Journal of Pain and Symptom Management
Volume 39, Issue 3 , Pages 477-485, March 2010

Impact of Pain and Symptom Burden on the Health-Related Quality of Life of Hemodialysis Patients

  • Sara N. Davison, MD, MHSc (Bioethics), FRCP(C)

      Affiliations

    • Division of Nephrology & Immunology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
    • Corresponding Author InformationAddress correspondence to: Sara N. Davison, MD, 11-107 Clinical Sciences Building, Edmonton, Alberta, Canada T6G 2G3.
    • ,
  • Gian S. Jhangri, MSc

      Affiliations

    • Department of Public Health Sciences, University of Alberta, Edmonton, Alberta, Canada

Accepted 12 August 2009.

Article Outline

Abstract 

Context

Dialysis patients experience tremendous symptom burden and substantial impaired health-related quality of life (HRQL).

Objectives

We determined the association between symptom burden and HRQL in 591 hemodialysis patients.

Methods

Patients completed the modified Edmonton Symptom Assessment System and the Kidney Dialysis Quality of Life Short Form at baseline and after six months.

Results

There were no demographic, serological, or dialysis-related predictors for either HRQL or symptom burden. Pain, tiredness, lack of well-being, and depression were the only independent predictors of mental HRQL, accounting for 42.5% of the variation in the baseline mental health composite (MHC). Pain, fatigue, lack of well-being, and shortness of breath were the only independent predictors of physical HRQL, accounting for 38.5% of the variation in the baseline physical health composite (PHC). After follow-up, only changes in depression, anxiety, tiredness, and lack of appetite were independently associated with a change in MHC score, accounting for 48.7% of the variability. Only changes in pain, tiredness, and lack of appetite were independently associated with a change in PHC, accounting for 44.6% of the variability in the final multivariate regression model. No change in biochemical parameters predicted a change in either the MHC or the PHC.

Conclusion

Symptom burden in end-stage renal disease was substantial and had a tremendous negative impact on all aspects of hemodialysis patients' HRQL. These patients, therefore, would likely benefit from the institution of programs to reduce symptom burden.

Key Words: Pain, symptom burden, quality of life, end-stage renal disease, dialysis

 

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Introduction 

There is an increasing awareness in the literature that patients with end-stage renal disease (ESRD) experience substantial impaired health-related quality of life (HRQL)1 and tremendous symptom burden.2, 3, 4, 5, 6, 7 In fact, the number and severity of physical and mental symptoms are similar to those of many cancer patients hospitalized in palliative care settings.4, 8, 9 Approximately 50% of ESRD patients experience chronic pain, with 82% reporting this pain as moderate to severe in intensity. Depression is also common. Although no large-scale, well-designed, epidemiological studies of depression in ESRD have been conducted, prevalence rates between 5% and 50% have been reported.7, 10, 11, 12 Other common symptoms include insomnia, nausea, anorexia, pruritus, and shortness of breath. However, unlike many cancer patients, these symptoms are often present for several years. The medical community is largely unaware of the severity of symptom burden in ESRD patients,13 resulting in inadequate treatment and poor access to supportive care services.

Treatments aimed at minimizing morbidity and mortality in ESRD (such as more intensive dialysis) are often ineffective;14, 15 therefore, focusing on HRQL is an important therapeutic objective.14, 16, 17, 18 The clinical relevance of HRQL is not only because it is a basic aspect of health but also because a close relationship exists between HRQL, morbidity, and mortality.16, 17, 18 In the oncology and human immunodeficiency virus literature, there is a clear inverse relationship between symptoms and HRQL, leading investigators to focus on decreasing symptom burden as a way to improve patient well-being.19, 20 Despite the high symptom burden in ESRD, similar work in dialysis patients is limited and the role of symptom burden in ESRD patients' perception of their HRQL appears to be greatly underappreciated.13 Recent research suggests that chronic kidney disease (CKD) patients' perceptions of symptom burden may be more important than objective clinical assessments in determining HRQL.1, 8, 10, 21, 22, 23, 24, 25 Unfortunately, studies to date have been limited by small sample sizes, lack of comorbidity and biochemical data, and cross-sectional descriptions without longitudinal follow-up. A comprehensive assessment of the relationship between symptom burden and HRQL is an important step in highlighting the need for the routine implementation of symptom assessment and management in dialysis units.

