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Chronic Kidney Disease Diagnosis and Management : A Review

  • 1 Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
  • 2 Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland

Importance   Chronic kidney disease (CKD) is the 16th leading cause of years of life lost worldwide. Appropriate screening, diagnosis, and management by primary care clinicians are necessary to prevent adverse CKD-associated outcomes, including cardiovascular disease, end-stage kidney disease, and death.

Observations   Defined as a persistent abnormality in kidney structure or function (eg, glomerular filtration rate [GFR] <60 mL/min/1.73 m 2 or albuminuria ≥30 mg per 24 hours) for more than 3 months, CKD affects 8% to 16% of the population worldwide. In developed countries, CKD is most commonly attributed to diabetes and hypertension. However, less than 5% of patients with early CKD report awareness of their disease. Among individuals diagnosed as having CKD, staging and new risk assessment tools that incorporate GFR and albuminuria can help guide treatment, monitoring, and referral strategies. Optimal management of CKD includes cardiovascular risk reduction (eg, statins and blood pressure management), treatment of albuminuria (eg, angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers), avoidance of potential nephrotoxins (eg, nonsteroidal anti-inflammatory drugs), and adjustments to drug dosing (eg, many antibiotics and oral hypoglycemic agents). Patients also require monitoring for complications of CKD, such as hyperkalemia, metabolic acidosis, hyperphosphatemia, vitamin D deficiency, secondary hyperparathyroidism, and anemia. Those at high risk of CKD progression (eg, estimated GFR <30 mL/min/1.73 m 2 , albuminuria ≥300 mg per 24 hours, or rapid decline in estimated GFR) should be promptly referred to a nephrologist.

Conclusions and Relevance   Diagnosis, staging, and appropriate referral of CKD by primary care clinicians are important in reducing the burden of CKD worldwide.

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Chen TK , Knicely DH , Grams ME. Chronic Kidney Disease Diagnosis and Management : A Review . JAMA. 2019;322(13):1294–1304. doi:10.1001/jama.2019.14745

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Open Access

Peer-reviewed

Research Article

Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis

* E-mail: [email protected]

Affiliation Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom

ORCID logo

Affiliation Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom

  • Nathan R. Hill, 
  • Samuel T. Fatoba, 
  • Jason L. Oke, 
  • Jennifer A. Hirst, 
  • Christopher A. O’Callaghan, 
  • Daniel S. Lasserson, 
  • F. D. Richard Hobbs

PLOS

  • Published: July 6, 2016
  • https://doi.org/10.1371/journal.pone.0158765
  • Reader Comments

Fig 1

Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking. Thus we sought to determine the prevalence of CKD globally, by stage, geographical location, gender and age. A systematic review and meta-analysis of observational studies estimating CKD prevalence in general populations was conducted through literature searches in 8 databases. We assessed pooled data using a random effects model. Of 5,842 potential articles, 100 studies of diverse quality were included, comprising 6,908,440 patients. Global mean(95%CI) CKD prevalence of 5 stages 13·4%(11·7–15·1%), and stages 3–5 was 10·6%(9·2–12·2%). Weighting by study quality did not affect prevalence estimates. CKD prevalence by stage was Stage-1 (eGFR>90+ACR>30): 3·5% (2·8–4·2%); Stage-2 (eGFR 60–89+ACR>30): 3·9% (2·7–5·3%); Stage-3 (eGFR 30–59): 7·6% (6·4–8·9%); Stage-4 = (eGFR 29–15): 0·4% (0·3–0·5%); and Stage-5 (eGFR<15): 0·1% (0·1–0·1%). CKD has a high global prevalence with a consistent estimated global CKD prevalence of between 11 to 13% with the majority stage 3. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes.

Citation: Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS, et al. (2016) Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis. PLoS ONE 11(7): e0158765. https://doi.org/10.1371/journal.pone.0158765

Editor: Giuseppe Remuzzi, Mario Negri Institute for Pharmacological Research and Azienda Ospedaliera Ospedali Riuniti di Bergamo, ITALY

Received: November 19, 2015; Accepted: June 21, 2016; Published: July 6, 2016

Copyright: © 2016 Hill 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.

Data Availability: All data are from Dryad (datadryad.org); the DOI number is doi: 10.5061/dryad.3s7rd .

Funding: NH is funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre based at Oxford University Hospitals NHS Trust and University of Oxford. FDRH is part funded as Director of the National Institute for Health Research (NIHR) School for Primary Care Research (SPCR), Theme Leader in the NIHR Oxford Biomedical Research Centre (BRC), and Director of the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) Oxford. DSL is part funded by the NIHR Oxford Diagnostic Evidence Co-operative and NIHR Oxford BRC. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Chronic kidney disease (CKD) is associated with age-related renal function decline accelerated in hypertension, diabetes, obesity and primary renal disorders. [ 1 ] Cardiovascular disease (CVD) is the primary cause of morbidity and mortality where CKD is regarded as an accelerator of CVD risk and an independent risk factor for CVD events. [ 2 ] There is a graded inverse relationship between CVD risk and glomerular filtration rate (GFR) that is independent of age, sex and other risk factors. [ 3 – 6 ] Decreased renal function is a predictor of hospitalisation [ 1 , 2 ], cognitive dysfunction [ 7 ] and poor quality of life. [ 8 , 9 ] The healthcare burden is highest in early stages due to increased prevalence, affecting around 35% of those over 70 years. [ 10 ]

CKD is defined by indicators of kidney damage—imaging or proteinuria (commonly using albumin to creatinine ratio, ACR)—and decreased renal function (below thresholds of GFR estimated from serum creatinine concentration). [ 11 , 12 ] Current recommendations by Kidney Outcomes Quality Initiative (KDOQI) and National Institute for Health Excellence (NICE) [ 11 , 12 ] are to use serum creatinine concentration to estimate GFR (eGFR) and transform it using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. [ 13 ] CKD-EPI replaces the Modification of Diet in Renal Disease (MDRD) equation [ 14 ] as a more accurate predictor of clinical risk [ 15 ] and both these equations correct for selected non-renal influences (age, race, gender).

CKD can be classified into five stages using KDOQI [ 11 ] guidelines using thresholds of eGFR within the CKD range and/or evidence of structural renal changes e.g. proteinuria. NICE have suggested that stage 3 be subdivided into 3a and 3b reflecting increasing CVD risk. [ 12 ] The largest stage of CKD, with over 90% of cases, has been estimated from a UK retrospective lab audit study to be CKD stage 3 with 84% stage 3a (GFR of 45 to 59 ml/min/1·73m 2 ) and 16% stage 3b GFR of 30 to 44 ml/min/1·73m 2 . [ 16 ]

Changes over time in CKD prevalence are contentious. Data from the American National Health and Nutrition Examination Survey demonstrate that in the period 1999 to 2004 the prevalence of CKD stages 1 to 4 increased significantly when compared to the survey period 1988 to 1994 (13·1 versus 10·0%). [ 4 , 17 , 18 ] While this high (and rising 4 ,) prevalence is in part due to the ageing population, it is also associated with increases in hypertension and diabetes mellitus[ 1 ]. However, conversely a UK manuscript published in 2014 examined nationally representative cross-sectional studies within the UK and found that the prevalence estimates reported declined over time. [ 19 ]

CKD is recognised as having changed from a subspecialty issue to a global health concern. [ 20 ] The authors, therefore, sought to determine the global prevalence of CKD according to KDOQI criteria in published observational studies in the adult general population, by a systematic review and meta-analysis.

Materials and Methods

Search strategy and selection criteria.

The protocol has been published (PROSPERO: CRD42014009184) and conducted in accordance with the Meta-analysis Of Observational Studies in Epidemiology guidelines [ 21 ]. Search strategy was discussed with a librarian for optimum inclusion sensitivity. An early consensus panel on the search results expanded the criteria to include additional general populations not identified originally (e.g. laboratory based large population studies). The librarian performed iterative searches using the following repositories for published observational studies: Medline/PubMed, Embase, CINAHL, the Cochrane Register for Controlled Trials (CENTRAL), LILACS, SciELO, clinicaltrials.gov, WHO ICTRP. They used the Cochrane Collaboration’s Highly Sensitive Search Strategy to optimize results. [ 22 ] The search strategy for clinicaltrials.gov was Condition = (“kidney disease” OR “kidney failure” OR “kidney insufficiency” OR “kidney function” OR “kidney dysfunction” OR “renal disease” OR “renal failure” OR “renal insufficiency” OR “renal function” OR “renal dysfunction”) AND Outcome = prevalence. The reference lists of other systematic reviews on prevalence of CKD were searched for potentially relevant articles. All databases were searched from inception to the 1st September 2014.

