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      The clinical utility and cost impact of cystatin C measurement in the diagnosis and management of chronic kidney disease: A primary care cohort study

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          Abstract

          Background

          To reduce over-diagnosis of chronic kidney disease (CKD) resulting from the inaccuracy of creatinine-based estimates of glomerular filtration rate (GFR), UK and international guidelines recommend that cystatin-C-based estimates of GFR be used to confirm or exclude the diagnosis in people with GFR 45–59 ml/min/1.73 m 2 and no albuminuria (CKD G3aA1). Whilst there is good evidence for cystatin C being a marker of GFR and risk in people with CKD, its use to define CKD in this manner has not been evaluated in primary care, the setting in which most people with GFR in this range are managed.

          Methods and findings

          A total of 1,741 people with CKD G3a or G3b defined by 2 estimated GFR (eGFR) values more than 90 days apart were recruited to the Renal Risk in Derby study between June 2008 and March 2010. Using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, we compared GFR estimated from creatinine (eGFR creat), cystatin C (eGFR cys), and both (eGFR creat-cys) at baseline and over 5 years of follow-up. We analysed the proportion of participants with CKD G3aA1 reclassified to ‘no CKD’ or more advanced CKD with the latter two equations. We further assessed the impact of using cystatin-C-based eGFR in risk prediction equations for CKD progression and all-cause mortality and investigated non-GFR determinants of eGFR cys. Finally, we estimated the cost implications of implementing National Institute for Health and Care Excellence (NICE) guidance to use eGFR cys to confirm the diagnosis in people classified as CKD G3aA1 by eGFR creat. Mean eGFR cys was significantly lower than mean eGFR creat (45.1 ml/min/1.73 m 2, 95% CI 44.4 to 45.9, versus 53.6 ml/min/1.73 m 2, 95% CI 53.0 to 54.1, P < 0.001). eGFR cys reclassified 7.7% (50 of 653) of those with CKD G3aA1 by eGFR creat to eGFR ≥ 60 ml/min/1.73 m 2. However, a much greater proportion (59.0%, 385 of 653) were classified to an eGFR category indicating more severe CKD. A similar pattern was seen using eGFR creat-cys, but lower proportions were reclassified. Change in eGFR creat and eGFR cys over 5 years were weakly correlated ( r = 0.33, P < 0.001), but eGFR cys identified more people as having CKD progression (18.2% versus 10.5%). Multivariable analysis using eGFR creat as an independent variable identified age, smoking status, body mass index, haemoglobin, serum uric acid, serum albumin, albuminuria, and C reactive protein as non-GFR determinants of eGFR cys. Use of eGFR cys or eGFR creat-cys did not improve discrimination in risk prediction models for CKD progression and all-cause mortality compared to similar models with eGFR creat. Application of the NICE guidance, which assumed cost savings, to participants with CKD G3aA1 increased the cost of monitoring by £23 per patient, which if extrapolated to be applied throughout England would increase the cost of testing and monitoring CKD by approximately £31 million per year. Limitations of this study include the lack of a measured GFR and the potential lack of ethnic diversity in the study cohort.

          Conclusions

          Implementation of current guidelines on eGFR cys testing in our study population of older people in primary care resulted in only a small reduction in diagnosed CKD but classified a greater proportion as having more advanced CKD than eGFR creat. Use of eGFR cys did not improve risk prediction in this population and was associated with increased cost. Our data therefore do not support implementation of these recommendations in primary care. Further studies are warranted to define the most appropriate clinical application of eGFR cys and eGFR creat-cys.

          Abstract

          Adam Shardlow and colleagues investigate whether using cystatin C in addition to serum creatinine can improve diagnosis and risk prediction for progression of CKD among patients in primary care, and estimate the costs of additional testing and monitoring.

          Author summary

          Why was this study done?
          • Estimation of kidney function (glomerular filtration rate) from serum creatinine concentration may be inaccurate in some people due to the impact of muscle mass, diet, and drugs on creatinine concentration.

          • To reduce over-diagnosis of chronic kidney disease, international and UK guidelines recommend that the diagnosis of chronic kidney disease should be confirmed with an estimate of kidney function based on a different marker of glomerular filtration, cystatin C, in those people with only a mild reduction in glomerular filtration rate and no albuminuria.