The aims of this study were to determine the association between symptom burden and HRQL in dialysis patients and to examine clinical correlates of symptom burden and HRQL. Our hypothesis was that symptom burden in dialysis patients would adversely affect all aspects of HRQL.

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Patients and Methods 

Patient Population and Data Collection 

Study participants were dialysis patients in the Northern Alberta Renal Program, a Canadian, university-based renal program, and included peritoneal dialysis patients and in-center and satellite hemodialysis patients from 10 hemodialysis units. Participants were consecutively approached. Patients were excluded if they were younger than 18 years, refused, or were unable to complete questionnaires because of cognitive impairment, acute illness, general frailty, or a language barrier. All study participants completed a baseline assessment, which was replicated six months later, as outlined below. Hemodialysis patients completed surveys while on dialysis during a mid-week treatment, and peritoneal dialysis patients completed the surveys while attending their regular clinic appointment. The hemodialysis or clinic nurse assisted patients in completing the forms when required. The Health Research Ethics Board of the University of Alberta approved all study procedures.

Measurement Tools 

Symptom burden was assessed using the modified Edmonton Symptom Assessment System (mESAS). This is a simple and widely used instrument for measuring physical and psychological symptom distress and has been validated in CKD.4, 5 The mESAS consists of 10 visual analog scales, with 0–10 measurements for pain, activity, nausea, depression, anxiety, drowsiness, appetite, well-being, pruritus, and shortness of breath. The scale for each symptom is anchored by the words “No” and “Severe” at 0 and 10, respectively. Overall symptom distress score is defined as the sum of the scores for all 10 symptoms and ranges from 0 to 100.

HRQL was assessed with the Kidney Dialysis Quality of Life Short Form (KDQOL-SF™), Version 1.3.26 This self-report measure of HRQL incorporates kidney disease-targeted items and the 12-item Medical Outcome Study Short Form (SF-12) as the generic core, which allows for the calculation of two summary scores: the mental health composite (MHC) and the physical health composite (PHC). The SF-12 was scored using the recommended methods for the RAND-12.27 The RAND method of scoring offers several theoretical advantages over the standard SF scoring, which is based on principle component factor analysis with orthogonal factor rotations.28 The RAND scoring approach better discriminates between known groups and appears more responsive to change.29, 30, 31, 32

Age, sex, race, cause of ESRD, comorbidity, duration of therapy for ESRD, Kt/V (a measure of dialysis adequacy), dialysis modality, hemoglobin, calcium, phosphorus, parathyroid hormone, and serum albumin concentrations were collected. We determined the modified Charlson comorbidity index (CCI) as a measure of comorbid conditions,33 as this index has been shown to adjust for the potential confounding effect of comorbidity in studies of HRQL.

Statistical Analysis 

SPSS 15.0 for Windows was used to perform statistical analysis. A P<0.05 was considered statistically significant. Patient characteristics were described as frequencies and percentages or as a mean (standard deviation [SD]). Similar descriptive statistics were obtained for each of the 10 symptoms on the mESAS, as well as the total symptom distress score and the number of moderate or severe symptoms. Moderate was defined as 4–6 and severe as 7–10 on the 0–10 mESAS scale. Descriptive statistics were also obtained for the RAND-12 summary scores (PHC and MHC), as well as the KDQOL-SF summary scores: symptom/problem list, effects of kidney disease, and burden of kidney disease, and the biochemical markers: Kt/V, serum albumin, hemoglobin, calcium, and phosphorous. This was done for both baseline and the six-month follow-up assessments.

