Effect of Aggressive Osteodystrophy Management on Clinical Outcomes in Stage 5 Chronic Kidney Disease

Article Outline

• Abstract
• Methods
  • Study Design and Subjects
  • Definition of Study Variables
    • Interventions
    • Bone Health Measures
    • Risk Factors
  • Statistical Analyses
• Results
• Discussion
• Conclusions
• References
• Copyright

Objective

The study investigated whether the type of bone disease management (aggressive versus conventional) had an impact on clinical outcomes, namely bone health measures (e.g., biointact parathyroid hormone [BiPTH], serum corrected calcium [cCa] level, serum phosphorus [phos] level, and corrected calcium-phosphorus product [cCaPO₄]).

Design and Setting

Retrospective chart review of 173 closed medical records of maintenance hemodialysis patients on thrice-weekly therapy from January 1, 2005, through December 31, 2005. Two Conventional Management (i.e., control group) and three Aggressive Management (i.e., treatment group) dialysis facilities were enrolled.

Results

There was a significant interaction for group assignment and BiPTH levels (F = 4.12, P = .01), with the Aggressive Group trending toward lower BiPTH levels than the Conventional Group. The Conventional Group experienced a significantly lower mean annualized serum cCa level (F = 8.85, P = .003), and used non–calcium-based binders significantly more (P < .0005) than the Aggressive Group. In terms of serum phos level, the Aggressive Group had a significantly lower (F = 2.73, P = .05) value than the Conventional Group. No significant differences were reported for cCaPO₄ product (F = 1.87, P = .17). The percentage of the total sample that achieved target range for all bone health measures included 29.8% (n = 50).

Conclusions

The study demonstrated that aggressive bone disease management appears to be as effective as traditional interventions in the treatment of mineral and bone metabolism disorders in chronic kidney disease.

EVIDENCE exists as to the injurious effects of the abnormalities in mineral and bone metabolism frequently seen in patients diagnosed with chronic kidney disease (CKD).¹, ² This CKD–mineral and bone disorder (CKD-MBD) manifests in biochemical changes, “abnormalities in bone turnover, mineralization, volume, linear growth, or strength,” as well as “vascular or other soft tissue calcification.” ³ A component of this disorder, renal osteodystrophy, has been defined as an altered bone morphology that is identifiable by bone biopsy.³ Compromises in bone remodeling are detectable when the glomerular filtration rate (GFR) drops below 60 ml/min/1.73 m², suggesting that those patients diagnosed with stage 5 CKD with a GFR less than 15 ml/min/1.73 m² may have developed severe osteodystrophy complications requiring immediate treatment and management.¹, ², ³, ⁴, ⁵, ⁶ Additionally, bone disease after kidney transplantation has been associated in part with disordered bone metabolism while on dialysis, implying that improvements made during stage 5 CKD may have a beneficial impact on posttransplant outcomes.⁷ Hyperplasia of the parathyroid gland often occurs in the CKD patient due to hypocalcemia and/or 1,25-vitamin D deficiency.¹, ² As kidney function continues to decline, vitamin D receptors (VDR) and calcium receptors (CaR) in the parathyroid gland decrease as well, leading to increased resistance to vitamin D and calcium.¹, ² Increasing hyperphosphatemia leads to the worsening of secondary hyperparathyroidism, while the rate of skeletal remodeling in turn affects phosphate homeostasis.¹, ² The components of CKD-MBD have been correlated with muscle and bone pain, osteoporosis/osteopenia, bone fractures, and pruritis as well as systemic effects including soft tissue and vascular calcification along with erythropoietin-resistant anemia.¹, ³, ⁸, ⁹, ¹⁰, ¹¹ Research has documented the effects of such metabolic derangements on morbidity and mortality, including cardiovascular mortality, within this patient population.¹, ³, ¹⁰, ¹², ¹³ Scientific efforts toward reversing these trends and outcomes have and continue to be supported.³, ¹⁴