Study selection and data extraction

Original peer-reviewed publications were selected by two authors (NH, SF) if they included: a >500 people, conducted from year 2000+, used MDRD/CKD-EPI formula, reported CKD prevalence using KDOQI criteria and were in the general population (even if limited—e.g. aged >65). Studies were excluded if they had no criteria for diagnosis of CKD, did not include prevalence, were in a specialist restricted population (e.g. acute hospital patient cohort, nursing home), were an audit of existing results already included or if there was a more recent updated study. Translations were sought for non-English articles.

Data extraction was with standardised forms by two independent reviewers (NH, SF) disagreement was resolved by adjudicator (DL). Data included quality assessment, prevalence of CKD, method used to calculate eGFR, study setting: year, country, the population, gender split, age, and so on. Authors of relevant articles were contacted to provide additional information whenever necessary and references of selected articles were hand searched for additional articles. The KDOQI definition of CKD stages was used [ 11 ] and the method, calibration and traceability of the creatinine assessment extracted.

Statistical analysis and quality assessment

CKD prevalence was defined by the studies as being calculated for Stages 1 to 5 (eGFR & ACR) or Stages 3 to 5 (eGFR alone). 95% confidence intervals (95%CI) were calculated for each prevalence value. Meta-analyses were performed in Stata version 14. A procedure for pooling proportions in the meta-analysis of multiple studies study was used and the results displayed in a forest plot. The 95%CI’s are based on score(Wilson) procedures [ 23 ]. Heterogeneity was quantified using the I-squared measure, The I 2 heterogeneity was categorised as follows: <25% low, 25 to 50% moderate and >50% high [ 24 ]. A Freeman-Tukey Double Arcsine Transformation [ 25 ] was used to stabilise the variance prior to calculation of the pooled estimates. Random effects models were selected for the meta-analyses with the assumption that CKD prevalence by country would be variable.

Subgroup analysis was undertaken by country, geographic region, age and gender. Geographic regions were defined based on the geographic proximity of the country the studies occurred in and the possible similarity in the ethnicity of the populations. Meta-regression was weighted by number of subjects unless otherwise specified [ 24 ]. Random effects meta-regressions using aggregate level data for CKD prevalence, study year, participant characteristics and co-morbidities were performed.

Methodological quality was assessed by one reviewer (NH) defined as adherence to STROBE (Strengthening the Reporting of Observational Studies in Epidemiology Statement) recommendations. [ 26 ] The STROBE 22-point checklist was used to score each manuscript, items that had subdivision recommendations scored a point for each. Serum creatinine reporting quality was assessed by two reviews (NH & SF)—traceability of assay, number of measurements per patient, assay method used, and calibration of assay. A combined quality score was generated from methodological quality- as measured by STROBE adherence- and serum creatinine reporting quality. The weighting was arbitrarily chosen to be two-thirds STROBE adherence and one-third creatinine reporting. To assess bias, quality was used to weight CKD prevalence values in a meta-analysis.

Sensitivity analyses were undertaken to investigate the individual study influence and of limited populations (high altitude, single site of recruitment in rural area, single site of recruitment in urban area, laboratory audit, age by decile, or age restricted), studies that used age adjusted prevalence and using only high quality studies—quality score threshold of 56% (mean quality). Further sensitivity analyses were undertaken using studies that examined IDMS traceable creatinine only, studies that used double measuring of creatinine, studies that achieved two or more of the serum creatinine reporting quality items, and studies that used different eGFR equations (CKD-EPI or MDRD).

The search yielded 5,842 articles after duplicates had been removed and 143 articles were assessed relevant for the review by title and abstract. Forty-three were excluded on full manuscript assessment. A detailed review and data extraction was conducted on 100 manuscripts (covering 112 populations), Fig 1 . No additional studies were identified by examining reference lists. All studies that were included were published after the introduction of the KDOQI 2002 CKD definition guidelines [ 11 ].

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*112 Populations from 100 manuscripts as some manuscripts reported on more than one population or split their populations prior to analysis.

https://doi.org/10.1371/journal.pone.0158765.g001

China had the highest number of population samples with seventeen. [ 27 – 43 ] Numbers of participants ranged from 778 in a USA cohort [ 44 ] to 1,120,295 in a USA laboratory audit [ 2 ]. The S1 Appendix Study Table details the relevant details of all studies and populations.

The mean(95%CI) global prevalence of CKD was 13·4%(11·7–15·1%), I 2 = 99.9%, for the forty-four populations that measured prevalence by all 5 stages (1 to 5) [ 4 , 28 , 29 , 32 , 33 , 35 – 38 , 40 – 43 , 45 – 73 ], and 10·6%(9·2–12·2%),I 2 = 100%, in the sixty-eight populations [ 2 , 10 , 27 , 30 , 31 , 34 , 39 , 44 , 74 – 123 ] measuring Stages 3 to 5, Fig 2 .

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Studies are ordered by number of participants and split by whether the report 3 stages of CKD (“Three”) or five stages of CKD (“Five”).

https://doi.org/10.1371/journal.pone.0158765.g002

CKD prevalence breakdown was provided in seventy-four populations. [ 2 , 4 , 10 , 27 – 29 , 32 , 35 , 37 – 43 , 46 , 47 , 50 – 56 , 60 , 63 , 65 – 71 , 73 – 84 , 86 – 91 , 98 – 102 , 106 – 111 , 113 , 116 , 118 , 121 , 122 ] The 1 to 5 stages mean CKD prevalence was higher (13·4% vs. 11·0%). The breakdown by stage using all available data was Stage-1 (eGFR>90+ACR>30): 3·5%(2·8–4·2%); Stage-2 (eGFR 60–89+ACR>30): 3·9%(2·7–5·3%); Stage-3 (eGFR 30–59): 7·6%(6·4–8·9%); Stage-4 = (eGFR 29–15): 0·4%(0·3–0·5%); and Stage-5 (eGFR<15): 0·1%(0·1–0·1%). Separate reporting of Stage 3a/3b was not possible due to lack of reporting. Sensitivity analyses determined that no individual study or group of studies (limited populations—i.e. laboratory audits, age restricted, single site recruitment—, age adjusted prevalence, etc.) were suspected of excess influence on the prevalence estimates. Further, there was no difference between studies that reported using the higher quality IDMS traceable assay and those that did not.

Effect of Age, Hypertension, BMI, Obesity, Diabetes, Smoking.

Univariate meta-regressions of CKD prevalence and covariates were undertaken. Mean population age, given in 94 of 112 populations, was significantly associated (β = 0·4%, p<0·001, R 2 = 25·5), as was prevalence of diabetes (n = 82, β = 0·16%, p = 0·006, R 2 = 8·0), prevalence of hypertension (n = 75, β = 0·15%, p = 0·002, R 2 = 11·4) but not average BMI or prevalence of obesity. Smoking (n = 60) was negatively associated with CKD prevalence (an increase of smoking status was associated with a decreased prevalence of CKD (β = -0·14 p = 0·07, R 2 = 4·2).

Prevalence of CKD increased with age, Fig 3 . To determine an estimated prevalence for each age the sample population was divided by mean age into deciles. Studies measuring 5 stages of CKD mean(95%CI) were—30s: 13·7%(10·8, 16·6%), 40s: 12·0%(9·9, 14·1%), 50s: 16·0%(13·5, 18·4%), 60s: 27·6%(26·7, 28·5%), 70s: 34·3%(31·9, 36·7%). Studies measuring stages 3 to 5–30s: 8·9%(4·7, 13·1%), 40s: 8·7%(6·9, 10·5%), 50s: 12·2%(9·8, 14·5%), 60s: 11·3%(8·1, 14·5%), 70s: 27·9%(16·40, 39·3%).

