurea levels were 20%, 28%, and 52%, respectively. Median urine volume was 300 (IQR, 200–450), 600 (IQR, 500–900), and 1200 (IQR–850, 1675) ml/d in the low, middle, and high rCLurea groups, respectively. Patients with greater rCLurea tended to have higher albumin and uncorrected calcium levels and had lower creatinine, phosphorus, intact PTH, and ALP levels (Table 1). A total of 8102 (23%) patients died during the median follow-up of 1.3 years (IQR, 0.6–2.3 years), with an incidence of 15.0 deaths per 100 patient-years. The leading cause of death was cardiovascular disease (40%) followed by withdrawal from dialysis/uremia (10%), infection (7%), and malignancy (4%).

View this table:
Table 1.

Baseline characteristics of 35,114 incident hemodialysis patients stratified by baseline residual renal urea clearance

Compared with 76,923 excluded patients who lacked data on baseline rCLurea, phosphorus, albumin-corrected calcium, intact PTH, or ALP, the 35,114 included patients were more likely to be men, non-Hispanic white, and vitamin D receptor activator users; had higher levels of body mass index, Kt/V, hemoglobin, and albumin; and had lower levels of ALP and ferritin (standardized difference >0.1) (Supplemental Table 1). Associations of these MBD parameters with all-cause mortality were found to be similar between included versus excluded patients in the fully adjusted models without adjustment for rCLurea and nPCR, the missingness of which was the most common reason for exclusion (>95%) (Supplemental Figure 7).

Association of Phosphorus and All-Cause Mortality according to rCLurea Strata

In the unadjusted model, higher serum phosphorus was associated with better survival. This association was attenuated in the case mix model and even reversed in the MICS model (fully adjusted model) across all rCLurea strata (Figure 1, A–C). Fully-adjusted mortality risk associated with serum phosphorus was significantly modified by rCLurea (Pinteraction=0.001), in which the association of higher serum phosphorous with mortality was more pronounced across higher levels of rCLurea: adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) of the highest phosphorous group (≥7.0 mg/dl) versus the second lowest group (4.0 to <5.0 mg/dl) were 1.31 (95% CI, 1.05 to 1.64), 1.77 (95% CI, 1.45 to 2.17), and 1.93 (95% CI, 1.59 to 2.33) among patients in the low, middle, and high rCLurea strata, respectively (Figure 1, A–C). When categorizing patients into 15 groups according to combined baseline levels of serum phosphorus and rCLurea (reference: serum phosphorous =4.0–5.0 mg/dl and rCLurea≥3.0 ml/min per 1.73 m2), a trend toward lower mortality risk was observed across higher rCLurea within given serum phosphorus categories <6.0 mg/dl (Ptrend<0.001) but was not observed within the higher categories (Figure 1D).

Figure 1.
Figure 1.

Higher mortality risk associated with higher serum phosphorus was observed across the three strata of renal urea clearance (rCLurea) but pronounced among patients with greater rCLurea. Association of baseline serum phosphorus with all-cause mortality in 35,114 incident hemodialysis patients with baseline rCLurea of (A) <1.5, (B) 1.5 to <3.0, and (C) ≥3.0 ml/min per 1.73 m2 and (D) the mortality risk of 15 groups stratified by baseline rCLurea and serum phosphorus in the case mix and malnutrition-inflammation cachexia syndrome (MICS) model (phosphorus of 4.0 to <5.0 mg/dl with rCLurea≥3.0 ml/min per 1.73 m2 as the reference).

Association of Calcium and All-Cause Mortality according to rCLurea Strata

The overall mortality risk associated with higher albumin-corrected calcium was higher in all models (Ptrend≤0.002 for all models). Compared with the middle corrected calcium group (i.e., 8.8 to <9.2 mg/dl), aHR was 1.08 (95% CI, 1.01 to 1.16) in the highest group (i.e., ≥9.6 mg/dl) overall (Supplemental Figure 7B). The association between corrected calcium and mortality was not significantly modified by rCLurea in the fully adjusted model (Pinteraction=0.34), and the trend in the adjusted association between corrected calcium and mortality seemed consistent across rCLurea strata (Figure 2, A–C). Higher rCLurea was consistently associated with lower mortality risk across serum calcium categories in models evaluating 15 groups of combined rCLurea and corrected calcium levels (reference: corrected calcium =8.8 to <9.2 mg/dl and rCLurea≥3.0 ml/min per 1.73 m2; Ptrend<0.001 for all)(Figure 2D). Consistent patterns were observed in the association between uncorrected calcium and mortality (Supplemental Figure 8).

Figure 2.
Figure 2.