Finding and maintaining the correct balance among the serum markers of bone disease such as serum corrected calcium (cCa), serum phosphorus (phos), corrected calcium-phosphorus product (cCa × PO₄), and parathyroid hormone (PTH) levels requires careful monitoring, particularly as these various bone health measures (BHMs) affect one another. The challenge arises in correcting the imbalance of one serum value while not disrupting the balance of another biomarker. Therapy choices, including phosphate binders, vitamin D analogs, and calcimimetics, have been used in combination for individualized patient care and the concomitant use of these therapies has been studied with the intent of monitoring therapeutic effects.¹⁵, ¹⁶, ¹⁷, ¹⁸ Care is warranted in the treatment of secondary hyperparathyroidism as oversuppression of the parathyroid gland can lead to adynamic bone disease and further disturb bone remodeling. The ultimate goal for effective osteodystrophy management is the stimulation of skeletal remodeling and the halting of extracellular calcification.², ³ In an attempt to minimize or reduce renal osteodystrophy with the purpose of improving quality of life and enhancing longevity, the NKF-KDOQI Clinical Practice Guidelines for Bone Metabolism and Disease in CKD (2003) strongly encourage the achievement of target values, supported by research evidence and clinical expertise/opinion, for cCa (8.4-9.5 mg/dl), phos (3.5-5.5 mg/dl), cCa × PO₄ (<55 mg²/dl²), and intact PTH (150-300 pg/ml).¹ An international, representative sample of 6,864 patients from the DOPPS II study, between the years of 2002 and 2004, reported that the majority did not reach KDOQI guideline ranges for either intact PTH, serum phos, or cCa, although better achievement of the established guideline for cCa × PO₄ was experienced. This observational study also found a significant positive association between all-cause and cardiovascular mortality and higher concentrations of these BHMs.¹⁹ Close monitoring of serum markers and responding to abnormalities in a timely fashion through treatment adjustment and nutritional therapy are required for achievement of such target ranges. To ensure that such careful and skillful examination of BHMs is occurring, many dialysis facilities have designated health professionals as osteodystrophy managers within the center. In fact, the NKF-KDOQI Clinical Practice Guidelines recommend that the registered dietitian (RD) specializing in renal disease be available to routinely monitor such biomarkers.¹ RDs are uniquely positioned and qualified for bone disease management and many are already fulfilling this role.²⁰, ²¹ However, no studies have examined whether allocating staff time such as RD hours to conduct aggressive bone disease management actually improves clinical outcomes.¹ Thus, the purpose of this study was to evaluate the effect of two types of bone disease management (Aggressive versus Conventional) on BHMs in patients diagnosed with stage 5 CKD on maintenance hemodialysis.

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Methods 

Study Design and Subjects 

Institutional review board approval was obtained from both the principal investigator's institution and at each of the respective dialysis facilities. This was a 12-month retrospective study of 173 stage 5 CKD patients on maintenance hemodialysis from five separate dialysis clinics within the states of New Jersey and Pennsylvania. All of the dialysis facilities selected for the study were self-nominated at a local Council on Renal Nutrition (CRN) meeting. Data were collected from closed medical records for the study period of January 1, 2005, to December 31, 2005, using two selection methods. For those facilities identified as the “control group” (n = 2), all eligible patient records were included in the study. Because the “treatment group” facilities (n = 3) were much larger, patient records were randomly selected until 40 charts from each of these dialysis units were eligible. Subject inclusion criteria consisted of those greater than 18 years of age, on hemodialysis for at least 3 months at the beginning of the data collection period, and receiving in-center hemodialysis treatments three times weekly. Exclusion criteria included a change in treatment modality during the study period, parathyroidectomy, enrollment in another bone management research study protocol, involvement in a home hemodialysis program, or greater than seven consecutive treatment days absent from the dialysis clinic (e.g., including vacations and hospitalizations). For comparisons between the treatment and control groups, data concerning the dialysis facilities and the RD practice patterns were collected from each of the study dietitians and reported descriptively.