          • The clinical utility of this guidance has not been adequately evaluated in primary care, the setting in which most people with chronic kidney disease are cared for.

          What did the researchers do and find?
          • We estimated glomerular filtration rate from serum creatinine and cystatin C in a cohort of 1,741 mainly older people diagnosed with chronic kidney disease in primary care.

          • The use of cystatin C to confirm a diagnosis of chronic kidney disease resulted in reclassification of a small proportion (7.7%) of people as not having chronic kidney disease, but a much greater proportion were reclassified as having more advanced disease (59%).

          • In this cohort, the use of cystatin C did not result in improved risk prediction for all-cause mortality or progression of chronic kidney disease.

          • We estimate that the use of cystatin C as recommended in current guidelines would result in increased healthcare costs of £23 per person in the first year of implementation.

          What do these findings mean?
          • Our data do not support the use of cystatin C to confirm a diagnosis of chronic kidney disease in primary care.

          • Cystatin C may be useful for estimating glomerular filtration rate in other settings where creatinine is known to be unreliable, for example in people with extremes of body habitus.

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          Most cited references22

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          Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis.

          Chronic kidney disease is characterised by low estimated glomerular filtration rate (eGFR) and high albuminuria, and is associated with adverse outcomes. Whether these risks are modified by diabetes is unknown. We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and end-stage renal disease (ESRD) associated with eGFR and albuminuria in individuals with and without diabetes. We analysed data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts. In the combined general population and high-risk cohorts with data for all-cause mortality, 75,306 deaths occurred during a mean follow-up of 8·5 years (SD 5·0). In the 23 studies with data for cardiovascular mortality, 21,237 deaths occurred from cardiovascular disease during a mean follow-up of 9·2 years (SD 4·9). In the general and high-risk cohorts, mortality risks were 1·2-1·9 times higher for participants with diabetes than for those without diabetes across the ranges of eGFR and albumin-to-creatinine ratio (ACR). With fixed eGFR and ACR reference points in the diabetes and no diabetes groups, HR of mortality outcomes according to lower eGFR and higher ACR were much the same in participants with and without diabetes (eg, for all-cause mortality at eGFR 45 mL/min per 1·73 m(2) [vs 95 mL/min per 1·73 m(2)], HR 1·35; 95% CI 1·18-1·55; vs 1·33; 1·19-1·48 and at ACR 30 mg/g [vs 5 mg/g], 1·50; 1·35-1·65 vs 1·52; 1·38-1·67). The overall interactions were not significant. We identified much the same findings for ESRD in the chronic kidney disease cohorts. Despite higher risks for mortality and ESRD in diabetes, the relative risks of these outcomes by eGFR and ACR are much the same irrespective of the presence or absence of diabetes, emphasising the importance of kidney disease as a predictor of clinical outcomes. US National Kidney Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Detection of chronic kidney disease with creatinine, cystatin C, and urine albumin-to-creatinine ratio and association with progression to end-stage renal disease and mortality.

            A triple-marker approach for chronic kidney disease (CKD) evaluation has not been well studied. To evaluate whether combining creatinine, cystatin C, and urine albumin-to-creatinine ratio (ACR) would improve identification of risks associated with CKD compared with creatinine alone. Prospective cohort study involving 26,643 US adults enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study from January 2003 to June 2010. Participants were categorized into 8 groups defined by estimated glomerular filtration rate (GFR) determined by creatinine and by cystatin C of either <60 or ≥60 mL/min/1.73 m(2) and ACR of either <30 or ≥30 mg/g. All-cause mortality and incident end-stage renal disease with median follow-up of 4.6 years. Participants had a mean age of 65 years, 40% were black, and 54% were women. Of 26,643 participants, 1940 died and 177 developed end-stage renal disease. Among participants without CKD defined by creatinine, 24% did not have CKD by either ACR or cystatin C. Compared with those with CKD defined by creatinine alone, the hazard ratio for death in multivariable-adjusted models was 3.3 (95% confidence interval [CI], 2.0-5.6) for participants with CKD defined by creatinine and ACR; 3.2 (95% CI, 2.2-4.7) for those with CKD defined by creatinine and cystatin C, and 5.6 (95% CI, 3.9-8.2) for those with CKD defined by all biomarkers. Among participants without CKD defined by creatinine, 3863 (16%) had CKD detected by ACR or cystatin C. Compared with participants who did not have CKD by any measure, the HRs for mortality were 1.7 (95% CI, 1.4-1.9) for participants with CKD defined by ACR alone, 2.2 (95% CI, 1.9-2.7) for participants with CKD defined by cystatin C alone, and 3.0 (95% CI, 2.4-3.7) for participants with CKD defined by both measures. Risk of incident end-stage renal disease was higher among those with CKD defined by all markers (34.1 per 1000 person-years; 95% CI, 28.7-40.5 vs 0.33 per 1000 person-years; 95% CI, 0.05-2.3) for those with CKD defined by creatinine alone. The second highest end-stage renal disease rate was among persons missed by the creatinine measure but detected by both ACR and cystatin C (rate per 1000 person-years, 6.4; 95% CI, 3.6-11.3). Net reclassification improvement for death was 13.3% (P < .001) and for end-stage renal disease was 6.4% (P < .001) after adding estimated GFR cystatin C in fully adjusted models with estimated GFR creatinine and ACR. Adding cystatin C to the combination of creatinine and ACR measures improved the predictive accuracy for all-cause mortality and end-stage renal disease.
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              • Abstract: found
              • Article: not found

