A previous publication highlighting our multidisciplinary clinic demonstrated the feasibility and clinical effectiveness of a model to deliver anemia management to patients with CKD. In the clinic model, the target hemoglobin (11 to 12 g/dL) for erythropoietic stimulating agent treatment was based on guidelines endorsed by the National Kidney Foundation. 27
In this manuscript, we provide baseline and follow-up estimates of quality of life (as measured by the KDQOL-SF™) for a cohort of our clinic patients with CKD receiving anemia management with erythropoietic proteins. Overall, our kidney disease specific estimates (as assessed by the kidney disease components in the KDQOL™) demonstrated better quality of life as compared to patients with ESRD.23,24
Our baseline measures of kidney disease specific quality of life are useful as a benchmark in CKD patients. This benchmark is useful to help gauge the effectiveness of anemia interventions and to put the negative effects of CKD into perspective. Our baseline measures suggest that CKD is especially detrimental with regard to ability to work (i.e., work status = 31.7) and role limitations caused by physical health problems (i.e., role-physical = 39.0).
Because the KDQOL-SF™ is designed specifically for kidney disease, quality of life measured on this scale cannot be compared to a healthy population. However, the SF-36 – a generic measure of health status – has been used as a measure of quality of life in healthy populations.26
Compared to healthy populations, patients with pre-dialysis CKD demonstrated significantly lower health status scores on the SF-36 – as shown in . Compared to populations with ESRD,23, 24
patients with pre-dialysis CKD had similar health status. This finding of similar QOL score for general health domains, as measured by the SF-36 for CKD and ESRD patients, suggests that the SF-36 may not be sensitive enough to detect kidney disease stage specific measures of QOL. Our data also suggested this - showing a trend toward disparate scores in several measures of the kidney disease specific questions of the KDQOL-SF™ between CKD and ESRD and a lack of disparate scores in similar domains of the SF-36 component between these groups. The implications of this observation may be that specific reductions in QOL attributed to kidney disease will be overlooked in the SF-36. Hence, centers that use this latter measure only may not have the sensitivity to find true reductions in QOL in the CKD patient population. Additionally, as patients move from one stage of CKD to another, it may not be practical to detect QOL changes that may be apparent from less severe to more severe disease staging. Therefore, the impact of stage of kidney disease on QOL may best be assessed by the kidney specific component of the KDQOL-SF™. Further validation of this assertion is needed since the KDQOL-SF™ has not previously been validated in CKD, even though it has been used in previous studies of CKD.15, 16
In the subset of our patients who provided longitudinal assessments of quality of life, we found general trends towards improvement in quality of life while enrolled in the CKD clinic. With regard to the kidney disease specific domains, improvements in QOL were statistically significant with regard to sleep and social functioning. It is difficult to expand on why these factors improved, and future work should consider further exploration of this area. We did not see any statistically significant improvements (only trends in improvements) in the general health domains of the KDQOL-SF™. We also did not assess changes in KDQOL-SF™ scores in relationship to changes in CKD stage since our follow-up time period was ≤ one year in duration. A study that tested KDQOL™ in a longitudinal approach from CKD to ESRD showed that patients who transitioned to dialysis had significant decreases in the domain scores for burden and effects of kidney disease.28
This suggests that changes in kidney function may obscure clinical and QOL improvements that result from other interventions such as management of anemia.
The slightly lower reported general SF-36 scores in our population versus the previous publication needs to be explored. There are at least two possible explanations for this observation. The first being differences in the racial make-up of the two studies. Our study had ~50% African-Americans and the previous CKD study had ~25% of patients in this race category.25
While it has been reported in hemodialysis patients that African-American patients report higher QOL scores in most domains,29
one needs to consider the effect of changes in kidney function (consistent with the CKD process) and its effect on QOL. Hence, the second factor is the effect of changes in kidney function (i.e. changes in CKD staging). Declines in kidney function may occur at different rates in different racial backgrounds and hence may effect QOL self-reports. 28
If patients were evaluated in a relative state of a more rapid decline, it is reasonable to entertain the prospect that this may result in a lower reported QOL value across many domains. This would potentially reduce the positive impact that race may have had on QOL score (as in an African-American population). We did not assess changes in kidney function over time to enable an assessment in this regard. Additionally, trends in follow-up QOL values in the Perlman, et al study were not reported.25
Although not an initial aim of our study, we retrospectively evaluated patient demographic and clinical parameters to assess their impact on predicting baseline QOL. While most clinical measures (calcium, phosphorus, parathyroid hormone, glomerular filtration rate, serum creatinine, transferrin saturation, and ferritin) did not appear to have a significant effect on QOL, their contribution cannot be ruled out since our study was not adequately powered for this analysis. Hemoglobin trended towards significance (i.e., P = 0.06) as a predictor of kidney specific domains. Since previous studies have reported that anemia – assessed by low hemoglobin – is related to lower quality of life,25,30
we hypothesize that untreated baseline anemia is a contributing factor to the low QOL estimates we found in the CKD clinic. Our mean ±
standard deviation follow-up hemoglobin values for these patients (11.7 ±
were within the planned target range and are consistent with the currently recommended range by the Food and Drug Administration for patients receiving erythropoiesis stimulating agents.13
A recent CKD study showed QOL values in low (11.5 g/dL) and high (13.5 g/dL) hemoglobin arms to be relatively consistent after therapy with erythropoietin beta for two years.12
Hence correction of hemoglobin levels to within the acceptable range appears to provide similar scores for QOL without enhanced risk for cardiovascular complications.12,31
Although we did not have sufficient statistical power to actually test whether longitudinal improvements in hemoglobin were correlated with improvements in quality of life, this presents an opportunity for future research.
Our study has several other limitations that need to be considered. First and foremost, it was observational in nature and was not powered to detect statistically significant changes. Future studies should use our preliminary effect size estimates to conduct a randomized, controlled study to test (a priori) the factors, such as hemoglobin and/or changes in CKD staging, that may predict improved quality of life. The baseline estimates of quality of life are limited by our relatively small convenience sample. Patients were not randomly selected, but rather were eligible due to their participation in our CKD clinic and their willingness to complete quality of life surveys. Furthermore, our study population was derived from one clinical site. We conducted hypothesis tests among a subset of patients that had endpoint assessments to determine whether quality of life changed over time; these tests should be interpreted in light of the fact that our study was not designed to test hypotheses. Multivariate analysis should be viewed strictly as exploratory given the small sample size. Sample size also limited our ability to make stage-specific inferences. Still, this study provides insight for a pre-dialysis CKD population that has not been well studied in terms of QOL assessments by the KDQOL-SF™.