This study explored the relationship between the dependent variables, BHMs, and the independent variable, the treatment intervention used either aggressive or conventional management of bone disease, which is fully described later under the next section. In addition, there are a number of risk factors identified in the research literature that may potentially affect the interpretation of the causal relationship between the dependent and independent variables. These included patient demographics, the severity of illness, and treatment characteristics. The effect of these potential covariates on the clinical outcomes (dependent variable) as well as their effect on the relationship between the type of intervention (aggressive versus conventional management) and the BHMs was explored statistically.

Definition of Study Variables 

Interventions 

Aggressive bone management describes the intensiveness of the treatment administered. It was operationalized as that intervention whereby BHMs were monitored by a designated osteodystrophy manager in the dialysis unit implementing therapy protocols with the intent of achieving target ranges for the BHMs. The anticipated cycle (i.e., recorded time from when the lab values were received to when modifications in therapy were implemented) was, on average, 48 hours. Conversely, conventional management, as provided by the control group, was defined as the routine monitoring of BHMs by traditional means—i.e., nephrologists and/or nursing monitoring lab values and making changes in therapy in response to abnormalities or values out of target range. The anticipated cycle (i.e., recorded time from when the lab values were received to when modifications in therapy were implemented) was approximately 2 weeks.

Bone Health Measures 

BHMs were routinely collected for osteodystrophy management within each dialysis facility on a monthly (e.g., serum cCa and phos levels, and cCa × PO₄) or quarterly (e.g., BiPTH) basis. The 2003 NKF-KDOQI Clinical Practice Guidelines for Bone Metabolism and Disease in CKD only account for intact parathyroid hormone (iPTH) levels (150-300 pg/ml).¹ Research literature has suggested that iPTH assay may overestimate the true concentration of PTH in biologic samples, leading to an inadvertent oversuppression of the parathyroid gland.²² As the biointact PTH (BiPTH) assay was the current standard measurement of PTH levels at the time of data collection, and recognizing the consequences of over suppression, clinicians used BiPTH for this study. Nonetheless, BiPTH has not been proved to have better diagnostic ability in clinical practice than the “older” iPTH assays.²³ It was generally accepted within the nephrology community that the BiPTH level represents approximately 60% of the iPTH value; as such, clinicians have established the target level for BiPTH as 75 to 150 pg/ml (Pathology Associates Medical Laboratories, product literature, 2003). As stated, there was no research evidence to support this target range and there was concern over whether such tight control may lead to oversuppression of the parathyroid gland. In fact, Block and colleagues²⁴ have suggested that the relative risk for death is significantly increased only when the iPTH is greater than or equal to 600 pg/ml (i.e., BiPTH ≥ 300 pg/ml). It was agreed among the co-investigators that the optimal level for BiPTH levels, for the purposes of this study, would range from 75 to 250 pg/ml.

The serum calcium level was measured monthly within each dialysis clinic. If the serum calcium level was drawn more than once a month, the value reported as part of the monthly chemistries was the value used for the study. As per the KDOQI Practice Guidelines for Bone Metabolism and Disease in Chronic Kidney Disease, optimal serum calcium level will range from 8.4 to 9.5 mg/dl.¹ If the patient experienced hypoalbuminemia (<4.0 g/dl), the following formula was used to correct the serum calcium value, according to the recommended KDOQI equation, and thus, such values were reported as applicable¹:

The serum phos level was measured monthly within each dialysis clinic. If the serum phos level was drawn more than once, the value reported as part of the monthly chemistries was the value collected. As per the KDOQI Practice Guidelines for Bone Metabolism and Disease in Chronic Kidney Disease, optimal serum phos level will range from 3.5 to 5.5 mg/dl.¹ The serum cCa × PO₄ was calculated by multiplying the serum cCa level by the serum phos level.¹ To reduce risk for complications, it is recommended that the cCa × PO₄ should be maintained at less than 55 mg²/dl². The cCa × PO₄ included the corrected calcium level (cCalcium).

Risk Factors 

Additional study variables that were collected to assist in interpreting the effect of the interventions on outcomes included patient demographics, severity of illness, and treatment characteristics. The patient demographics comprised sex, race/ethnicity, type of dialysis facility, and dialysis vintage. Severity of illness was recorded as it relates to patient acuity—e.g., number of hospitalizations, surgeries/procedures performed, and number of co-morbidities. Treatment characteristics included dialysate baths used, medications prescribed, number of missed HD treatments, and duration of prescribed HD treatment sessions.