The association between higher baseline albumin-corrected serum calcium and higher mortality was consistent across the three strata of renal urea clearance (rCLurea). Association of baseline albumin-corrected serum calcium with all-cause mortality in 35,114 incident hemodialysis patients with baseline rCLurea of (A) <1.5, (B) 1.5 to <3.0 2, and (C) ≥3.0 ml/min per 1.73 m2 and (D) the mortality risk of 15 groups stratified by baseline rCLurea and albumin-corrected calcium in the case mix and malnutrition-inflammation cachexia syndrome (MICS) model (albumin-corrected calcium of 8.8 to <9.2 mg/dl with rCLurea≥3.0 ml/min per 1.73 m2 as the reference).

Association of PTH and All-Cause Mortality according to rCLurea Strata

Higher serum intact PTH levels were associated with lower risk of mortality in the unadjusted models across all three rCLurea groups. In the fully adjusted model, this association was attenuated but still significant in the lowest rCLurea group (P=0.004), but it reversed in the middle and highest rCLurea groups (P=0.05 and P<0.01, respectively; Pinteraction<0.001) (Figure 3, A–C). Compared with the second lowest PTH group (150 to <300 pg/ml), the aHRs of the lowest group (<150 pg/ml) were 1.05 (95% CI, 0.92 to 1.19), 0.94 (95% CI, 0.83 to 1.07), and 0.99 (95% CI, 0.90 to 1.09) among patients in the low, middle, and high rCLurea groups, respectively, whereas the aHRs of the highest intact PTH group (≥600 pg/ml) versus the reference were 0.93 (95% CI, 0.79 to 1.09), 1.11 (95% CI, 0.96 to 1.29), and 1.12 (95% CI, 0.99 to 1.26) among patients in the low, middle, and high rCLurea groups, respectively. Models using spline functions yielded consistent results (Supplemental Figure 5). When categorizing patients into 12 groups according to baseline levels of intact PTH and rCLurea, the mortality risk in the high rCLurea group versus the low rCLurea group was attenuated to some extent in higher intact PTH levels but consistently lower across PTH categories (reference: intact PTH =150 to <300 pg/ml and rCLurea≥3.0 ml/min per 1.73 m2) (Figure 3D).

Figure 3.
Figure 3.

Lower serum intact parathyroid hormone (PTH) showed a higher mortality risk among patients with low renal urea clearance (rCLurea), whereas higher serum PTH was associated with higher mortality among patients with high rCLurea. Association of baseline serum intact PTH with all-cause mortality in 35,114 incident hemodialysis patients with baseline rCLurea of (A) <1.5, (B) 1.5 to <3.0, and (C) ≥3.0 and (D) the mortality risk of 12 groups stratified by baseline rCLurea and serum intact PTH in the case mix and malnutrition-inflammation cachexia syndrome (MICS) model (intact PTH of 150 to <300 pg/ml with rCLurea≥3.0 ml/min per 1.73 m2 as the reference).

Association of ALP and All-Cause Mortality according to rCLurea Strata

Higher ALP was associated with higher mortality irrespective of adjustment models overall. Compared with the middle ALP group (i.e., 60 to <80 IU/L), the highest group (i.e., ≥120 IU/L) was associated with higher mortality risk with aHR of 1.36 (95% CI, 1.28 to 1.45) (Supplemental Figure 7D). The association between ALP and mortality was not significantly modified by rCLurea in the fully adjusted models (Pinteraction=0.53). Trends in the adjusted association between ALP and mortality were consistent across rCLurea strata (Figure 4, A–C), which was also supported in models using restricted cubic splines (Supplemental Figure 6). When categorizing patients into 15 groups according to baseline levels of ALP and rCLurea, higher rCLurea was consistently associated with lower mortality risk across serum ALP categories (reference: ALP=60 to <80 U/L and rCLurea≥3.0 ml/min per 1.73 m2; Ptrend<0.001) (Figure 4D).

Figure 4.
Figure 4.

The association between higher baseline alkaline phosphatase (ALP) and higher mortality was consistent across the three strata of renal urea clearance (rCLurea). Association of baseline serum ALP with all-cause mortality in 35,114 incident hemodialysis patients with baseline rCLurea of (A) <1.5, (B) 1.5 to <3.0, and (C) ≥3.0 ml/min per 1.73 m2 and (D) the mortality risk of 15 groups stratified by baseline rCLurea and serum ALP in the case mix and malnutrition-inflammation cachexia syndrome (MICS) model (ALP of 60 to <80 U/L with rCLurea≥3.0 ml/min per 1.73 m2 as the reference).