Regression analysis was conducted to find the variables associated with either baseline values of HRQL (MHC and PHC) or change in HRQL at the six-month follow-up. Four regression models were developed with primary outcome as follows: 1) baseline MHC, 2) baseline PHC, 3) change in MHC, and 4) change in PHC. In univariate and multivariate regression analyses, the predictors included baseline mESAS and baseline biochemical markers for baseline HRQL outcomes, and change in mESAS and change in biochemical markers at the six-month follow-up for change in HRQL outcomes. The change scores were computed as six-month follow-up scores minus baseline scores. The percentage of missing follow-up data was less than 3% for HRQL assessments and was less than 2% for the mESAS; these subjects were excluded from the final model. We adjusted all four models for covariates that might influence the baseline or follow-up HRQL, including age, sex, race, diabetic status, modality of dialysis, years on dialysis, and CCI. Independent variables significant at P<0.2 in univariate analyses were selected and fit into multivariate models. Variables found to be statistically significant in the multivariate models (P<0.05) were kept in the final parsimonious model. To ensure that there was sufficient variability in the ESAS and biochemical parameters over the six-month follow-up period to detect correlations with the HRQL scores, the coefficient of variation (CV) was calculated.

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Results 

Of the 654 eligible patients who were approached, 591 (90%) completed the questionnaires. Patients were on average 61.3 years of age, were mostly white (72.6%), had been on dialysis for a mean of 3.3 years, and had substantial comorbidity, with a mean (SD) CCI of 7.7 (2.9). Baseline HRQL was markedly impaired (Table 1). Patients reported a mean (SD) of 7.4 (2.5) symptoms and a mean (SD) of 4.5 (2.9) moderate or severe symptoms. Table 2 summarizes the prevalence for each of the mESAS symptoms. Each symptom was experienced by 54.3%–92.2% of patients, with the most frequently reported symptoms being tiredness (92.2%), decreased well-being (90.9%), and anorexia (82.1%). These were also the most common severe symptoms, followed closely by pain. Pain was experienced by 72.4% of patients and was moderate or severe in intensity in 46.5% of all study patients.

Table 1. Patient Characteristics
CharacteristicsMean (SD) or %
Age (years)61.3 (16.3)
Male55.0
Race
White72.6
Aboriginal11.3
Others16.1
Cause of ESRD
Diabetes mellitus27.6
Glomerulonephritis5.2
Hypertension10.2
Polycystic kidney disease3.4
Renovascular3.4
Other11.0
Unknown6.4
Missing22.8
Diabetic47.2
CCI7.7 (2.9)
Years on dialysis3.3 (2.8)
Biochemical markers
Kt/V1.6 (0.3)
Serum albumin, g/L35.8 (4.7)
Hemoglobin, g/L112 (16)
Calcium, mmol/L2.3 (0.2)
Phosphorous, mmol/L1.7 (0.6)
HRQL scores (baseline)
MHC39.0 (10.9)
PHC36.3 (11.0)
Symptoms/problems71.7 (16.4)
Effects of kidney disease60.7 (22.1)
Burden of kidney disease31.1 (30.6)
Table 2. mESAS Symptoms
Symptom% of PatientsMean (SD)
SymptomModerate/Severe
PresentSymptoms
Tired92.273.15.1 (2.7)
Lack of well-being90.959.14.2 (2.5)
Appetite82.147.03.6 (2.7)
Drowsy77.045.73.4 (2.8)
Itching75.844.53.6 (3.1)
Pain72.446.53.5 (3.0)
Anxious65.739.12.8 (2.9)
Depressed64.637.72.8 (2.9)
Shortness of breath61.932.72.6 (2.8)
Nauseated54.324.22.0 (2.5)

Total symptom distress score 33.4 (18.3)