Statistical Analyses 

The statistical program used for all data analysis was the Statistical Program for the Social Sciences (SPSS) version 16.0. Statistical analyses used included parametric and nonparametric analyses such as frequency distributions, correlation coefficients between the dependent variable (BHMs) and the independent variable (type of treatment used: aggressive versus conventional), as well as a repeated measures analysis of variance (ANOVA) to locate differences between the two groups over the course of the study period. The a priori alpha level was set at P ≤ .05. At the time of the study, there were no similar studies to establish a power estimation based on sample means of BHMs. Thus, the power analysis was initially conducted using the Pearson's correlation coefficient, and it was estimated that to detect a significant linear relationship between the independent variables (BHMs) and dependent variables (group assignment) at 80% power for a magnitude of 0.30 for a two-tailed correlational test with an alpha priori level of P = .05, 183 patient records were required.

For purposes of statistical analyses, 12-month data were categorized into four time periods; First Quarter (months inclusive of January-March), Second Quarter (months inclusive of April-June), Third Quarter (months inclusive of July-September), and Fourth Quarter (months inclusive of October-December). The annualized mean values were calculated by determining the average value of each BHM over the course of the 12-month study period.

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Results 

Of the five dialysis facilities included in this study, two represented the Conventional Management group (known hereafter as the “Conventional Group”) and three units belonged to the Aggressive Management group (known hereafter as the “Aggressive Group”) (Table 1). Although this investigation was limited to studying maintenance hemodialysis patients treated in-center, both groups also managed peritoneal dialysis patients. The Aggressive Group reported additional responsibilities for home hemodialysis and transplant programs. Even though the census of the dialysis patients was much larger for the Aggressive Group, the staffing mix consisted of a lower number of nephrologists and students (e.g., nephrology fellows, dietetic interns, nursing students, etc.), but more allied health professionals than the Conventional Group. The mean patient-to-dietitian staffing ratio was higher for the Aggressive Group, with approximately 19 more maintenance dialysis patients covered by the RD on a monthly basis (Table 1).

Table 1. Comparisons of the Five Dialysis Facilities by Aggressive or Conventional Management Assignment (N = 5)

N/A, not applicable.

∗Subpercentages under this category may not equal 100% due to rounding and other activities not reported.

Practice patterns for the RDs were comparable between the two groups for direct patient care activities (62.5% versus 68.7%) which contributed to the largest percentage of their time (Table 1). The Aggressive Group, however, spent more time reviewing monthly chemistries, implementing treatment changes, and monitoring patients, whereas the Conventional Group reported more time conducting nutrition assessments and providing education. According to indirect patient care activities tracked, the Aggressive Group recorded a greater proportion of time spent in administrative activities, namely charting and interdisciplinary meetings (e.g., continuous quality improvement (CQI) and care planning).

In regard to demographics, the patients' mean age and facility location were the only significant differences between the two groups (Table 2). The Aggressive Group was approximately 6 years older (P = .02), and the dialysis units were more likely to be located in an urban/suburban setting (P < .0005). Race and ethnicity was not significantly different between the two groups (P = .12), with the largest percentage being African American. There were, however, a greater proportion of males in the Conventional Group (P = .06). Both groups contained dialysis units that were either hospital-based or free-standing, for-profit facilities (P = .75).

Table 2. Comparisons Between Groups According to Patient Demographics, Co-Morbidities, and Treatment Characteristics (N = 173)

Significance was set at an alpha level <.05.

∗Equal variances not assumed independent-samples t-test.

†Chi-square of independence test.

‡Recoded for analyses using chi-square independent test as white and other.

§Independent-samples t-test.

¶Recoded for analyses using Fisher's exact test as rural and nonrural.

∗∗Fisher's exact test since greater than 20% cells had counts less than 5.