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Each circle represents a study prevalence estimate with the size denoting the precision of the estimate.

https://doi.org/10.1371/journal.pone.0158765.g003

There were no significant differences in prevalence between groups of studies that adjusted for age compared to those that did not. Further, a sensitivity test found that older age restricted populations did not significantly change the estimated pooled prevalence for CKD, Stages 3 to 5 mean (95%CI) 10·2%(8·4–12·0%) vs. 10·6%(9·2–12·2%) and stages 1 to 5 mean (95%CI) 11·5%(9·3–13·9%) vs. 11·4%(9·4–13·1%). A sensitivity analysis examining glomerular filtration estimating equation was planned but only 12 studies used the CKD-EPI equation making the analysis unfeasible.

CKD prevalence by geographical grouping was examined, Table 1 . Geographical areas with more than one study were pooled using random effects models.

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https://doi.org/10.1371/journal.pone.0158765.t001

Fifty-one studies reported sex-specific prevalence of CKD. [ 27 – 29 , 32 , 37 – 39 , 44 , 46 , 48 , 50 , 52 – 55 , 57 , 58 , 61 , 64 , 68 – 71 , 78 , 79 , 82 , 83 , 85 , 87 , 92 – 94 , 98 , 100 – 103 , 105 , 106 , 108 , 110 , 115 , 119 ] Male mean (95%CI) CKD prevalence, for studies that defined 5 stages of CKD, was 12·8%(10·8–11·9%) and for studies that used stages 3 to 5 it was 8·1%(6·3–10·2%). Female CKD prevalence for studies that defined CKD by stages 1 to 5 was 14·6%(12·7–16·7%) and for studies that used stages 3 to 5 it was 12·1%(10·6–13·8%). Thirty-eight studies [ 27 – 29 , 32 , 37 – 39 , 44 , 46 , 50 , 55 , 64 , 69 – 71 , 78 , 79 , 83 , 85 , 87 , 92 , 98 , 100 – 103 , 105 , 106 , 108 , 110 , 115 , 119 ] reported that CKD was more prevalent in women than in men with the pattern reversed in thirteen studies. [ 39 , 44 , 48 , 52 – 54 , 57 , 58 , 61 , 68 , 82 , 93 , 94 ]

The methodological quality of studies ranged from 32·1% [ 31 ] to 92·9%. [ 4 , 68 ] No study complied completely with the STROBE guidelines and the mean(SD) quality was 69·6(12·5)%.

Quality of serum creatinine measurement was assessed. Two studies scored 100%- four methods. [ 115 , 122 ] Thirty-six studies scored 0% [ 30 – 32 , 34 , 39 , 40 , 48 , 49 , 52 , 57 – 60 , 62 , 64 , 71 , 72 , 74 , 76 , 81 , 82 , 85 , 87 , 89 , 92 , 95 , 102 , 103 , 105 , 106 , 109 , 113 , 116 , 117 ], thirty-five studies scored 25%-one method-[ 2 , 28 , 29 , 33 , 35 – 38 , 41 , 43 , 47 , 51 , 53 , 61 , 65 , 67 – 70 , 75 , 77 – 79 , 83 , 84 , 97 – 100 , 108 , 110 , 114 , 121 ], twenty-seven scored 50%-two methods-[ 4 , 27 , 42 , 44 , 46 , 50 , 54 – 56 , 66 , 74 , 80 , 88 , 90 , 101 , 104 , 107 , 111 , 112 , 118 , 119 , 123 ] and ten scored 75%-three methods. [ 10 , 45 , 63 , 73 , 86 , 91 , 93 , 94 , 96 , 120 ]

Sensitivity analyses determined no difference in the prevalence estimate of CKD when using only high quality studies, studies that used double measures of creatinine only or studies that had two or more factors for the measurement of creatinine.

CKD prevalence Stages 1 to 5 was 13·4% and 10·6% in stages 3 to 5. This systematic review is the first meta-analysis of CKD prevalence globally and provides a comprehensive overview of the current literature. These estimates indicate that CKD may be more common than diabetes, which has an estimated prevalence of 8·2%. [ 124 ] However, the reported prevalence of CKD varied widely amongst the studies and had high heterogeneity.

CKD was more prevalent in women than in men. Two-thirds of studies -that reported gender-specific CKD prevalence- determined higher prevalence in women. Women, in general, have less muscle mass than men and muscle mass is a major determinant of serum creatinine concentration. However, the GFR estimation equations adjust for gender differences, using a correction factor for women. These findings add to the existing literature that recognise a gender-specific difference between CKD prevalence. [ 125 – 127 ]However, these data cannot answer why this may occur. We can speculate that this finding may be partially explained by selection bias inherent within the studies due to a different age demographic for the two sexes. Alternatively it may be due to complex factors in the disease pathology that are not captured within the studies. Or that there is in fact more renal disease in men but the eGFR equations preferentially identify renal disease in women in the stage 3 zones.

Studies that were outliers in terms of reported results were of interest. Smoking was found to be negatively associated with CKD prevalence but this finding was negated when a single outlier was removed. The outlier [ 120 ] was a study in which smoking was defined as >100 cigarettes ever and thus 69·1% were smokers. A Spanish study [ 106 ] (n: 7202, Quality: 52%, CKD: 21·3%) reported 66.7% hypertension prevalence within the population compared with a global mean (from all other studies) of 31·1%. Hypertension was not defined any differently. Further, 31.5% of their sample population had diabetes and 31.1% were obese. The population was reported as unrestricted older population but although it was older than other studies (mean age 60·6yrs) these rates of co-morbidity are unexpected and were not explained. A number of studies had very high prevalence of CKD (>30%) the highest of these was a Canadian study (n: 123,499, Quality: 52%, CKD: 36·4%), a laboratory audit of patients over 65 years. The prevalence observed may be due to selection bias as the mean age of this cohort was 74 years, with 23% diabetes in the sample population, two factors associated with renal decline.

The geographical stratification of results revealed that developed areas such as Europe, USA, Canada and Australia had higher rates of CKD prevalence in comparison to areas where economies are growing such as sub Saharan Africa, India etc. With the exception of Iran that had similar high level of CKD prevalence possibly due dietary risks, high BMI, high systolic BP and co-morbid conditions within the country [ 128 ]. Although percentage prevalence was higher in more developed areas projected worldwide population changes will increase the absolute numbers of people in developing countries where the populations of elderly are increasing. This increase will exacerbate the double burden of dealing with communicable and non communicable disease in a developing economy[ 129 ].

Serum creatinine measurement bias was inherent in the majority of the studies. Serum creatinine concentrations are highly variable within individuals, up to 21% within a 2-week period. [ 130 ] NICE guidelines advise two measures of eGFR 3-months apart and within the last 12-months to minimise intra-individual variation. Not all countries have such guidelines only 5 manuscripts reported this in study design. Jaffe creatinine assay was the main method used but it is known to systematically overestimate serum creatinine to varying degrees. [ 131 ] Thirty-seven of the studied populations reported that they calibrated directly to the laboratory to minimize assay bias effect and twenty-seven studies used a minimally biased traceably assay (IDMS). A comparison of these studies to the remainder found no significant difference in prevalence estimates. A third of the studies (n = 36) made no mention of measures, traceability, or calibrations. It is further known that the MDRD equation systematically overestimates CKD in the general population [ 13 ] and the prevalence rates calculated may be lower. Estimated GFR is accepted as the most useful index of kidney function in health and disease, but an uncorrected, untraceable single measure inherently introduces noise and outliers into the dataset. This latter point has been very recently clarified as an epidemiological study in Morocco found that up to 30% of patients initially classified as CKD 3a using the MDRD formula had improved renal function over 12 months and therefore would not have a CKD diagnosis[ 132 ].

Estimation of GFR from serum creatinine is the clinical standard worldwide and the CKD the KDOQI diagnostic criteria[ 11 ] guidelines emphasise the importance of estimation of GFR rather than use of serum creatinine concentration. However, the 2002 KDOQI guidelines that the included studies reference have stimulated controversies and questions. In particular, there have been concerns that use of its definition of CKD has caused excessive false identification of CKD and that its staging system was not sufficiently informative about prognosis. A new KDIGO guideline was published in 2013 [ 133 ] that sought to address this with the splitting of the stage 3 category to emphasise the risks of mortality and other outcomes vary greatly between these groups and have further and further sub-stratified by the inclusion of urinary albuminuria. There is a limitation in our study in that unfortunately the analysis of stages 3a and 3b was not possible due to lack of reporting and studies using the previous KDOQI guidelines so no conclusions about whether the patients really have ‘disease’ rather than normal variation due to aging could be drawn.