Analysis of Baseline HRQL and Symptom Burden 

Predictors of baseline mental and physical HRQL can be seen in Table 3, Table 4, respectively. Although age, comorbidity, and serum albumin were associated with mental HRQL in the univariate analysis, only the mESAS symptoms pain, tiredness, lack of well-being, and depression remained significant in the multivariate regression analysis, accounting for 45.2% of the variation in the MHC (Table 3). Similarly, three of these four symptoms (pain, fatigue, and lack of well-being), along with shortness of breath, were the only independent predictors of physical HRQL, accounting for 38.5% of the variation seen in the PHC. There were no demographic or dialysis-related predictors for either baseline HRQL or symptom burden.

Table 3. Predictors of Baseline MHC
VariablesUnivariate Regression AnalysisMultivariate Regression Analysis
Slope (95% CI)R2 (%)P-valueSlope (95% CI)R2 (%)P-value
Age (years)−0.08 (−0.14, −0.03)1.50.004
Male−1.24 (−3.01, 0.54)0.30.173
Race 0.1
Aboriginal vs. white0.26 (−2.58, 3.09) 0.859
Others vs. white−0.79 (−3.26, 1.69) 0.532
CCI—tertiles 1.6
T2 (7–9) vs. T1 (≤6)−2.23 (−4.39, −0.07) 0.043
T3 (≥10) vs. T1 (≤6)−3.67 (−6.09, −1.25) 0.003
Years on dialysis−0.18 (−0.50, 0.13)0.20.256
ESAS symptom 45.2
Depressed−2.11 (−2.37, −1.84)31.6<0.001−1.29 (−1.56, −1.01) <0.001
Tired−2.20 (−2.48, −1.92)29.3<0.001−1.13 (−1.43, −0.82) <0.001
Lack of well-being−1.99 (−2.30, −1.68)21.4<0.001−0.58 (−0.90, −0.26) <0.001
Pain−1.46 (−1.73, −1.19)16.5<0.001−0.40 (−0.65, −0.14) 0.002
Anxious−1.90 (−2.17, −1.64)25.3<0.001
Drowsy−1.76 (−2.04, −1.47)19.9<0.001
Appetite−1.47 (−1.77, −1.17)13.5<0.001
Shortness of breath−1.24 (−1.54, −0.94)10.3<0.001
Nauseated−1.19 (−1.53, −0.84)7.3<0.001
Itching−0.76 (−1.04, −0.48)4.8<0.001
Biochemical markers
Kt/V0.77 (−1.80, 3.30)0.10.557
Serum albumin0.23 (0.04, 0.42)1.00.017
Hemoglobin0.03 (−0.02, 0.09)0.20.286
Calcium0.40 (−3.47, 4.27)<0.10.205
Phosphorous0.90 (−0.70, 2.51)0.20.270

ESAS totala−0.37 (−0.41,−0.33)39.4<0.001

CI=confidence interval.

aESAS total is not used in the multivariate model.