Discussion

This study examined the modification of the association of several MBD parameters with mortality by RKF among incident hemodialysis patients and found several novel observations. RKF levels modified the association of phosphorus and intact PTH with all-cause death. The relative mortality risk associated with high serum phosphorus concentrations was stronger in patients with higher rCLurea levels. As for serum intact PTH, lower concentrations showed a higher mortality risk among patients with low rCLurea, whereas higher concentrations were associated with higher mortality among patients with high rCLurea levels. In contrast, higher concentrations of calcium and ALP were associated with all-cause death irrespective of rCLurea levels. Of note, higher rCLurea was associated with better survival across MBD marker categories, with the exception that patients with serum phosphorus ≥7.0 mg/dl showed comparable mortality risk irrespective of rCLurea levels.

Mortality risk associated with high serum phosphorus concentrations was pronounced in the high rCLurea group versus the low rCLurea group. Serum phosphorus was lower among patients on hemodialysis with higher rCLurea levels, which is consistent with the observation that RKF, even at such low levels, contributes to substantial clearance of phosphorus in patients with ESRD (23). High serum phosphorus levels among patients with high RKF may indicate nonadherence to diet, hemodialysis prescription, and/or medications, including phosphorus binders and cinacalcet, as well as high-turnover bone disease. High dietary phosphorus loading has been shown to induce inflammation, malnutrition, vascular calcification, and premature death in rodent CKD models (24,25), and nonuse of phosphorus binders has also been linked to higher mortality (26).

Previous studies have shown a U-shaped or linear association between serum calcium and mortality in patients on hemodialysis depending on the calcium categorizations, assays used, variables accounted for, statistical models, and the underlying study population (12,27–31). Our results also confirmed that higher serum calcium levels were associated with higher mortality risk in the overall analysis, which could be explained by several mechanisms, including vascular calcification, hypertension, and infection (32). Meanwhile, in contrast to the interaction between serum phosphorus and rCLurea, the association of serum calcium with all-cause mortality was not significantly modified by rCLurea. This finding may be explained by the fact that calcium is less likely to be affected by RKF than phosphorus. Recent calcium balance studies have consistently shown that calcium loads resulted in little or no increase in urinary calcium excretion, even in patients with CKD stages 3 and 4 (33,34). Calcium may be excreted into the urine at even lower levels in patients with ESRD and low RKF, and indeed, we did not observe significant differences in albumin-corrected calcium across rCLurea strata.

There have been mixed data on the PTH-mortality association in patients on hemodialysis (1), and these inconsistent findings may be explained by unmeasured or residual confounding by their RKF. Several-fold higher concentrations of intact PTH are required to maintain normal bone turnover among patients with ESRD (35), known as skeletal resistance to PTH (36). This phenomena is partly due to the diminished PTH receptor expression of osteoblast in the uremic milieu (37,38). Also, accumulated bioinactive 7–84 PTH fragment in patients with ESRD interferes with the second generation intact PTH assay, resulting in falsely higher values of PTH (39). However, these abnormalities in the uremic milieu are likely to be less severe among patients with substantial RKF compared with those with little or no RKF (6,40–42). Our study showed for the first time that higher intact PTH levels were associated with lower mortality among patients on hemodialysis with low RKF, whereas higher intact PTH levels showed a higher mortality risk among patients with substantial RKF. Additionally, the effect of impaired capacity of the bone to buffer mineral loads due to low bone turnover may be accentuated among patients with little or no RKF, resulting in accelerated cardiovascular calcification (43,44). In contrast, we observed a consistent association between higher ALP and higher mortality across rCLurea levels. Although PTH affects bone metabolism, ALP is excreted from the bone and arteries with calcification (45), and hence, it is a useful marker of bone metabolism and active osteochondrogenesis (46–48).

Our results can be interpreted from the other viewpoint of the effect modification of the association between RKF levels and mortality by MBD parameters. The association of higher RKF with better survival was attenuated among patients with higher levels of phosphorus and intact PTH. Nevertheless, patients with greater RKF consistently showed better survival even after rigorous adjustment, supporting the recently highlighted importance of RKF in the hemodialysis population (6,20).

Strengths of our study include its large sample size of patients on hemodialysis with RKF data and use of uniform laboratory measurements. However, several limitations should be noted. First, as with other observational studies, our study cannot prove causality. There may also be residual confounding or unmeasured confounders on the basis of vitamin D deficiency, inflammatory status, elevated fibroblast growth factor–23, treatment adherence, and inadequate predialysis care (49–54). Second, RKF may not be accurate given the use of rCLurea, the difficulties in punctual and complete collection of urine samples, and the use of factor 0.9 for estimating average predialysis serum urea. Nevertheless, the population-level associations can be estimated from an adequate number of patients if such errors are not associated with the outcome, and a recent study has shown that change in rCLurea used in this study was closely related to all-cause mortality (20). Third, the reason for urine being collected (or not collected) was not available in this administrative database, and potential selection bias may exist, because patients with limited RKF are less likely to have undergone urine collections. However, similar patterns of association between all MBD markers and mortality were observed between included and excluded patients, suggesting the independence of the eligibility criteria of this study from those associations. Fourth, we included exclusively incident hemodialysis patients, and it is unclear whether our findings can be extrapolated to prevalent hemodialysis patients. Fifth, cause-specific death was not examined given a limited number of each event, even with, so far, the largest number of patients on hemodialysis with data on rCLurea.