Observational studies are individually subject to bias and residual confounding from unspecified sources but it is difficult to quantify how much bias and/or confounding. One study may report an effect size adjusted for several possible confounders; others may report the crude prevalence. The authors have sought to address this limitation by using STROBE quality weighting and creatinine quality factors and participant per study-weighted rates. Ideally future research should report the crude and adjusted rates based on multiple measures over time.

This systematic review and meta-analysis significantly extends existing systematic reviews in a number of ways. The search strategy allowed the detection of a large number of additional studies that had not been considered in previous systematic reviews. It increased the number of reference databases searched. The reviewers undertook to screen non-English publications through the use of translations. The studies included used the same definitions of CKD and used broadly comparable definitions for severity markers or related conditions (albuminuria, hypertension, diabetes and obesity). However, there are limitations due to the heterogeneity that arises from differences in age and sex distributions, use of creatinine assays, different sampling frames, inclusion criteria of general population based studies, and time period of the study. A proportion of the variation across studies may not be due to real differences in CKD prevalence. However, the authors did seek to provide a robust assessment of the quality and use this to determine a weighted global prevalence of CKD in the meta-analysis. The prevalence rates calculated highlight the likely numbers of people with CKD that may be of relevance to health care providers and national health programs with finite resources with which to address this epidemic.

CKD constitutes a major cost burden to healthcare systems worldwide. The high prevalence and the extensive existing evidence that intervention is effective in reducing CVD events demonstrates a need for national initiatives that will slow the progression to end stage renal disease and reduce CVD-related events in CKD patients.

This comprehensive meta-analysis of observational studies confirms that CKD has a high prevalence. Using CKD prevalence weighted by quality, using ‘High’ quality studies only and using studies weighted by number of participants consistently estimated a global CKD prevalence of between 11 to 13%. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes. Evaluation of the roles of these interventions and the associated costs needs to be undertaken. CKD prevalence studies should report more detail on disease definitions and population demographics and state unadjusted as well as adjusted findings.

Supporting Information

S1 appendix. study table—summary descriptions of included studies (n = 100) and the populations (n = 112) within those studies..

https://doi.org/10.1371/journal.pone.0158765.s001

S2 Appendix. PRISMA Checklist—Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist.

https://doi.org/10.1371/journal.pone.0158765.s002

Acknowledgments

We wish to thank Ms. Nia Roberts for her extensive assistance in conducting the search and Dr Yaling Yang for her translation of a Chinese language manuscript. Systematic Review Registration: PROSPERO CRD42014009184.

Author Contributions

Conceived and designed the experiments: NH DL FDRH. Performed the experiments: SF NH DL COC FDRH. Analyzed the data: NH SF JO JH. Wrote the paper: NH SF COC JO JH DL FDRH.

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  • Published: 08 July 2024

Treatment of chronic kidney disease in older populations

  • Seiji Kishi   ORCID: orcid.org/0000-0001-6205-1661 1 ,
  • Hiroyuki Kadoya 2 &
  • Naoki Kashihara   ORCID: orcid.org/0000-0002-9487-984X 3 , 4  

Nature Reviews Nephrology ( 2024 ) Cite this article

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  • Chronic kidney disease

As the world population ages, an expected increase in the prevalence of chronic kidney disease (CKD) among older individuals will pose a considerable challenge for health care systems in terms of resource allocation for disease management. Treatment strategies for older patients with CKD should ideally align with those applied to the general population, focusing on minimizing cardiovascular events and reducing the risk of progression to kidney failure. Emerging therapies, such as SGLT-2 inhibitors and GLP-1 receptor agonists, hold promise for the effective management of CKD in older individuals. In addition, non-pharmacological interventions such as nutritional and exercise therapies have a crucial role. These interventions enhance the effects of pharmacotherapy and, importantly, contribute to the maintenance of cognitive function and overall quality of life. Various factors beyond age and cognitive function must be taken into account when considering kidney replacement therapy for patients with kidney failure. Importantly, all treatment options, including dialysis, transplantation and conservative management approaches, should be tailored to the individual through patient-centred decision-making. The dynamic integration of digital technologies into medical practice has the potential to transform the management of CKD in the aging population.

Aging is an important risk factor for chronic kidney disease (CKD); the expected increase in CKD prevalence with the aging population will likely pose a challenge to health care systems in terms of resource allocation and strategies for effective disease management.

Structural and functional changes that occur in the kidney with aging are associated with a decline in kidney function from around 40 years of age; although these changes vary considerably between individuals, diseases such as hypertension and diabetes accelerate this decline.

Older patients with CKD should be treated the same way as other members of the general population, with the goal of minimizing cardiovascular events and slowing progression to kidney failure; available evidence suggests that SGLT-2 inhibitors and GLP-1 receptor agonists may be effective in older populations and associated with a low risk of adverse events.

Nutritional and exercise therapies are essential non-pharmacological treatments for older patients with CKD; these therapies not only enhance the effects of pharmacotherapies but may also help to maintain cognitive function and quality of life.

Choice of kidney replacement therapy for patients with kidney failure should not solely depend on age or cognitive function; alongside dialysis and transplantation, conservative treatment options, including conservative kidney management, should be considered through patient-centred decision making.

Digital technologies using wearable devices and virtual reality systems are expected to facilitate the treatment of CKD in older populations.

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Seiji Kishi

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Hiroyuki Kadoya

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Naoki Kashihara

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systematic literature review chronic kidney disease

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Health related quality of life utility weights for economic evaluation through different stages of chronic kidney disease: a systematic literature review

  • Jacie T. Cooper 1 ,
  • Andrew Lloyd   ORCID: orcid.org/0000-0002-7597-6556 2 ,
  • Juan Jose Garcia Sanchez   ORCID: orcid.org/0000-0001-6546-7769 3 ,
  • Elisabeth Sörstadius 4 ,
  • Andrew Briggs 1 , 5 &
  • Phil McFarlane 6  

Health and Quality of Life Outcomes volume  18 , Article number:  310 ( 2020 ) Cite this article

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A Task Force from the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) provides recommendations on how to systematically identify and appraise health state utility (HSU) weights for cost-effectiveness analyses. We applied these recommendations to conduct a systematic review (SR) to identify HSU weights for different stages of chronic kidney disease (CKD), renal replacement therapy (RRT) and complications.

MEDLINE® and Embase were searched for interventional and non-interventional studies reporting HSU weights for patients with CKD stages 1–5 or RRT. As per ISPOR Task Force Guidance, study quality criteria, applicability for Health Technology Assessment (HTA) and generalisability to a broad CKD population were used to grade studies as either 1 (recommended), 2 (to be considered if there are no data from grade 1 studies) or 3 (not recommended).

A total of 17 grade 1 studies were included in this SR with 51 to 1767 participants, conducted in the UK, USA, Canada, China, Spain, and multiple-countries. Health related quality of life (HRQL) instruments used in the studies included were EQ-5D-3L (10 studies), SF-6D (4 studies), HUI2/HUI3 (1 study), and combinations (2 studies). Although absolute values for HSU weights varied among instruments, HSU weights decreased with CKD severity in a consistent manner across all instruments.

Conclusions

This SR identified HSU weights for a range of CKD states and showed that HRQL decreases with CKD progression. Data were available to inform cost-effectiveness analysis in CKD in a number of geographies using instruments acceptable by HTA agencies.

Chronic kidney disease (CKD) has a substantial impact on patients’ health and life expectancy. CKD has been estimated to affect between 10 and 15% of the population in the U.S. and Canada [ 1 , 2 ]. CKD can be a progressive disease and the leading causes include diabetes (38%), high blood pressure (26%), and glomerulonephritis (16%) [ 3 ]. Progression to end-stage renal disease (ESRD) leaves the patients reliant on dialysis or a kidney transplant [ 4 ]. CKD also leads to substantial healthcare resource use. The total Medicare spending on both CKD and ESRD was over $114 billion in 2016 [ 5 ].

The KDIGO (Kidney Disease: Improving Global Outcomes) 2012 guidelines recommended that CKD patients should be categorised based on cause, glomerular filtration rate (GFR) category, and albuminuria category in order to aid in predicting CKD prognosis.

