A Systematic Review and Meta-Analysis of Utility-Based Quality of Life in Chronic Kidney Disease Treatments

Abstract

Melanie Wyld and colleagues examined previously published studies to assess pooled utility-based quality of life of the various treatments for chronic kidney disease. They conclude that the highest utility was for kidney transplants, with home-based automated peritoneal dialysis being second.

Abstract

Background

Chronic kidney disease (CKD) is a common and costly condition to treat. Economic evaluations of health care often incorporate patient preferences for health outcomes using utilities. The objective of this study was to determine pooled utility-based quality of life (the numerical value attached to the strength of an individual's preference for a specific health outcome) by CKD treatment modality.

Methods and Findings

We conducted a systematic review, meta-analysis, and meta-regression of peer-reviewed published articles and of PhD dissertations published through 1 December 2010 that reported utility-based quality of life (utility) for adults with late-stage CKD. Studies reporting utilities by proxy (e.g., reported by a patient's doctor or family member) were excluded.

In total, 190 studies reporting 326 utilities from over 56,000 patients were analysed. There were 25 utilities from pre-treatment CKD patients, 226 from dialysis patients (haemodialysis, n = 163; peritoneal dialysis, n = 44), 66 from kidney transplant patients, and three from patients treated with non-dialytic conservative care. Using time tradeoff as a referent instrument, kidney transplant recipients had a mean utility of 0.82 (95% CI: 0.74, 0.90). The mean utility was comparable in pre-treatment CKD patients (difference = −0.02; 95% CI: −0.09, 0.04), 0.11 lower in dialysis patients (95% CI: −0.15, −0.08), and 0.2 lower in conservative care patients (95% CI: −0.38, −0.01). Patients treated with automated peritoneal dialysis had a significantly higher mean utility (0.80) than those on continuous ambulatory peritoneal dialysis (0.72; p = 0.02). The mean utility of transplant patients increased over time, from 0.66 in the 1980s to 0.85 in the 2000s, an increase of 0.19 (95% CI: 0.11, 0.26). Utility varied by elicitation instrument, with standard gamble producing the highest estimates, and the SF-6D by Brazier et al., University of Sheffield, producing the lowest estimates. The main limitations of this study were that treatment assignments were not random, that only transplant had longitudinal data available, and that we calculated EuroQol Group EQ-5D scores from SF-36 and SF-12 health survey data, and therefore the algorithms may not reflect EQ-5D scores measured directly.

Conclusions

For patients with late-stage CKD, treatment with dialysis is associated with a significant decrement in quality of life compared to treatment with kidney transplantation. These findings provide evidence-based utility estimates to inform economic evaluations of kidney therapies, useful for policy makers and in individual treatment discussions with CKD patients.

Editors' Summary

Background

Ill health can adversely affect an individual's quality of life, particularly if caused by long-term (chronic) conditions, such as chronic kidney disease—in the United States alone, 23 million people have chronic kidney disease, of whom 570,000 are treated with dialysis or kidney transplantation. In order to measure the cost-effectiveness of interventions to manage medical conditions, health economists use an objective measurement known as quality-adjusted life years. However, although useful, quality-adjusted life years are often criticized for not taking into account the views and preferences of the individuals with the medical conditions. A measurement called a utility solves this problem. Utilities are a numerical value (measured on a 0 to 1 scale, where 0 represents death and 1 represents full health) of the strength of an individual's preference for specified health-related outcomes, as measured by “instruments” (questionnaires) that rate direct comparisons or assess quality of life.

Why Was This Study Done?

Previous studies have suggested that, in people with chronic kidney disease, quality of life (as measured by utility) is higher in those with a functioning kidney transplant than in those on dialysis. However, currently, it is unclear whether the type of dialysis affects quality of life: hemodialysis is a highly technical process that directly filters the blood, usually must be done 2–4 times a week, and can only be performed in a health facility; peritoneal dialysis, in which fluids are infused into the abdominal cavity, can be done nightly at home (automated peritoneal dialysis) or throughout the day (continuous ambulatory peritoneal dialysis). In this study, the researchers reviewed and assimilated all of the available evidence to investigate whether quality of life in people with chronic kidney disease (as measured by utility) differed according to treatment type.

What Did the Researchers Do and Find?