In conclusion, our study showed that RKF modified the association of serum phosphorus and intact PTH with all-cause mortality among incident hemodialysis patients, whereas serum calcium and ALP showed consistent associations with mortality irrespective of RKF. Future studies with a long-term follow-up period are needed to explain the underlying mechanisms of those associations and examine whether taking account for RKF in the assessment of mortality risk associated with serum phosphorus and intact PTH improves patient management and clinical outcomes among patients on hemodialysis.

Disclosures

K.K.-Z. has received honoraria from Abbott (Abbott Park, Illinois), Abbvie (North Chicago, Illinois), Alexion (New Haven, Connecticut), Amgen (Thousand Oaks, California), Astra-Zeneca (Wilmington, Delaware), Aveo (Cambridge, Massachusetts), Chugai (Berkeley Heights, New Jersey), DaVita (Denver, Colorado), Fresenius (Waltham, Massachusetts), Genentech (South San Francisco, California), Haymarket Media (Bute Gardens, London, UK), Hospira (Lake Forest, Illinois), Kabi (Lake Zurich, Illinois), Keryx (Boston, Massachusetts), Novartis (New York, New York), Pfizer (New York, New York), Relypsa (Redwood City, California), Resverlogix (Calgary, Alberta, Canada), Sandoz (Princeton, New Jersey), Sanofi-Aventis (Bridgewater, New Jersey), Shire (Lexington, Massachusetts), Vifor (Glattbrugg, Zurich, Switzerland), UpToDate (Waltham, Massachusetts), and ZS Pharma (Coppell, Texas).

Acknowledgments

The work in this manuscript was performed with the support of National Institute of Diabetes, Digestive and Kidney Disease (NIDDK) of the National Institutes of Health research grants R01-DK095668 (to K.K.-Z.), K24-DK091419 (to K.K.-Z.), and R01-DK078106 (to K.K.-Z.). Y.O. is supported by the Uehara Memorial Foundation Research Fellowship for Research Abroad. E.S. is supported by Department of Veterans Affairs grant IK2-CX001266-001. C.M.R. is supported by NIDDK grant K23-DK102903. C.P.K. is supported by NIDDK grants R01-DK096920 and U01-DK102163. K.K.-Z. is supported by philanthropic grants from Mr. Harold Simmons, Mr. Louis Chang, Dr. Joseph Lee, and Aveo.

Footnotes

  • Received November 21, 2016.
  • Accepted April 4, 2017.