Despite guideline directed management of risk factors and use of renin angiotensin aldosterone system inhibitors (RAASi), disease progression, adverse clinical outcomes and mortality rates remain high in patients with CKD, particularly in those patients at risk such as those with moderately or severely increased albuminuria, highlighting a clinical need for new treatments to delay renal disease progression and improve health related quality of life (HRQL).

Since the introduction of health technology assessment (HTA) agencies across the world, the decision to adopt new treatments is becoming more frequently based on the results of cost-effectiveness analyses. The cost-effectiveness of new treatments is influenced by HRQL weights (referred to as health state utility [HSU] weights). HSU weights range between 0 and 1, with 1 representing the valuation of perfect health and 0 representing the valuation of death and are used to estimate quality adjusted life years (QALYs). A systematic review (SR) reported that most cost-effectiveness models in CKD utilised a framework based on disease progression defined by a worsening in GFR stage or albuminuria category [ 6 ].

A Task Force from the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) led by Brazier and colleagues (2019) provided recommendations on how to systematically identify and appraise HSU weights for cost-effectiveness analysis. The recommendations were divided into four sections which describe: (1) iterative search strategy; (2) review process to include studies based on inclusion criteria and data quality; (3) data to be extracted from each study; (4) basis for selecting HSUs to inform a cost-effectiveness analysis (e.g. data availability for a country of interest or data availability using a specific instrument) (Fig.  1 ).

figure 1

Brazier (2019) HSU identification and selection process. Abbreviations: HSU, health state utility

The impact of dialysis and renal transplantation on HSU weights has been reported in previous SRs, however, it remains uncertain how the magnitude of HSU weights change as CKD progresses between stages 1 and 5 [ 7 , 8 , 9 , 10 , 11 ].

The aim of this SR was to identify HSU weights to inform cost-effectiveness modelling in CKD applying current best practices, and the review was conducted to provide an international perspective.

Search strategy

This SR was based on a prespecified protocol and conducted in accordance with the standards prescribed by the ISPOR Task Force (but also reflects best practice at the Centre for Reviews and Dissemination, National Institute for Health and Care Excellence (NICE), and the Cochrane Collaboration) [ 12 , 13 , 14 , 15 ]. The search was conducted in both MEDLINE (PubMed) and Embase (OVID) in August 2019. The full search strategy is provided in Additional file  1 . Grey literature searches included conference proceedings of three major nephrology congresses and one health economics congress held between 2017 and 2019, and reports from four major HTA agencies (Additional file  2 ). The bibliographies of relevant published SRs and cost-effectiveness analyses were hand-searched to find additional articles that were not identified in the electronic database searches.

Two independent reviewers (JC, JGS) screened the title and abstract of each record (stage 1), as well as the full texts of all potentially eligible records identified in stage 1 (stage 2). A third independent reviewer (AL) resolved any disagreements.

Study inclusion criteria are shown in Table  1 and are based on the PICOS (population, intervention, comparator, outcome, study) framework.

Critical appraisal

Each study was assessed against the following criteria:

The study was conducted in a CKD population

The study reports original empirical HSU weights

Data were collected using a generic HRQL measure (i.e. EQ-5D, short-form 6-dimention [SF-6D] or a mappable equivalent such as short-form 36 [SF-36] or short-form 12 [SF-12]; or the Health Utility Index [HUI])

The study sample size was at least 25 patients

The study was conducted in a country of interest (i.e., USA, Canada, Australia, China, UK, Spain, Italy, France or Germany)

HSU weights were presented in a comprehensive way that is useful to inform cost-effectiveness analysis (e.g. HSU weights were available by CKD stage)

To weigh both data quality and data appropriateness as recommended by Brazier and colleagues (2019), each study that met the critical appraisal at stage 1 was then reviewed in full in stage 2 and graded from 1 to 3 with consideration to the presence of bias, alignment with HTA criteria, and general compliance with our initial selection criteria (Table  2 ). To assess bias, each study’s methodology was examined for selection bias, bias in data analysis or interpretation, drop out or missing data, or bias in study execution such as unblinding in randomised control trials.

Grade 1 studies were considered most appropriate for HTA. If data for a specific health state was not available using Grade 1 studies, then, Grade 2 studies would be reviewed to identify a missing value following the iterative approach recommended by Brazier and colleagues (2019). Grade 3 studies were considered to be inappropriate.

Relevant data, as recommended by Brazier and colleagues (2019), was extracted from the included studies into a prespecified extraction grid.

Electronic database searches identified 1091 records. After title/abstract screening, 150 studies were selected for full-text review, of which 52 met the final inclusion criteria. The grey literature identified 83 studies, although no new studies met our inclusion criteria (Additional file 2 ). The article selection process is displayed in Fig.  2 .

figure 2

PRISMA Diagram. Abbreviations: CKD, chronic kidney disease; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Of the 52 included studies, the grading process identified 17 Grade 1, 30 Grade 2, and 5 Grade 3 studies (Additional file  3 ). Data were extracted for the Grade 1 studies (Additional file  4 ). Fourteen of the studies reported more than one CKD HSU weight, resulting in a total of 58 CKD HRQL estimates across different health states (i.e., CKD stages, haemodialysis (HD), peritoneal dialysis (PD) and renal transplant (Trx)).

Ten studies (59%) used the EQ-5D-3L, four (24%) used the SF-6D, one (6%) used the HUI3, and two (12%) used multiple instruments (HUI2 and HUI3; EQ-5D-3L and HUI3). Of the reported HSU weights, 18 (41%) described dialysis patients, 17 (39%) described transplant patients, and 9 (21%) described cohorts by CKD stages. Studies were reported from Canada ( n  = 4; 29%), the UK ( n  = 3; 18%), the US ( n  = 3; 28%), Spain ( n  = 2; 12%), and China ( n  = 2; 12%), and two studies (12%) were multinational. A summary of key study characteristics is reported in Table  3 .

HSU weights for the different CKD health states are reported in Table  4 . HRQLs for haemodialysis and post-transplant patients were the most common. There is a scarcity of data describing HRQL for patients in CKD stages 1–5; only one study was identified that reported an HSU value for stage 2 patients and no studies reported HSUs for stage 1 patients.

Four longitudinal studies reported HSU weights. Limited data were available describing HRQL changes with disease progression. Regarding HRQL in patients undergoing RRT, HSU weights increased with time (Table  5 ).

Mean weighted HSU weights for the different CKD health states according to instrument are reported in Fig.  3 . There is clear variation in utility values across instruments. However, there is an overall consistent trend with each instrument showing a reduction in HRQL with CKD progression. HRQL is lowest with dialysis. HSU weights reported using SF-6D indicate no difference between haemodialysis and peritoneal dialysis while HSU weights are lower for peritoneal dialysis when using EQ-5D-3L. HRQL increases after renal transplantation.

figure 3

Mean HSU weights by state presented by instrument. HSU values are weighted averages calculated using subgroup population sizes; Error bars represent standard error. Abbreviations: CKD, chronic kidney disease; HSU, health state utility; HUI2, Health Utilities Index Mark 2; HUI3, Health Utilities Index Mark 3; SF-6D, Short Form questionnaire-6 Dimensions

Only one study identified in our SR reported the impact of adverse events or complications on CKD patients on dialysis [ 18 ]. The HSU weights reported are shown in Table  6 . No studies reported the impact of adverse events or complications on patients with CKD stage 1–5 or after a renal transplant.

Study quality is reported in Additional file  5 . Since all analysed studies met our grade 1 screening requirements, overall study quality was high. Quality assessment reported a lack of clarity in 7 studies regarding drop out or missing data rates. Lee et al. reported a low 33% response rate but was retained due to the questionnaire administration method (survey packets were mailed to patients’ houses) [ 19 ].

This SR was designed to identify HSU weights for a range of CKD health states using methods promoted by Brazier and colleagues (2019) and other best guidance available. To our understanding, this is the first SR to report HSU weights for CKD stages 2–5, as well as RRT, as previous SRs focused on RRT only [ 7 , 10 , 33 , 34 , 35 , 36 , 37 ].

The review identified a large number of published studies that reported HSU weights for CKD populations. By focusing to the most generalisable and reliable Grade 1 studies, we hope to present the most accurate summary of HSU weights in CKD.