The patients' severity of illness indicators were not significantly different between the two groups for either the number of reported comorbidities (P = .30) or frequency of hospitalizations and/or surgical procedures (P = .11) (Table 2). Of the treatment characteristics monitored, the mean number of missed treatments, the duration of the HD treatment session, and the use of non–calcium-based binders and vitamin D analogs were significantly different between the two groups. The Aggressive Group missed on average 1.5 more HD treatment sessions per patient per year (P = .001), and the mean duration of the HD treatment session was approximately 15 minutes longer (P < .0005) than the Conventional Group. The Aggressive Group was also significantly less likely to prescribe lanthanum carbonate (P < .0005) and was more likely to use a vitamin D analog (e.g., paricalcitol) (P = .04). Although not statistically significant, the Conventional Group was more likely to prescribe calcimimetics, whereas the Aggressive Group used nontraditional binders containing magnesium- and aluminum-based agents sparingly. The prescribing practices for calcium-containing dialysate baths were comparable to each other (P = .08).

As presented in Table 2, there were a number of variables that were significantly different between the Aggressive and Conventional Groups, according to patient demographics, severity of illness, and treatment characteristics (e.g., age, facility location, number of missed treatments, medication usage, and duration of HD treatment sessions). Thus, a correlation matrix was completed to determine whether a linear relationship existed between any of these variables and the mean annualized value for each of the BHMs (Table 3). Three variables were excluded as potential covariates from the analysis. Facility location, even though significantly different according to region between the two groups, this variable was collinear with group assignment (Aggressive versus Conventional Groups). For example, all of the dialysis facilities in the Aggressive Group were in the urban/suburban region and all of the dialysis facilities in the Conventional Group were in rural locations. Hence, the addition of this variable did not further explain the variance between the dependent and independent variables. Differences according to medications prescribed (e.g., lanthanum carbonate and paricalcitol) were also not included as covariates as these nuances reflected the prescribing practices in the bone disease management protocols specific to the Conventional and Aggressive Groups and, thus, was collinear with group assignment.

Table 3. Correlation Matrix Between Potential Covariates and the Dependent Variable, Bone Health Measures

BiPTH, biointact parathyroid hormone.

Significance level was set at alpha <.05.

∗cCalcium, corrected calcium levels recorded as applicable, according to KDOQI Bone Disease Management Clinical Practice Guidelines.1

†cCaXPO4, corrected calcium levels recorded as applicable, according to KDOQI Bone Disease Management Clinical Practice Guidelines.1

As indicated in Table 3, age was significantly correlated with all four of the BHMs, and missed treatments was only significantly associated with cCa × PO₄ and serum phos. The duration of HD treatment sessions was not significantly correlated with any of the BHMs. To determine the impact of these potential covariates on the interpretation of the outcome measure, a univariate analysis of covariance (ANCOVA) with repeated measures was conducted. While significant correlations existed between the dependent variable and these co-factors, all other effects were not significant. Therefore, the original main effects are reported using a univariate repeated measures ANOVA.

Despite outliers being identified in the dataset for the BHMs, such extreme cases were not removed nor were the data transformed since the values were thought to be an accurate description of the typical practice setting in maintenance hemodialysis. Repeated measures ANOVA assessed the impact of the type of bone disease management (Aggressive versus Conventional) on BiPTH across four time periods (Quarters 1-4). There was a significant interaction effect between group assignment (Aggressive versus Conventional) over the study time period (F = 4.12, P = .01) (Fig. 1). In reviewing the post hoc within subject contrasts for Quarter 1 to Quarter 2, the Aggressive Group significantly decreased BiPTH levels by 20.3 pg/ml and the BiPTH rose by 48.1 pg/ml in the Conventional Group (F = 6.52, P = .01). Any changes detected from Quarters 2-4 were not significantly different between the two groups. There were also no significant main effects within subjects for BiPTH values over the course of the four quarters (F = 0.44, P = .63), nor were there any significant mean differences in BiPTH levels between groups at the end of the study period (F = 0.22, P = .64).

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• Figure 1 

  Interaction Effect of Type of Bone Disease Management (Aggressive versus Conventional) on BiPTH Levels.