References

  1. ↵
    1. Kidney Disease Improving Global Outcomes CKD-MBD Work Group
    : KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney Int 76: S1–S130, 2009
    OpenUrl
  2. ↵
    1. Schlüter KD,
    2. Piper HM
    : Left ventricular hypertrophy and parathyroid hormone: A causal connection? Cardiovasc Res 39: 523–524, 1998pmid:9798537
    OpenUrlCrossRefPubMed
    1. Amann K,
    2. Törnig J,
    3. Kugel B,
    4. Gross ML,
    5. Tyralla K,
    6. El-Shakmak A,
    7. Szabo A,
    8. Ritz E
    : Hyperphosphatemia aggravates cardiac fibrosis and microvascular disease in experimental uremia. Kidney Int 63: 1296–1301, 2003pmid:12631346
    OpenUrlCrossRefPubMed
    1. Shanahan CM,
    2. Crouthamel MH,
    3. Kapustin A,
    4. Giachelli CM
    : Arterial calcification in chronic kidney disease: Key roles for calcium and phosphate. Circ Res 109: 697–711, 2011pmid:21885837
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Wu M,
    2. Rementer C,
    3. Giachelli CM
    : Vascular calcification: An update on mechanisms and challenges in treatment. Calcif Tissue Int 93: 365–373, 2013pmid:23456027
    OpenUrlCrossRefPubMed
  6. ↵
    1. Mathew AT,
    2. Fishbane S,
    3. Obi Y,
    4. Kalantar-Zadeh K
    : Preservation of residual kidney function in hemodialysis patients: Reviving an old concept. Kidney Int 90: 262–271, 2016pmid:27182000
    OpenUrlCrossRefPubMed
    1. Marquez IO,
    2. Tambra S,
    3. Luo FY,
    4. Li Y,
    5. Plummer NS,
    6. Hostetter TH,
    7. Meyer TW
    : Contribution of residual function to removal of protein-bound solutes in hemodialysis. Clin J Am Soc Nephrol 6: 290–296, 2011pmid:21030575
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Penne EL,
    2. van der Weerd NC,
    3. Grooteman MP,
    4. Mazairac AH,
    5. van den Dorpel MA,
    6. Nubé MJ,
    7. Bots ML,
    8. Lévesque R,
    9. ter Wee PM,
    10. Blankestijn PJ; CONTRAST investigators
    : Role of residual renal function in phosphate control and anemia management in chronic hemodialysis patients. Clin J Am Soc Nephrol 6: 281–289, 2011pmid:21030579
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Chertow GM,
    2. Levin NW,
    3. Beck GJ,
    4. Daugirdas JT,
    5. Eggers PW,
    6. Kliger AS,
    7. Larive B,
    8. Rocco MV,
    9. Greene T; Frequent Hemodialysis Network (FHN) Trials Group
    : Long-term effects of frequent in-center hemodialysis. J Am Soc Nephrol 27: 1830–1898, 2016
    OpenUrlAbstract/FREE Full Text
    1. Rocco MV,
    2. Daugirdas JT,
    3. Greene T,
    4. Lockridge RS,
    5. Chan C,
    6. Pierratos A,
    7. Lindsay R,
    8. Larive B,
    9. Chertow GM,
    10. Beck GJ,
    11. Eggers PW,
    12. Kliger AS; FHN Trial Group
    : Long-term effects of frequent nocturnal hemodialysis on mortality: The Frequent Hemodialysis Network (FHN) nocturnal trial. Am J Kidney Dis 66: 459–468, 2015pmid:25863828
    OpenUrlCrossRefPubMed
  11. ↵
    1. Obi Y,
    2. Streja E,
    3. Rhee CM,
    4. Ravel V,
    5. Amin AN,
    6. Cupisti A,
    7. Chen J,
    8. Mathew AT,
    9. Kovesdy CP,
    10. Mehrotra R,
    11. Kalantar-Zadeh K
    : Incremental hemodialysis, residual kidney function, and mortality risk in incident dialysis patients: A cohort study. Am J Kidney Dis 68: 256–265, 2016pmid:26867814
    OpenUrlCrossRefPubMed
  12. ↵
    1. Wald R,
    2. Sarnak MJ,
    3. Tighiouart H,
    4. Cheung AK,
    5. Levey AS,
    6. Eknoyan G,
    7. Miskulin DC
    : Disordered mineral metabolism in hemodialysis patients: An analysis of cumulative effects in the Hemodialysis (HEMO) Study. Am J Kidney Dis 52: 531–540, 2008pmid:18657891
    OpenUrlCrossRefPubMed
  13. ↵
    1. US Renal Data System
    : USRDS 2013 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States, Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2013
  14. ↵
    1. Daugirdas J,
    2. Blake PG,
    3. Ing TS
    : Handbook of Dialysis, Philadelphia, Lippincott Williams & Wilkins, 2014
  15. ↵
    Anonymous: Clinical practice recommendations for peritoneal dialysis adequacy. Am J Kidney Dis 48[Suppl 1]: S130–S158, 2006pmid:16813985