This is also the first SR to have been undertaken in the area of HSU weights since the Brazier and colleagues (2019) guidance on SR methods for the identification of HSU weights for cost-effectiveness analysis was released [ 12 ]. Based on our experience of implementing the guidance, we found that the recommended approach worked well and the guidance provided a very good rationale and set of methods for identifying the most relevant data.

According to the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices, conducting a meta-analysis on this topic may have been appropriate. However, the Brazier and colleagues (2019) guidance for identification of HSU weights in particular does not specify the need for this type of analysis. We believe this SR more directly addresses the needs of decision-making entities in different countries, as ideal data for decision-making would be country-specific with a relevant presence of comorbidities, settings, HSU instruments, and date-of-publication ranges - entities that may be lost in meta-analysis.

The review found an overall trend across studies for a decline in HSU scores as CKD deteriorated, (based on GFR). This fits with clinical expectation, but it is a point worth making because we believe that it provides some justification or validation of the identified HSU weights. Different factors may affect HRQL decline at different CKD stages. For instance, reductions in HRQL in early CKD stages may be driven by the presence of comorbidities such as diabetes, while a decline in HRQL in more advanced CKD stages may also be driven by an increase in the incidence of heart failure, and cardiovascular complications such as myocardial infarction or stroke which could also have a substantial impact on HRQL [ 38 , 39 , 40 , 41 ]. However, it is difficult to determine the cause of any decline in HRQL when exploring published data because we are limited to the data that have been included in the publication. This is one important limitation of the published data and of this SR. The studies included varied in terms of their design (cross-sectional survey, randomised trial, prospective observational study) and used different instruments which made comparisons between them challenging. Although a similar declining trend was observed with CKD progression across instruments, absolute HSU values were different across instruments with EQ-5D-3L reporting the highest values. This could reflect that sensitivity to capture the impact of CKD progression on HRQL may be different between the instruments reported in this systematic review. This could also present a challenge when estimating QALYs gained in cost-effectiveness analyses of new treatments for CKD. As a consequence, incremental cost-effectiveness ratios could be different depending on the instrument used and, potentially, this could result in different recommendations for the adoption of new treatments for CKD by HTA agencies. Variability in HSU weights between instruments remains a source of bias when combining results from studies using different instruments. This could be avoided by only including studies which use one specific instrument. While the number of patients assessed differed substantially between studies, by HSU instruments used and CKD stages, this did not seem to influence HSUs reported as they seemed aligned for each instrument and CKD stage regardless of sample size. While HSU weights were lowest for dialysis, it was not clear if HSU differs between haemodialysis and peritoneal dialysis as different trends were noted between the instruments used. Further research should be conducted to increased the understanding of these differences.

A number of aspects may affect the mix of patients included in the studies reported in this SR and, therefore, the eventual HSU weights reported. For example, patients receiving in-centre dialysis may have more comorbidities and complications than patients that are good candidates for peritoneal dialysis, dialysis at home or nocturnal dialysis. Patients with less severe kidney disease or higher HRQL may also be more likely to respond to voluntary questionnaires or participate in trials, potentially skewing the data. Further, it is possible that geographical variations may arise due to differences in clinical practice but also how people interpret HRQL questionnaires.

Regression methods such as those applied by Briggs and colleagues (2012) provide a way to estimate HSUs from longitudinal studies for different CKD stages improving the precision of the effects and understand their origin. Regression analyses of large datasets allow us to understand the impact of CKD related events on HRQL as well as understanding the influence of covariates and so this offers advantages over SR methods. It may also be possible to explore some of these issues with meta-regression type techniques. However, the studies are not consistent in the information that they present which makes it difficult to compare these variables systematically. Alternatively, it could be assumed that a ‘true’ score for a specific health state lies within the range of scores that have been identified from the review for a specific health state. Therefore, cost-effectiveness analysis could be informed by the range of scores as opposed to a single point estimate.

All studies used generic instruments of health rather than disease-specific instruments, but despite this the HSU weight varied substantially between different instruments (Fig. 3 ). This figure showed that the HUI3 questionnaire produces lower HRQL scores in comparison to the SF-6D and EQ-5D-3L. Higher HSU weights were reported with the SF-6D. SF-6D values for dialysis patients in particular, (0.76, and 0.78 for haemodialysis and peritoneal dialysis, respectively) seemed high considering that these applied to patients receiving dialysis. If the measures are not in agreement, then this could be explored (and perhaps controlled for) using a meta-regression approach. Where possible, HSU weights used in a cost-effectiveness analysis could be limited to a single instrument relevant to the specific research question for a cost-effectiveness analysis such as the EQ-5D-3L for cost-effectiveness analyses submitted to NICE in England.

In 2012, KDIGO provided guidelines for the categorisation of patients according to GFR and albuminuria [ 42 ]. Our SR did not find any studies that reported HSU weights based on both GFR and albuminuria or albuminuria alone. A data gap exists to understand the impact of albuminuria on HRQL. Additional data gaps exist around the reporting of HSUs related to CKD stage 1, adverse events and complications in patients with CKD.

To our knowledge, this is the first SR examining HSU scores for patients with CKD stages 1–5 with stratification by CKD stage. This is also one of the first reviews to apply the Brazier and colleagues (2019) guidance. There were sufficient data to provide weighted mean HSU weights for most CKD stages of interest [ 2 , 3 , 4 , 5 ] and RRT. No data was found reporting HSUs weights according to the KDIGO 2012 GFR/albuminuria categories. The findings from the SR illustrate how HRQL is worse for patients with worse renal function. Although similar trends were seen, notable differences in absolute values were identified across instruments highlighting potential differences in sensitivity to capture changes in HRQL in patients with CKD. This could result in the estimation of different QALYs gained in cost-effectiveness models and could affect the recommendation to adopt new treatments for CKD by HTA agencies. Regression methods are an option to provide refined HSU values from longitudinal studies while meta-analytical methods could help explore differences when using aggregate data.

Availability of data and materials

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Abbreviations

Chronic kidney disease

End-stage renal disease

Glomerular filtration rate

Haemodialysis

Health related quality of life

Health state utility

Health technology assessment

Health utility index

Health Utilities Index Mark 2

Health Utilities Index Mark 3

Immunoglobulin A

International Society of Pharmacoeconomics and Outcomes Research

Kidney Disease: Improving Global Outcomes

National Institute for Health and Care Excellence

Not reported

Peritoneal dialysis

Quality adjusted life year

Renin angiotensin aldosterone system inhibitors

Renal replacement therapy

Standard deviation

Short-form 12

Short-form 36

Short-form questionnaire-6 dimensions

Systematic review

Type 2 diabetes

Renal transplant

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Acknowledgements

This study was sponsored by AstraZeneca plc. Support for third-party writing assistance for this article, provided by Acaster Lloyd, was funded by AstraZeneca plc in accordance with Good Publication Practice (GPP3) guidelines ( http://www.ismpp.org/gpp3 ).

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Contributions

Substantial contributions to study conception and design: JC, AL, AB, JJGS, ES; substantial contributions to analysis and interpretation of the data: JC, AL, AB, JJGS, ES, PM; drafting the article or revising it critically for important intellectual content: JC, AL, AB, JJGS, ES, PM; final approval of the version of the article to be published: JC, AL, AB, JJGS, ES, PM.

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Correspondence to Juan Jose Garcia Sanchez .

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The study was funded by AstraZeneca plc. Support for third-party writing assistance, provided by Acaster Lloyd Consulting Ltd., was funded by AstraZeneca plc in accordance with Good Publication Practice (GPP3) guidelines. Disclosures for all authors are as follows:

• AL: Employee of Acaster Lloyd Consulting

• JC, AB: Employees of Avalon Health Economics

• JJGS, ES: Employees of AstraZeneca

• PM: Consultancy and research support from AMGEN, Astra-Zeneca, Bayer, Boehringer Ingelheim, Ilanga, Janssen, Lilly, Novartis, Otsuka, Pfizer, Sanofi-Aventis, and Takeda, as well as research support from AMGEN, Astra-Zeneca, Bayer, Boehringer Ingelheim, GSK, Janssen, Novartis, Novo-Nordisk, Ortho-Biotech, Otsuka, and Reata.

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Supplementary information

Additional file 1..