The researchers did a comprehensive search of 11 databases to identify all relevant studies that included people with severe (stage 3, 4, or 5) chronic kidney disease, their form of treatment, and information on utilities—either reported directly, or included in quality of life instruments (SF-36), so the researchers could calculate utilities by using a validated algorithm. The researchers also recorded the prevalence rates of diabetes in study participants. Then, using statistical models that adjusted for various factors, including treatment type and the method of measuring utilities, the researchers were able to calculate the pooled utilities of each form of treatment for chronic kidney disease.

The researchers included 190 studies, representing over 56,000 patients and generating 326 utility estimates, in their analysis. The majority of utilities (77%) were derived through the SF-36 questionnaire via calculation. Of the 326 utility estimates, 25 were from patients pre-dialysis, 226 were from dialysis patients (the majority of whom were receiving hemodialysis), 66 were from kidney transplant patients, and three were from conservative care patients. The researchers found that the highest average utility was for those who had renal transplantation, 0.82, followed by the pre-dialysis group (0.80), dialysis patients (0.71), and, finally, patients receiving conservative care (0.62). When comparing the type of dialysis, the researchers found that there was little difference in utility between hemodialysis and peritoneal dialysis, but patients using automated peritoneal dialysis had, on average, a higher utility (0.80) than those treated with continuous ambulatory peritoneal dialysis (0.72). Finally, the researchers found that patient groups with diabetes had significantly lower utilities than those without diabetes.

What Do These Findings Mean?

These findings suggest that in people with chronic kidney disease, renal transplantation is the best treatment option to improve quality of life. For those on dialysis, home-based automated peritoneal dialysis may improve quality of life more than the other forms of dialysis: this finding is important, as this type of dialysis is not as widely used as other forms and is also cheaper than hemodialysis. Furthermore, these findings suggest that patients who choose conservative care have significantly lower quality of life than patients treated with dialysis, a finding that warrants further investigation. Overall, in addition to helping to inform economic evaluations of treatment options, the information from this analysis can help guide clinicians caring for patients with chronic kidney disease in their discussions about possible treatment options.

Additional Information

Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001307.

• Information about chronic kidney disease is available from the National Kidney Foundation and MedlinePlus

• Wikipedia gives information on general utilities (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)

Contributors

: Role: Academic Editor

Journal

Journal ID (nlm-ta): PLoS Med

Journal ID (iso-abbrev): PLoS Med

Journal ID (publisher-id): PLoS

Journal ID (pmc): plosmed

Title: PLoS Medicine

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Print): 1549-1277

ISSN (Electronic): 1549-1676

Publication date Collection: September 2012

Publication date (Print): September 2012

Publication date (Electronic): 11 September 2012

Volume: 9

Issue: 9

Affiliations

[1 ]Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia

[2 ]School of Public Health and Community Medicine, University of New South Wales, Sydney, New South Wales, Australia

[3 ]Centre for Transplant and Renal Research, Westmead Hospital, Westmead, New South Wales, Australia

University of Edinburgh, United Kingdom

Author notes

* E-mail: mwyl6884@ 123456uni.sydney.edu.au

The authors have declared that no competing interests exist.

Conceived and designed the experiments: MW RLM AH KH ACW. Performed the experiments: MW RLM AH KH ACW. Analyzed the data: MW RLM AH KH ACW. Contributed reagents/materials/analysis tools: AH. Wrote the first draft of the manuscript: MW. Contributed to the writing of the manuscript: MW RLM AH KH ACW. ICMJE criteria for authorship read and met: MW RLM AH KH ACW. Agree with manuscript results and conclusions: MW RLM AH KH ACW.

Article

Publisher ID: PMEDICINE-D-11-02649

DOI: 10.1371/journal.pmed.1001307

PMC ID: 3439392

PubMed ID: 22984353

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Page count

Pages: 10

Funding

No specific funding was received for this study. MW was supported by a summer scholarship stipend. RM was supported through National Health and Medical Research Council grants #457281 and #571372. AH was supported through a National Health and Medical Research Council grant #633003. KH and AW were personally salaried by their institutions during the period of writing (though no specific salary was set aside or given for the writing of this paper). No funding bodies had any role in the study design, data collection, analysis, decision to publish or preparation of the manuscript.

Categories

Subject: Research Article

Subject: Medicine

Subject: Nephrology

Subject: Acute Renal Failure

Subject: Chronic Kidney Disease

Subject: Dialysis

Subject: Renal Transplantation

Subject: Non-Clinical Medicine

Subject: Health Care Policy

Subject: Quality of Life

Subject: Social and Behavioral Sciences

Subject: Economics

Subject: Health Economics