    OpenUrlCrossRefPubMed
  16. ↵
    1. Mosteller RD
    : Simplified calculation of body-surface area. N Engl J Med 317: 1098, 1987pmid:3657876
    OpenUrlCrossRefPubMed
  17. ↵
    1. Depner TA,
    2. Daugirdas JT
    : Equations for normalized protein catabolic rate based on two-point modeling of hemodialysis urea kinetics. J Am Soc Nephrol 7: 780–785, 1996pmid:8738814
    OpenUrlAbstract
  18. ↵
    1. Eriguchi R,
    2. Obi Y,
    3. Streja E,
    4. Tortorici AR,
    5. Rhee CM,
    6. Soohoo M,
    7. Kim T,
    8. Kovesdy CP,
    9. Kalantar-Zadeh K
    : Longitudinal associations among renal urea clearance-corrected normalized protein catabolic rate, serum albumin, and mortality in patients on hemodialysis. Clin J Am Soc Nephrol 12: 1109–1117, 2017
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Schacht A,
    2. Bogaerts K,
    3. Bluhmki E,
    4. Lesaffre E
    : A new nonparametric approach for baseline covariate adjustment for two-group comparative studies. Biometrics 64: 1110–1116, 2008pmid:18266888
    OpenUrlCrossRefPubMed
  20. ↵
    1. Austin PC
    : Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 28: 3083–3107, 2009pmid:19757444
    OpenUrlCrossRefPubMed
  21. ↵
    1. Obi Y,
    2. Rhee CM,
    3. Mathew AT,
    4. Shah G,
    5. Streja E,
    6. Brunelli SM,
    7. Kovesdy CP,
    8. Mehrotra R,
    9. Kalantar-Zadeh K
    : Residual kidney function decline and mortality in incident hemodialysis patients. J Am Soc Nephrol 27: 3758–3768, 2016pmid:27169576
    OpenUrlAbstract/FREE Full Text
  22. ↵
    1. Hemodialysis Adequacy 2006 Work Group
    : Clinical practice guidelines for hemodialysis adequacy, update 2006. Am J Kidney Dis 48[Suppl 1]: S2–S90, 2006pmid:16813990
    OpenUrlCrossRefPubMed
  23. ↵
    1. Wang M,
    2. You L,
    3. Li H,
    4. Lin Y,
    5. Zhang Z,
    6. Hao C,
    7. Chen J
    : Association of circulating fibroblast growth factor-23 with renal phosphate excretion among hemodialysis patients with residual renal function. Clin J Am Soc Nephrol 8: 116–125, 2013pmid:23085728
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Yamada S,
    2. Tokumoto M,
    3. Tatsumoto N,
    4. Taniguchi M,
    5. Noguchi H,
    6. Nakano T,
    7. Masutani K,
    8. Ooboshi H,
    9. Tsuruya K,
    10. Kitazono T
    : Phosphate overload directly induces systemic inflammation and malnutrition as well as vascular calcification in uremia. Am J Physiol Renal Physiol 306: F1418–F1428, 2014pmid:24808541
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Obi Y,
    2. Qader H,
    3. Kovesdy CP,
    4. Kalantar-Zadeh K
    : Latest consensus and update on protein-energy wasting in chronic kidney disease. Curr Opin Clin Nutr Metab Care 18: 254–262, 2015pmid:25807354
    OpenUrlCrossRefPubMed
  26. ↵
    1. Isakova T,
    2. Gutiérrez OM,
    3. Chang Y,
    4. Shah A,
    5. Tamez H,
    6. Smith K,
    7. Thadhani R,
    8. Wolf M
    : Phosphorus binders and survival on hemodialysis. J Am Soc Nephrol 20: 388–396, 2009pmid:19092121
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Block GA,
    2. Klassen PS,
    3. Lazarus JM,
    4. Ofsthun N,
    5. Lowrie EG,
    6. Chertow GM
    : Mineral metabolism, mortality, and morbidity in maintenance hemodialysis. J Am Soc Nephrol 15: 2208–2218, 2004pmid:15284307
    OpenUrlAbstract/FREE Full Text
    1. Floege J,
    2. Kim J,
    3. Ireland E,
    4. Chazot C,
    5. Drueke T,
    6. de Francisco A,
    7. Kronenberg F,
    8. Marcelli D,
    9. Passlick-Deetjen J,
    10. Schernthaner G,
    11. Fouqueray B,
    12. Wheeler DC; ARO Investigators
    : Serum iPTH, calcium and phosphate, and the risk of mortality in a European haemodialysis population. Nephrol Dial Transplant 26: 1948–1955, 2011pmid:20466670
    OpenUrlCrossRefPubMed
    1. Obi Y,
    2. Mehrotra R,
    3. Rivara MB,
    4. Streja E,
    5. Rhee CM,
    6. Lau WL,
    7. Kovesdy CP,
    8. Kalantar-Zadeh K
    : Hidden hypercalcemia and mortality risk in incident hemodialysis patients. J Clin Endocrinol Metab 101: 2440–2449, 2016pmid:27045726
    OpenUrlPubMed
    1. Tentori F,
    2. Blayney MJ,