Search Strategy. PubMed search results.

Additional file 2.

Grey Literature Search. Grey literature search results.

Additional file 3.

Full Text Screening. Full text screening results with decision, HTA compatibility, bias assessment, and grade.

Additional file 4.

HSU weights from studies identified in SLR. Author and year, HRQOL Elicitation and scoring methods, subgroups, and mean utility scores for each grade one study identified in the SLR.

Additional file 5.

Quality Assessment. Bias assessment using a traffic light grading system of grade one studies identified in SLR.

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Cooper, J., Lloyd, A., Sanchez, J.J.G. et al. Health related quality of life utility weights for economic evaluation through different stages of chronic kidney disease: a systematic literature review. Health Qual Life Outcomes 18 , 310 (2020). https://doi.org/10.1186/s12955-020-01559-x

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Publication

Targeted Literature Review of the Burden of Illness in Patients With Chronic Kidney Disease and Type 2 Diabetes

Objectives: Chronic kidney disease (CKD) is increasingly prevalent among patients with type 2 diabetes (T2D). CKD is associated with increased mortality rates, clinical and humanistic burden, and substantial health care costs in the T2D population. The objective of this review was to summarize the burden of illness among patients with CKD and T2D, including the profile of patients, incidence, prevalence, mortality, progression, diagnosis and screening rates, and cardiovascular (CV) events.

Methods: A targeted literature review of published studies was conducted using Embase; Medline; Medline In-Process Citations, Daily Update, and Epub Ahead of Print; Igaku Chuo Zasshi databases; and 7 websites. Methods recommended by the Cochrane collaboration handbook, the Centre for Reviews and Dissemination, and the Joanna Briggs Institute critical appraisal checklist were employed.

Results: A total of 1290 full-text articles were reviewed for eligibility and 73 were included in this analysis. Patient profiles indicated older age was associated with more severe disease and number of comorbidities. The definition of kidney disease varied between studies reporting incidence and prevalence, with reported values up to 37.0% and 43.5% for incidence and prevalence, respectively. CKD among patients with T2D contributed to higher mortality rates. Higher disease progression rates were associated with higher albuminuria and lower estimated glomerular filtration rate levels. The available literature suggested annual screening rates for CKD declined over time. CV events were reported to have a substantial effect on morbidity and resource use.

Conclusions: This review highlights the burden of CKD among patients with T2D and underscores a need for new treatment alternatives to reduce the burden of disease.

Am J Manag Care . 2021;27(suppl 8):S168-S177. https://doi.org/10.37765/ajmc.2021.88660

For author information and disclosures, see end of text

Introduction

The Kidney Disease Improving Global Outcomes 2011 reportdefines chronic kidney disease (CKD) as an estimated glomerular filtration rate (eGFR) below 60 mL/min/1.73m 2 or a urinary albumin to creatinine ratio (UACR) of greater than 30mg/g. 1 As the disease progresses, persistent albuminuria, hypertension, and deterioration of renal function are observed. CKD can be classified based on level of kidney function, or eGFR, and the amount of protein in the urine. The lower the eGFR level (G1-G5) and the higher the albuminuria (A1-A3), the more severe the disease. Therefore, CKD is characterized by a gradual loss of kidney function and the frequent cooccurrence of other complications, including cardiovascular (CV) events, kidney failure requiring renal replacement therapy, mortality, and poor quality of life for survivors. 2,3

Kidney damage from diabetes is also called diabetic kidney disease (DKD) or diabetic nephropathy. 4 CKD is among the most severe complications of type 2 diabetes (T2D), making up the most significant contribution to the global CKD burden, with a heavy weight on the Western world.5 CKD occurs in 20% to 40% of patients with diabetes, and it can progress to end-stage renal disease (ESRD) that requires dialysis or kidney transplantation. 6 Approximately 85% to 95% of all cases of diabetes are T2D, and diabetic nephropathy is the most frequent cause of ESRD in most countries. 4 Moreover, among patients with diabetes, the presence of CKD markedly increases CV disease (CVD) risk.

Currently, treatment strategies focus on treating the underlying cause of kidney disease, controlling blood pressure, preventing CVD, slowing the progression of renal disease, and preventing death, creating an accumulation of patients with mid- to late-stage disease. 7 Antihypertensive treatments that target the renin-angiotensin-aldosterone system (RAAS), such as angiotensin-converting-enzyme inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs), have been shown to reduce proteinuria and delay disease progression. 8-10

The current standard of care in the treatment of patients with CKD and T2D includes RAAS blockers; namely, ACEIs and ARBs in patients with hypertension and albuminuria, 3,6 as well as sodium-glucose cotransporter-2 inhibitors, which are emerging treatment options based on results from recent clinical trials. 11,12

Medical costs associated with CKD in T2D increase substantially as the disease progresses to a more severe stage. 13 In 2017, total CKD in T2D-related expenditures in the US Medicare population were approximately $21.5 billion. 14 Analysis of data collected in 2012 to 2017 revealed that patients with T2D and CKD at stage 4 or 5 had substantially higher medical costs compared with those with earlier stages of CKD. Each 1 mL/min/1.73m 2 lower eGFR (starting from 30 mL/min/1.73m 2 ) was associated with an increase of $1870 in all-cause total medical costs and $1805 of all-cause nondrug medical costs per patient. 13 Data from 2016 and 2017 showed that annual mean medical costs per patient grew exponentially with increasing stages of CKD across all subgroups of patients with different comorbidities. 15

In addition to the substantial economic burden, patients with CKD and T2D have a high burden of disease and remain at a high risk of associated complications. The objective of this review is to summarize the evidence available from studies that report the burden of illness among patients with CKD and T2D. This literature review aimed to present the evidence on the profile of patients, incidence, prevalence, mortality, progression, diagnosis and screening rates, and CV events among the specified populations.

There is no defined standard or accepted methodology for conducting a targeted literature review; therefore, the initial stages of this review (ie, literature searching study selection, data extraction, and risk of bias assessment) followed methods recommended by the Cochrane collaboration handbook 16 and the Centre for Reviews and Dissemination 17 to reduce the risk of bias and errors.

The search was performed in Embase, Medline, Medline In-Process Citations, Daily Update and Epub Ahead of Print, and Igaku Chuo Zasshi databases. Additionally, websites of the National Health Service, National Institute for Clinical Excellence, Guidelines International Network, National Guidelines Clearinghouse, FDA, European Medicines Agency, and Haute Autorité de santéwere searched. Abstracts and full texts were screened by 2 independent reviewers to select relevant articles based on the inclusion criteria.

The review focused on the largest studies and the most recently published study results at the time of the literature review (March 2021). Studies were selected to cover all countries of interest (Canada, China, France, Germany, Italy, Japan, Spain, United Kingdom [UK], and United States). Studies with limited applicability due to highly selected population (eg, veterans; a single sex) and studies reporting minimal data were also excluded.

Data from included studies were extracted using templates created in Excel. One reviewer extracted the data while another validated the accuracy of the extracted information. A quality assessment was undertaken by using the Joanna Briggs Institute critical appraisal checklist for studies reporting prevalence data. 18

After removing duplicate studies, 20,878 records were identified, which were subjected to title and abstract screening. Of these, 1290 were selected to be checked at the full-paper stage. After the full-paper screening, 1217 additional records were excluded. Overall, after the study selection process and reference checking, 73 studies were included in the present targeted literature review. The study selection process is depicted in the Figure . The list of studies included in the review, along with reported variables, are presented in Table 1 . 19-125

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  • DOI: 10.1007/s11936-024-01048-0
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Managing Heart Failure in Chronic Kidney Disease: A Review of Current Literature

  • Benjamin Lidgard , N. Bansal
  • Published in Current Treatment Options in… 2 July 2024

32 References

Dietary sodium and fluid intake in heart failure. a clinical consensus statement of the heart failure association of the esc, empagliflozin and rapid kidney function decline incidence in type 2 diabetes: an exploratory analysis from the empa-reg outcome trial, clinical outcomes with glp-1 receptor agonists in patients with heart failure: a systematic review and meta-analysis of randomized controlled trials, novel potassium binders to optimize raasi therapy in heart failure: a systematic review and meta-analysis., guideline-directed medical therapy for the treatment of heart failure with reduced ejection fraction, the efficacy and safety of sacubitril/valsartan in chronic kidney disease: a systematic review and meta-analysis, real-world modifications of renin-angiotensin-aldosterone system inhibitors in patients with hyperkalemia initiating sodium zirconium cyclosilicate therapy: the optimize i study, efficacy of empagliflozin in patients with heart failure across kidney risk categories., cardiac and kidney benefits of empagliflozin in heart failure across the spectrum of kidney function: insights from the emperor‐preserved trial, effects of oral semaglutide on cardiovascular outcomes in individuals with type 2 diabetes and established atherosclerotic cardiovascular disease and/or chronic kidney disease: design and baseline characteristics of soul, a randomized trial, related papers.