There was a significant mean difference between groups for cCa at study completion (F = 8.85, P = .003) (Table 4). The Conventional Group experienced an annualized mean for serum cCa level that was 0.25 ± 0.08 mg/dl lower than the Aggressive Group. There was no significant (F = 1.54, P = .20) interaction effect for group assignment over the study period concerning cCa level. There were also no significant (F = 1.12, P = .31) mean changes within subjects over the course of the study period for cCa level. Similarly, the corrected calcium-phosphorus product (cCa × PO₄) resulted in no significant interaction effect (F = 1.87, P = .17) for group assignment over the course of the study. There were no significant mean differences within subjects for cCa × PO₄ (F = 2.32, P = 0.08). Likewise, there were no significant mean differences between the two groups for cCa × PO₄ at study completion (F = 0.14, P = .71).

Table 4. Comparison of Mean Bone Health Measures for Quarters 1, 2, 3, and 4 Over 12 Month Period (January 2005-December 2005)

BiPTH, biointact parathyroid hormone.

QTR1 = Jan-Mar

QTR2 = Apr-Jun

QTR3 = Jul-Sep

QTR4 = Oct-Dec

∗Corrected calcium values (cCa) reported as applicable, according to KDOQI Bone Disease Management Clinical Practice Guidelines.1

†Corrected calcium-phosphorus product (cCaXPO4) reported as applicable, according to KDOQI Bone Disease Management Clinical Practice Guidelines.1

There was a significant within subjects effect over time for serum phos level (F = 2.73, P = 0.05). In studying the post hoc within subjects contrasts, the Aggressive Group was significantly lower in serum phos level than the Conventional Group between Quarters 2 and 3 with a mean difference of 0.24 ± 0.06 mg/dl, and from Quarters 3 to 4 with a recorded mean difference of 0.43 ± 0.06 mg/dl, respectively. There was no significant interaction effect (F = 1.33, P = .26) for group assignment over the course of the study, and there were no significant differences between groups at the end of the study (F = 1.53, P = .22).

When inspecting the mean value for each of the BHMs at the respective Quarter (Table 4), the Aggressive Group achieved the treatment goals outlined for all of the outcome measures, except for serum phos level at Quarter 2. The Conventional Group met goals for all BHMs, excluding serum phos levels at Quarters 2 and 4. Therefore, the percentage of the total sample (N = 173) of hemodialysis patients achieving the target goals for the 12-month study period is reported in Table 5. The highest reported frequency (n = 115, 66.8%) was for cCa × PO₄, and the lowest rate of compliance was for serum phos level (n = 97, 56%). When inspected by group assignment, the Conventional Group had a larger proportion of patients achieving goal for cCa, whereas the Aggressive Group experienced greater compliance for BiPTH. Otherwise, the two groups were fairly comparable for the remaining BHMs. When each of the BHMs were evaluated in comparison to each other (Table 6), approximately 30% (n = 50) of the sample achieved target range for all four BHMs, whereas 5% (n = 9) did not meet any of the treatment goals for these clinical outcomes. Both groups were similar to each other for the number of targets achieved.

Table 5. Percentage of Maintenance Hemodialysis Patients Achieving Goal for Annualized Bone Health Measures (N = 173)

BiPTH, biointact parathyroid hormone; cCa, corrected calcium levels; cCaXPO₄, corrected calcium phosphorus product.

∗As defined by study team.

†As stated by KDOQI Bone Disease Management Clinical Practice Guidelines.1

‡Based on missing data, the total sample for BiPTH was n = 171 and n = 172 for cCa and cCaXPO4.

§Based on a total number of 116.

¶Based on a total number of 117.

Table 6. Frequency Distribution of Total Sample Achieving Target Ranges for Annualized Bone Health Measures (N = 168)

Bone health measures = BiPTH, cCa, cCaPO₄ product, Phos.

BiPTH, biointact parathyroid hormone; cCa, corrected calcium levels; cCaXPO₄, corrected calcium phosphorus product.

∗Five participants had at least one missing value.