    3. Albert JM,
    4. Gillespie BW,
    5. Kerr PG,
    6. Bommer J,
    7. Young EW,
    8. Akizawa T,
    9. Akiba T,
    10. Pisoni RL,
    11. Robinson BM,
    12. Port FK
    : Mortality risk for dialysis patients with different levels of serum calcium, phosphorus, and PTH: The Dialysis Outcomes and Practice Patterns Study (DOPPS). Am J Kidney Dis 52: 519–530, 2008pmid:18514987
    OpenUrlCrossRefPubMed
  31. ↵
    1. Obi Y,
    2. Nguyen DV,
    3. Streja E,
    4. Rivara MB,
    5. Rhee CM,
    6. Lau WL,
    7. Chen Y,
    8. Kovesdy CP,
    9. Mehrotra R,
    10. Kalantar-Zadeh K
    : Development and validation of a novel laboratory-specific correction equation for total serum calcium and its association with mortality among hemodialysis patients. J Bone Miner Res 32: 549–559, 2017pmid:27714897
    OpenUrlPubMed
  32. ↵
    1. Rivara MB,
    2. Ravel V,
    3. Kalantar-Zadeh K,
    4. Streja E,
    5. Lau WL,
    6. Nissenson AR,
    7. Kestenbaum B,
    8. de Boer IH,
    9. Himmelfarb J,
    10. Mehrotra R
    : Uncorrected and albumin-corrected calcium, phosphorus, and mortality in patients undergoing maintenance dialysis. J Am Soc Nephrol 26: 1671–1681, 2015pmid:25613037
    OpenUrlAbstract/FREE Full Text
  33. ↵
    1. Hill KM,
    2. Martin BR,
    3. Wastney ME,
    4. McCabe GP,
    5. Moe SM,
    6. Weaver CM,
    7. Peacock M
    : Oral calcium carbonate affects calcium but not phosphorus balance in stage 3-4 chronic kidney disease. Kidney Int 83: 959–966, 2013pmid:23254903
    OpenUrlCrossRefPubMed
  34. ↵
    1. Spiegel DM,
    2. Brady K
    : Calcium balance in normal individuals and in patients with chronic kidney disease on low- and high-calcium diets. Kidney Int 81: 1116–1122, 2012pmid:22297674
    OpenUrlCrossRefPubMed
  35. ↵
    1. Iwasaki Y,
    2. Yamato H,
    3. Nii-Kono T,
    4. Fujieda A,
    5. Uchida M,
    6. Hosokawa A,
    7. Motojima M,
    8. Fukagawa M
    : Insufficiency of PTH action on bone in uremia. Kidney Int Suppl 102: S34–S36, 2006pmid:16810309
    OpenUrlPubMed
  36. ↵
    1. Quarles LD,
    2. Lobaugh B,
    3. Murphy G
    : Intact parathyroid hormone overestimates the presence and severity of parathyroid-mediated osseous abnormalities in uremia. J Clin Endocrinol Metab 75: 145–150, 1992pmid:1619003
    OpenUrlCrossRefPubMed
  37. ↵
    1. Ureña P,
    2. Kubrusly M,
    3. Mannstadt M,
    4. Hruby M,
    5. Trinh MM,
    6. Silve C,
    7. Lacour B,
    8. Abou-Samra AB,
    9. Segre GV,
    10. Drüeke T
    : The renal PTH/PTHrP receptor is down-regulated in rats with chronic renal failure. Kidney Int 45: 605–611, 1994pmid:8164450
    OpenUrlCrossRefPubMed
  38. ↵
    1. Nii-Kono T,
    2. Iwasaki Y,
    3. Uchida M,
    4. Fujieda A,
    5. Hosokawa A,
    6. Motojima M,
    7. Yamato H,
    8. Kurokawa K,
    9. Fukagawa M
    : Indoxyl sulfate induces skeletal resistance to parathyroid hormone in cultured osteoblastic cells. Kidney Int 71: 738–743, 2007pmid:17264878
    OpenUrlCrossRefPubMed
  39. ↵
    1. Slatopolsky E,
    2. Finch J,
    3. Clay P,
    4. Martin D,
    5. Sicard G,
    6. Singer G,
    7. Gao P,
    8. Cantor T,
    9. Dusso A
    : A novel mechanism for skeletal resistance in uremia. Kidney Int 58: 753–761, 2000pmid:10916099
    OpenUrlCrossRefPubMed
  40. ↵
    1. Shafi T,
    2. Michels WM,
    3. Levey AS,
    4. Inker LA,
    5. Dekker FW,
    6. Krediet RT,
    7. Hoekstra T,
    8. Schwartz GJ,
    9. Eckfeldt JH,
    10. Coresh J
    : Estimating residual kidney function in dialysis patients without urine collection. Kidney Int 89: 1099–1110, 2016pmid:26924062
    OpenUrlCrossRefPubMed
    1. Wong J,
    2. Sridharan S,
    3. Berdeprado J,
    4. Vilar E,
    5. Viljoen A,
    6. Wellsted D,
    7. Farrington K
    : Predicting residual kidney function in hemodialysis patients using serum β-trace protein and β2-microglobulin. Kidney Int 89: 1090–1098, 2016pmid:26924065
    OpenUrlCrossRefPubMed
  42. ↵
    1. Kato A,
    2. Odamaki M,
    3. Hishida A
    : Association between blood indoxyl sulfate and carbonyl stress marker in hemodialysis patients. Clin Nephrol 60: 161–167, 2003pmid:14524578