Table 4. Predictors of Baseline PHC
VariablesUnivariate Regression AnalysisMultivariate Regression Analysis
Slope (95% CI)R2 (%)P-valueSlope (95% CI)R2 (%)P-value
Age (years)0.20 (0.15, 0.25)8.7<0.001
Male0.23 (−1.57, 2.03)<0.10.801
Race 0.1
Aboriginal vs. white−2.84 (−5.68, −0.00) 0.050
Others vs. white−0.12 (−2.62, 2.37) 0.923
CCI—tertiles 2.1
T2 (7–9) vs. T1 (≤6)3.79 (1.61, 5.97) 0.001
T3 (≥10) vs. T1 (≤6)2.90 (0.46, 5.34) 0.020
Years on dialysis−0.23 (−0.55, 0.10)<0.10.166
ESAS symptom 38.5
Pain−2.05 (−2.29, −1.80)31.7<0.001−1.51 (−1.78, −1.24) <0.001
Tired−1.78 (−2.08, −1.48)18.6<0.001−0.58 (−0.91, −0.25) <0.001
Lack of well-being−1.79 (−2.12, −1.47)16.9<0.001−0.59 (−0.92, −0.25) <0.001
Shortness of breath−1.32 (−1.62, −1.02)11.3<0.001−0.44 (−0.73, −0.16) 0.002
Drowsy−1.38 (−1.68, −1.07)11.9<0.001
Anxious−1.26 (−1.56, −0.97)10.8<0.001
Depressed−1.18 (−1.47, −0.88)9.5<0.001
Appetite−1.24 (−1.55, 1.92)9.3<0.001
Nauseated−1.11 (−1.46, −0.76)6.2<0.001
Itching−0.74 (−1.02, −0.46)4.4<0.001
Biochemical markers
Kt/V−0.61 (−3.23, 2.01)<0.10.649
Serum albumin−0.11 (−0.31, 0.08)<0.10.238
Hemoglobin0.02 (−0.04, 0.08)<0.10.466
Calcium0.88 (−2.97, 4.73)<0.10.654
Phosphorous−1.47 (−3.09, 0.16)<0.10.076

ESAS totala−0.33 (−0.37, −0.29)29.2<0.001

CI=confidence interval.

aESAS total is not used in the multivariate model.

Analysis of Change in HRQL and Symptom Burden at Six-Month Follow-Up 

Over the six-month follow-up period, the mean (SD) change in total symptom burden score was 20.9 (15.4), with mean (SD)changes in individual symptom scores ranging from 2.7 (2.6) for shortness of breath to 3.4 (2.7) for pain. The mean (SD) changes in MHC and PHC were 10.5 (8.8) and 12.5 (8.9), respectively. Predictors of change in mental and physical HRQL after six months can be seen in Table 5, Table 6, respectively. Changes in biochemical parameters did not predict a change in the MHC score. In the univariate regression analysis, changes in all mESAS symptoms were associated with changes in the MHC, with the ESAS total score predicting 46.1% of the variation. In the multivariate regression analysis, only changes in depression, anxiety, tiredness, and lack of appetite scores were independently associated with a change in MHC score, accounting for 48.7% of the variability seen.

Table 5. Predictors of Change in the MHC at Six Months
VariablesUnivariate Regression AnalysisMultivariate Regression Analysis
Slope (95% CI)R2 (%)P-valueSlope (95% CI)R2 (%)P-value
Change in ESAS symptom 48.7
Depressed−2.12 (−2.50, −1.74)32.5<0.001−0.67 (−1.22, −0.13) 0.016
Tired−2.24 (−2.65, −1.84)32.0<0.001−1.18 (−1.61, −0.75) <0.001
Anxious−2.08 (−2.46, −1.70)31.4<0.001−0.72 (−1.11, −0.33) 0.002
Appetite−1.69 (−2.11, −1.28)20.4<0.001−0.83 (−1.35, −0.31) <0.001
Lack of well-being−1.96 (−2.42,−1.51)22.3<0.001
Pain−1.69 (−2.09, −1.28)21.5<0.001
Drowsy−1.83 (−2.27, −1.40)21.3<0.001
Shortness of breath−1.42 (−1.89, −0.94)11.9<0.001
Nauseated−1.44 (−1.94, −0.93)11.0<0.001
Itching−0.87 (−1.31, −0.43)5.7<0.001
Change in biochemical markers
Kt/V2.35 (−4.24, 8.95)<0.10.483
Serum albumin−0.15 (−0.75, 0.45)<0.10.617
Hemoglobin−0.10 (−0.21, 0.02)0.10.113
Calcium−7.51 (−18.7, 3.67)<0.10.187
Phosphorous0.79 (−3.00, 4.59)<0.10.681

Change in ESAS totala−0.40 (−0.45, −0.35)46.1<0.001

CI=confidence interval.

aChange in ESAS total is not used in the multivariate model.