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Discussion 

This study demonstrated that aggressive bone disease management is as effective as traditional interventions in the treatment of bone and mineral metabolism disorders in chronic kidney disease (CKD-MBD). Thus, the addition of the osteodystrophy manager role, often assumed by the registered dietitian, in the dialysis facility does aid in attempt of achieving target ranges necessary to improve patient outcomes.

The long-term complications of bone disease in CKD are well documented and, in recent years, have received considerable attention in the scientific literature.¹, ³ The treatment approaches have progressed dramatically over the past two decades as more research evidence has become available concerning the pathophysiology and metabolic aberrations that exist concerning calcium and vitamin D in CKD.¹ With significant knowledge gained, the advent of novel pharmacological agents (e.g., calcimimetics, vitamin D analogues, and phosphate binders) has assisted practitioners in the pursuit of better management in CKD-MBD.²⁵ Despite such advances, the ability to achieve target ranges remains elusive, largely because of the side effects induced by the medications used to treat the condition.²⁶ Vitamin D sterols, often prescribed for their parathyroid hormone (PTH) suppression capabilities, also enhance the absorption of calcium and phosphorus, thereby potentiating secondary hypercalcemia and hyperphosphatemia.²⁶, ²⁷, ²⁸, ²⁹ Additionally, calcium-based binders used in the treatment of hyperphosphatemia tend to further increase serum calcium levels.³⁰ Conversely, being too aggressive in the treatment of hyperparathyroidism may lead to oversuppression, thereby creating the condition known as adynamic bone disease, reflective by a suboptimal PTH level and an elevated serum calcium level, indicative of low bone turnover.¹

There may be some benefit in evaluating BHMs in terms of how they relate to each other as well as exploring the prognostic nature of these variables on morbidity and mortality. Perhaps BHM goals should be met in combination with each other rather than looking at each lab parameter separately. For example, Tentori and colleagues³¹ reported from the Dialysis Outcome and Practice Patterns Study (DOPPS) that the magnitude of mortality risk from high calcium and phosphorus levels differed based on the PTH level. Accordingly, from a secondary analysis of the DOPPS II data from 2002-2004, less than 6% of dialysis patients are able to keep all four measures within target range.¹⁹ The current investigation, concerning data collected for 2005, reported a higher proportion of clients (30%) achieving target goals for all BHMs.

However, it is difficult to assess from the studies thus reported if measuring PTH levels in combination with other indicators or that individual biomarkers alone are more predictive of underlying bone histology. The relative importance of lab outcomes is considered low since the true relationship to clinical endpoints has not been established.³² Ideally, bone histology and cardiovascular risk assessment would have been useful indicators in the current investigation, but serum values were obtained from closed medical records and such data were not accessible during chart abstraction. Nonetheless, this investigation used BHMs, accepted in the literature as surrogate markers for the presence of CKD-MBD.

Both the Aggressive and Conventional Groups were similarly effective in the management of BiPTH levels. Although statistical differences were identified between the two groups, both achieved mean values that were within target ranges. Regardless, there were large variances in the BiPTH levels possibly indicative of practice variation and extreme cases of secondary hyperparathyroidism. It should be noted that the BiPTH assay used in the current investigation was the standard of practice in 2005 within the five dialysis facilities participating in this study and that the Nichols Advantage Biointact PTH assay was gradually removed from the market that year (personal communication, May 30, 2008, Dr. Joseph Palameh, Quest Diagnostics, Cambridge, MA). None of the newer assays have been validated by bone biopsy.³³ As such, it is difficult to compare the results of this study to others, as the target goals published were solely based on accepted clinical practice and not solid evidence, in order to prevent oversuppression of PTH and consequent bone anomalies. Interestingly, the second-generation Allegro assay by Nichols on which KDOQI was based is also not currently available. In fact, Barreto and associates³⁴ have reported that meeting the KDOQI published targets for iPTH can cause oversuppression and therefore low bone turnover, as validated by bone biopsy.