    OpenUrlCrossRefPubMed
  43. ↵
    1. London GM,
    2. Marchais SJ,
    3. Guérin AP,
    4. Boutouyrie P,
    5. Métivier F,
    6. de Vernejoul MC
    : Association of bone activity, calcium load, aortic stiffness, and calcifications in ESRD. J Am Soc Nephrol 19: 1827–1835, 2008pmid:18480316
    OpenUrlAbstract/FREE Full Text
  44. ↵
    1. Kurz P,
    2. Monier-Faugere MC,
    3. Bognar B,
    4. Werner E,
    5. Roth P,
    6. Vlachojannis J,
    7. Malluche HH
    : Evidence for abnormal calcium homeostasis in patients with adynamic bone disease. Kidney Int 46: 855–861, 1994pmid:7996807
    OpenUrlCrossRefPubMed
  45. ↵
    1. Lomashvili KA,
    2. Garg P,
    3. Narisawa S,
    4. Millan JL,
    5. O’Neill WC
    : Upregulation of alkaline phosphatase and pyrophosphate hydrolysis: Potential mechanism for uremic vascular calcification. Kidney Int 73: 1024–1030, 2008pmid:18288101
    OpenUrlCrossRefPubMed
  46. ↵
    1. Regidor DL,
    2. Kovesdy CP,
    3. Mehrotra R,
    4. Rambod M,
    5. Jing J,
    6. McAllister CJ,
    7. Van Wyck D,
    8. Kopple JD,
    9. Kalantar-Zadeh K
    : Serum alkaline phosphatase predicts mortality among maintenance hemodialysis patients. J Am Soc Nephrol 19: 2193–2203, 2008pmid:18667733
    OpenUrlAbstract/FREE Full Text
    1. Magnusson P,
    2. Sharp CA,
    3. Magnusson M,
    4. Risteli J,
    5. Davie MW,
    6. Larsson L
    : Effect of chronic renal failure on bone turnover and bone alkaline phosphatase isoforms. Kidney Int 60: 257–265, 2001pmid:11422759
    OpenUrlCrossRefPubMed
  48. ↵
    1. Shantouf R,
    2. Kovesdy CP,
    3. Kim Y,
    4. Ahmadi N,
    5. Luna A,
    6. Luna C,
    7. Rambod M,
    8. Nissenson AR,
    9. Budoff MJ,
    10. Kalantar-Zadeh K
    : Association of serum alkaline phosphatase with coronary artery calcification in maintenance hemodialysis patients. Clin J Am Soc Nephrol 4: 1106–1114, 2009pmid:19423565
    OpenUrlAbstract/FREE Full Text
  49. ↵
    1. Duranton F,
    2. Rodriguez-Ortiz ME,
    3. Duny Y,
    4. Rodriguez M,
    5. Daurès JP,
    6. Argilés A
    : Vitamin D treatment and mortality in chronic kidney disease: A systematic review and meta-analysis. Am J Nephrol 37: 239–248, 2013pmid:23467111
    OpenUrlCrossRefPubMed
    1. Pilz S,
    2. Iodice S,
    3. Zittermann A,
    4. Grant WB,
    5. Gandini S
    : Vitamin D status and mortality risk in CKD: A meta-analysis of prospective studies. Am J Kidney Dis 58: 374–382, 2011pmid:21636193
    OpenUrlCrossRefPubMed
    1. Streja E,
    2. Lau WL,
    3. Goldstein L,
    4. Sim JJ,
    5. Molnar MZ,
    6. Nissenson AR,
    7. Kovesdy CP,
    8. Kalantar-Zadeh K
    : Hyperphosphatemia is a combined function of high serum PTH and high dietary protein intake in dialysis patients. Kidney Int Suppl (2011) 3: 462–468, 2013
    OpenUrlCrossRef
    1. Kalantar-Zadeh K,
    2. Kopple JD,
    3. Block G,
    4. Humphreys MH
    : A malnutrition-inflammation score is correlated with morbidity and mortality in maintenance hemodialysis patients. Am J Kidney Dis 38: 1251–1263, 2001pmid:11728958
    OpenUrlCrossRefPubMed
    1. Leggat JE Jr.
    .: Adherence with dialysis: A focus on mortality risk. Semin Dial 18: 137–141, 2005pmid:15771658
    OpenUrlCrossRefPubMed
  54. ↵
    1. Gutiérrez OM,
    2. Mannstadt M,
    3. Isakova T,
    4. Rauh-Hain JA,
    5. Tamez H,
    6. Shah A,
    7. Smith K,
    8. Lee H,
    9. Thadhani R,
    10. Jüppner H,
    11. Wolf M
    : Fibroblast growth factor 23 and mortality among patients undergoing hemodialysis. N Engl J Med 359: 584–592, 2008pmid:18687639
    OpenUrlCrossRefPubMed
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Association of Parameters of Mineral Bone Disorder with Mortality in Patients on Hemodialysis according to Level of Residual Kidney Function
Mengjing Wang, Yoshitsugu Obi, Elani Streja, Connie M. Rhee, Wei Ling Lau, Jing Chen, Chuanming Hao, Takayuki Hamano, Csaba P. Kovesdy, Kamyar Kalantar-Zadeh
CJASN Jul 2017, 12 (7) 1118-1127; DOI: 10.2215/CJN.11931116
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