Table 6. Predictors of Change in the PHC at Six Months
VariablesUnivariate Regression AnalysisMultivariate Regression Analysis
Slope (95% CI)R2 (%)P-valueSlope (95% CI)R2 (%)P-value
Change in ESAS symptom 44.6
Pain−1.95 (−2.27, −1.63)36.8<0.001−1.33 (−1.69, −0.97) <0.001
Tired−1.84 (−2.22, −1.47)27.2<0.001−0.86 (−1.26, −0.47) <0.001
Appetite−1.37 (−1.74, −0.99)16.9<0.001−0.56 (−0.91, −0.21) 0.002
Lack of well-being−1.60 (−2.02, −1.18)18.1<0.001
Drowsy−1.48 (−1.88, −1.08)17.4<0.001
Anxious−1.19 (−1.58, −0.80)12.8<0.001
Depressed−1.03 (−1.43, −0.64)9.7<0.001
Nauseated−1.17 (−1.62, −0.71)9.1<0.001
Shortness of breath−1.00 (−1.44, −0.57)7.6<0.001
Itching−0.59 (−0.98, −0.19)3.3<0.001
Change in biochemical markers
Kt/V6.54 ( 0.63, 12.45)2.20.030
Serum albumin−0.57 (−1.10, −0.04)2.00.035
Hemoglobin−0.10 (−0.20, 0.01)1.50.079
Calcium−12.1 (−21.9, −2.26)2.70.016
Phosphorous0.60 (−2.83, 4.04)<0.10.730

Change in ESAS totala−0.31 (−0.36, −0.25)33.8<0.001

CI=confidence interval.

aChange in ESAS total is not used in the multivariate model.

Changes in Kt/V, serum albumin, and calcium were associated with changes in PHC scores in the univariate analysis but accounted for only 2.0%–2.7% of the variation and were not predictive in the final multivariate model. In contrast, changes in all the mESAS symptoms were associated with changes in the MHC score, with the total ESAS score predicting 33.8% of the variation in the univariate regression analysis. In the final multivariate regression model, only changes in pain, tiredness, and lack of appetite scores were independently associated with a change in PHC score, accounting for 44.6% of the variability. The CV for all biochemical, ESAS, and HRQL scores indicated sufficient variation over the six months of follow-up to establish an association should a relationship between these variables exist (data not shown).

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Discussion 

It is increasingly being recognized that people with progressive, chronic, nonmalignant illnesses experience a similar degree of symptom burden as many cancer patients. A recent review showed that 11 symptoms are often as prevalent in advanced disease of four chronic illnesses (ESRD, chronic obstructive pulmonary disease, heart disease, and acquired immunodeficiency syndrome) as among advanced cancer patients.9 There appears to be a common pathway that people with advanced, progressive disease share. Fatigue and pain were found to be particularly universal and frequent; breathlessness and anorexia were also recurrent symptoms in all five conditions. These symptoms were frequently reported by the dialysis patients in this study, with patients reporting a mean of 7.4 of the 10 studied symptoms.

Dialysis patients will typically have endured several complex symptoms for a prolonged period of time, and it would, therefore, be surprising if this symptom burden did not adversely affect HRQL. There is increasing evidence to suggest that the chronic pain experienced by ESRD patients is associated with over a two-fold increase in prevalence of insomnia and depression10 and that the substantial overall symptom burden negatively affects HRQL.4, 5, 8, 10, 22, 24, 25, 34 These prior studies have been limited by the use of nonvalidated instruments to measure HRQL, small sample sizes, a lack of longitudinal follow-up, and a failure to record metabolic parameters, markers of dialysis adequacy, and comorbidity. The literature also is not clear on which particular symptoms appear to have the greatest impact on HRQL or the effect size of symptom burden on HRQL to determine clinical relevance.