              Estimating glomerular filtration rate for the full age spectrum from serum creatinine and cystatin C.

              We recently published and validated the new serum creatinine (Scr)-based full-age-spectrum equation (FAScrea) for estimating the glomerular filtration rate (GFR) for healthy and kidney-diseased subjects of all ages. The equation was based on the concept of normalized Scr and shows equivalent to superior prediction performance to the currently recommended equations for children, adolescents, adults and older adults.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                10 October 2017
                October 2017
                : 14
                : 10
                : e1002400
                Affiliations
                [1 ] Renal Unit, Royal Derby Hospital, Derby, United Kingdom
                [2 ] Centre for Kidney Research and Innovation, Division of Medical Sciences and Graduate Entry Medicine, School of Medicine, University of Nottingham, Royal Derby Hospital, Derby, United Kingdom
                [3 ] Academic Unit of Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
                [4 ] Division of Nephrology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
                Istituto Di Ricerche Farmacologiche Mario Negri, ITALY
                Author notes

                MWT is a member of the PLOS Medicine Editorial Board. RJF is Clinical CO-Chair, Internal Medicine Programme of Care, Specialised Commissioning, NHS England and chair, Think Kidneys, UK Renal Registry.

                Author information
                http://orcid.org/0000-0002-8077-3710
                http://orcid.org/0000-0001-9475-6850
                http://orcid.org/0000-0003-1094-8578
                Article
                PMEDICINE-D-17-01612
                10.1371/journal.pmed.1002400
                5634538
                29016597
                8bb9bdf0-b939-4687-8698-f052dbaa3209
                © 2017 Shardlow et al

                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.

                History
                : 13 May 2017
                : 1 September 2017
                Page count
                Figures: 3, Tables: 7, Pages: 18
                Funding
                Funded by: Dunhill Medical Trust (GB)
                Award ID: R302/0713
                Funded by: Joint British Renal Society and Kidney Research UK Fellowship
                Award ID: BRS3/2008
                Award Recipient :
                Funded by: Roche Products Ltd.
                Award ID: EPWE124712-G
                The RRID study is currently funded by a Research Project Grant (R302/0713) from the Dunhill Medical Trust ( http://www.dunhillmedical.org.uk). Previous study funding includes a joint British Renal Society ( http://www.britishrenal.org) and Kidney Research UK ( http://www.kidneyresearchuk.org) fellowship (BRS3/2008, to NJM), and an unrestricted educational grant (EPWE124712-G) from Roche Products Ltd. ( https://www.roche.co.uk). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Biology and Life Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Creatinine
                Medicine and Health Sciences
                Health Care
                Primary Care
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Forecasting
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Urine
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Urine
                Biology and Life Sciences
                Physiology
                Body Fluids
                Urine
                Medicine and Health Sciences
                Physiology
                Body Fluids
                Urine
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Custom metadata
                Anonymised data can be made available to researchers who meet the conditions of the ethics approval and research governance policy that applies to this study. Researchers may apply for data access by contacting Dr. Teresa Grieve, Research and Development Manager, Derby Teaching Hospitals NHS Foundation Trust ( teresa.grieve@ 123456nhs.net ).

                Medicine
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