Of the BHMs studied, cCa × PO₄ achieved the highest proportion of patients achieving target range and serum phos level recorded the lowest percentage. Annualized mean cCa level was slightly different between both groups, and may be partly explained by the binder and/or vitamin D analogue usage by the respective groups, rather than specific differences in calcium-containing dialysate baths. There were routine adjustments in the dialysate baths from month-to-month as the serum calcium levels were monitored. The ranges in calcium-containing baths ranged from as high as 2.0 mEq/L to 3.5 mEq/L. The Aggressive Group prescribed calcium-based binders and used paricalcitol with greater frequency than the Conventional Group. The reason for the greater control in cCa levels among the Conventional Group relates to perhaps the lowered incidence of calcium-based binders. However, the serum phos was not necessarily better controlled in the Conventional Group. Mean annualized serum phos levels were closer to target range as recorded by the Aggressive Group, which used other nontraditional binders for short-term periods in those dialysis patients refractory to the more common binders prescribed.¹ Even though the Aggressive Group had a longer mean duration of dialysis session for their patients and did record the most missed treatments per patient, these reasons were not plausible explanations for the accounted differences. There have been a few studies that have examined whether the type of binder makes an impact on the long-term complications, namely cardiovascular calcifications.³⁵, ³⁶, ³⁷, ³⁸ While some of these studies have reported a decreasing trend in risk for coronary complications, there is debate whether this finding actually leads to a lower morbidity and mortality rate among dialysis patients. A recent review recorded potential benefits to using a non–calcium-based binder such as sevelamer, but additional research is warranted.³⁹ The use of calcimimetics was minimal at the time that the data were collected, and since this time the effectiveness of combined therapy for cinacalcet and low-dose vitamin D sterols in the achievement of KDOQI targets for BHMs have been reported.²⁶

There are a number of limitations for this current study. Since the study was conducted retrospectively, there may be a number of confounding variables not measured or accounted for in the statistical models. For instance, other factors that determine what type of medications used could be related to reimbursement issues, availability, and, of course, patient preference and adherence, none of which were followed in this study. In addition, monitoring the impact of dialysis membranes, type of accesses, and therapeutic dose was not measured in this study except in a very crude manner, making further statistical analyses difficult. As previously mentioned, all the dialysis facilities enrolled for data collection were self-nominated, and the protocols were not standardized or compared with each other. The inclusion of the dialysis facilities into either the treatment or control arm was determined only by whether 1) there was an osteodystrophy manager role assigned in the unit and 2) the anticipated treatment cycle (e.g., 48 hours versus 2 weeks). Although the study was able to detect statistically significant differences between the two groups on some of the BHMs, such small changes were reported for cCa × PO₄ product as well as some of the other serum values, that a post hoc power estimation based on mean differences between the groups at the four time points revealed that the study was not sufficiently powered to truly document the effect of such interventions on all clinical outcomes. Based on the findings of this study, at 80% power, a sample size of at least 220 subjects in the Aggressive Group and 110 subjects in the Conventional Group would be required. This study also used observational data collected from over 3 years ago and practice patterns and the availability of various medications and treatment approaches have changed dramatically. It would be valuable to repeat this intervention prospectively with a larger sample to ascertain whether there are differences in patient outcome based on the type of bone disease management.

Despite these limitations, this was the first investigation that explored whether the type of bone disease management improves clinical outcomes in dialysis patients. Further, it documents that designating an osteodystrophy manager in the dialysis facility is an effective means for improving patient outcomes related to CKD-MBD.

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Conclusions 

Findings of this study support the focused attention given to osteodystrophy management in the dialysis facilities in the adherence of KDOQI target ranges for BHMs. The inclusion of the osteodystrophy manager role as an integral member of the health care team in the treatment of CKD-MBD has been supported. More research needs to be conducted to identify whether newer pharmacologic agents along with aggressive osteodystrophy management will positively impact patient care and outcomes.

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References 

1. National Kidney Foundation . KDOQI Clinical Practice Guidelines for Bone Metabolism and Disease in Chronic Kidney Disease. Am J Kidney Dis. 2003;42:S1–S202
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2. Hruska K, Saab G, Matthew S, et al. Renal osteodystrophy, phospate homeostasis, and vascular calcification. Semin Dial. 2007;20:309–315
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