This study shows a strong relationship between overall symptom burden and both physical and mental components of HRQL. Moreover, changes in symptom burden over a six-month period were strongly associated with all aspects of HRQL, accounting for 48.7% and 44.6% of the change in the MHC and PHC scores, respectively. This is clearly clinically relevant, and interventions aimed at decreasing symptom burden may have the most significant impact on the HRQL of dialysis patients outside of transplantation. Although total symptom burden was highly predictive of HRQL, tiredness, pain, a lack of well-being, and a decrease in appetite appear to be symptoms with the greatest negative impact on overall HRQL, both at baseline and during longitudinal assessments, with the addition of depression and anxiety affecting MHC scores and shortness of breath affecting PHC scores.

In contrast, no metabolic or patient-related factors were independently associated with HRQL at the baseline assessment or after six months of follow-up. Numerous studies in the literature have examined the association of variables such as anemia and erythropoietin use with HRQL. These have been recently reviewed and have led to conflicting conclusions.35 Several studies have failed to show a clinically meaningful association between hemoglobin concentration and HRQL.36, 37 Those that have shown an association have had numerous methodological limitations, including use of only portions of validated HRQL measures, a lack of statistical adjustment for potentially confounding clinical variables, exclusion of patients older than 65 years or with significant comorbidity, and a lack of effect size, thus limiting the comprehensiveness, validity, and clinical relevance of the results.38, 39, 40, 41 None of the studies included a comprehensive assessment of common symptoms. Most of the associations between anemia and HRQL have been limited to domains such as vitality37, 38, 42, 43 and have failed to show effect sizes greater than minimally important differences in HRQL, thus questioning the clinical relevance.4, 5, 23, 24, 44 Similarly, adjusting dialysis dose or membrane type has little impact on improving HRQL.45 These studies suggest that physical and psychosocial aspects of ESRD are likely more important mediators of HRQL impairment than biochemical or dialysis-related variables.

Given the prevalence and severity of symptoms and their negative impact on all aspects of HRQL, it is time that national and international societies develop guidelines and institute programs to reduce symptom burden. Symptom management strategies are core elements of palliative care services, but they have focused primarily on cancer patients. Less attention has been paid to patients with chronic nonmalignant conditions, with very little attention paid to patients with ESRD. Thus, additional research will be required to develop effective assessment and management strategies for various symptoms in CKD. Potentially, symptoms requiring the most immediate attention given their clear negative impact on HRQL may include pain, fatigue, depression, anorexia, and a lack of well-being. Multidisciplinary approaches aimed at treating symptom complexes will likely be needed because most patients experience numerous symptoms over prolonged periods of time. Novel pharmacological approaches will also likely be required given the complexity of symptom clusters. This may include research into agents, such as exogenous and endogenous cannabinoids, that have the potential to address several of the symptoms common to patients with ESRD.

There are limitations to this study. Generalizability to the entire ESRD population may not be possible given that the study consisted primarily of white patients. However, other patient characteristics are representative of the North American ESRD patient population.46, 47 Not all symptoms were assessed. However, the ESAS measures the symptoms that are particularly troublesome for ESRD patients and that appear to be present universally in several progressive, chronic, noncurable illnesses. An added advantage of the ESAS is its short length, allowing for high response rates (90% in this study). The ESAS has been used extensively in cancer patients as a measure of symptom burden. An advantage of using tools common to other end-of-life patient groups is that relevant and useful comparisons can be made.48 In addition, psychometrically sound assessments of HRQL were used.

The longitudinal aspect of this study strengthens the observation that symptom burden is substantial and has a tremendous negative impact on all aspects of ESRD patients' HRQL. Symptom burden is an area amenable to clinical intervention. These patients, therefore, would likely benefit from the institution of symptom assessment and management programs aimed at reducing symptom burden.

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 This study was partially funded by the Institute of Health Economics.

PII: S0885-3924(10)00089-8

doi:10.1016/j.jpainsymman.2009.08.008

Journal of Pain and Symptom Management
Volume 39, Issue 3 , Pages 477-485, March 2010

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