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Hypoxia-inducible factor-prolyl hydroxylase inhibitors for treatment of anemia in chronic kidney disease: a systematic review and network meta-analysis.

Song Ren&#x;

  • 1 Department of Nephrology and Institute of Nephrology, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, School of Medicine, Sichuan Clinical Research Centre for Kidney Diseases, University of Electronic Science and Technology of China, Chengdu, China
  • 2 Robotic Minimally Invasive Surgery Center, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China

Purpose: To review current evidence on the efficacy and safety outcomes of HIF-PHIs in chronic kidney disease (CKD) populations with an emphasize on the safety profile.

Methods: A systematic search was conducted in the Medline, Embase, and Cochrane Central databases. Randomized controlled trials that had assessed the efficacy and safety of HIF-PHIs for anemia in CKD were included. The efficacy outcome included change of hemoglobin and the safety outcomes any adverse events, severe adverse events, major adverse cardiovascular events, and mortality. The qualities of studies were assessed using the Cochrane ROB tool.

Results: 47 studies encompassing 55 RCTs for the study outcomes were included in this study. All six commercially available HIF-PHIs had direct comparisons to ESA and placebo, yet lacked direct comparisons among each other. The network analysis demonstrated all six HIF-PHIs were able to effectively elevate hemoglobin in the general CKD patients compared to placebo. All HIF-PHIs did not differ among each other in the efficacy of correcting anemia. Roxadustat and daprodustat had the largest number of reports in terms of adverse events. The overall risk of each safety outcome did not increase in comparison to erythropoiesis stimulating agent (ESA) or placebo, and did not differ among different types of HIF-PHIs.

Conclusion: HIF-PHIs can effectively elevate hemoglobin without causing higher risk of safety concerns in CKD patients with anemia. Further evidence from long-term studies and the ongoing post-market surveillance is necessary.

Introduction

Anemia is a prevalent condition observed in a significant number of individuals with chronic kidney disease (CKD) and plays a crucial role in the ongoing management of CKD ( Stauffer and Fan, 2014 ; Li et al., 2016 ). Despite advancements in the treatment of renal anemia through the use of erythropoiesis stimulating agents (ESAs) and iron supplements ( Coyne et al., 2011 ; Litton et al., 2013 ), there remains a subset of patients for whom the correction of hemoglobin levels proves challenging ( Coyne et al., 2011 ). Additionally, the need of transfusion raises the risk of allograft rejection in the future kidney transplantation.

Although the superiority of hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHIs) in reducing transfusion needs in comparison to ESAs has not been supported by evidence, HIF-PHIs have significantly transformed the therapeutic approach to renal anemia ( Besarab et al., 2015 ) and undergone notable advancements in recent years, helping to address the requirements of correcting anemia in CKD patients ( Borawski et al., 2021 ; Mima, 2021 ; Natale et al., 2022 ). Due to its distinct underlying mechanisms, HIF-PHIs have garnered substantial evidence supporting their efficacy in correcting anemia, mainly in CKD, as well as in hematological disease in scattered reports ( Mima, 2021 ; Chen et al., 2023 ; Yang et al., 2023 ).

Despite the demonstrated positive effects of HIF-PHIs on hemoglobin levels and iron metabolism ( Souza et al., 2020 ), the potential cardiovascular risks and elevated VEGF levels associated with their use have been a topic of ongoing discussion ( Guimarães et al., 2023 ). Four network meta-analyses have been published regarding the effectiveness and safety of HIF-PHIs in treating renal anemia ( Zheng et al., 2020 ; Fadlalmola et al., 2022 ; Chen et al., 2023 ; Yang et al., 2023 ); however, these network meta-analyses treated dialysis and non-dialysis dependent patients separately and primarily emphasized the efficacy of HIF-PHIs on hemoglobin and iron metabolism, with limited attention given to their safety profile. The efficacy and safety profiles in the overall CKD population are still to be illustrated.

Therefore, we undertook a comprehensive review and network meta-analysis of randomized controlled trials to evaluate the effectiveness and safety of HIF-PHIs in individuals with CKD, with a particular focus on assessing the safety profile. The aim of this study was to gain a thorough understanding of the existing evidence and offer valuable insights for clinical practitioners.

Data sources and literature search

We conducted a systematic literature search according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement ( Liberati et al., 2009 ) from inception through 13 September 2023 in MEDLINE via PubMed, EMBASE via Ovid, and Cochrane Central Library, using text words and medical subject headings (MESHs) relevant to “hypoxia-inducible factor-prolyl hydroxylase inhibitor,” “kidney disease,” and “randomized controlled trials” that were combined using Boolean search terms “AND” and “OR” ( Supplementary Table S1 ). The search was limited to studies published in English. This systematic review and network meta-analysis has been registered in PROSPERO (Identifier# CRD42023429560).

The outcomes in this meta-analysis encompassed efficacy and safety outcomes. The efficacy outcome referred to the effect of HIF-PHIs to correct renal anemia, either increase hemoglobin or maintain hemoglobin in target ranges. The safety outcomes referred to any adverse events (AE), severe adverse events (SAEs), major adverse cardiovascular events (MACEs), and mortality.

Study selection

Two reviewers (S.R. and Y.R.Z.) independently conducted the study selection following a standardized approach. Titles and abstracts of records returned from the literature research were carefully examined. The remaining articles then underwent a full-text review for further exclusion. Reference lists of review articles were also manually screened for eligible studies that could have been missed.

Only randomized controlled trials that had assessed the efficacy and safety of HIF-PHIs for anemia in CKD were considered eligible for this study. Studies were excluded if they were: 1) duplicates, 2) reviews, protocols, comments, or editorials; 3) conducted in pediatric population; 5) cohort observational studies; and 6) animal model or in vitro studies. Studies without information on the study outcomes were also excluded. Any discrepancy was resolved through discussion and also adjudication from a third reviewer (Y.L.F.).

Data extraction

Data was extracted by two reviewers (S.R. and S.Q.R.) independently using Microsoft Excel spreadsheet and compiled onto a single one after cross examination. Any disagreement was resolved by the third reviewer (Y.L.F.). The extracted data included authors, publication year, geographic region, targeted population, sample size, numbers of patients and the detailed regimen in the experimental and control groups, and outcomes.

Quality assessment

The risk of bias was independently assessed by two reviewers (S.R. and Y.R.Z.) based on the “Cochrane Handbook for Systematic Reviews of Interventions” imbedded in the RevMan analysis software (2022) ( Higgins et al., 2022 ). Any discrepancy was resolved by the third reviewer (Y.L.F.). Risk of bias was analyzed for all studies and each individual study separately.

Data synthesis and analysis

The STATA (version 17.0; Stata Corporation, TX, United States) software were used for data synthesis and analysis. To evaluate continuous outcomes, the changes following treatment in comparison to baseline were used. Changes in the studies that had only reported the results before and after treatments were calculated by subtracting the baseline value from the pre-treatment value prior to data synthesis. The meta-analysis for continuous outcomes included direct comparisons for each pair of treatments and the network meta-analysis for multiple comparisons including indirect comparisons via pooled mean differences (MD) with 95% confidence intervals (CIs) using a random-effects model. Network map was used to shown the interactions among different treatments. The meta-analysis for categorized outcomes followed a similar procedure and utilized pooled Odds Ratios (ORs) with 95% CI using a random-effects model. The treatments were sorted in rank based on surface under the cumulative ranking curve (SUCRA) ( Salanti et al., 2011 ) for each outcome and graphically illustrated using the ranking panel plots. The higher the rank, the superior the treatment effect. Statistical heterogeneity was estimated using the I 2 statistic, for which an I 2 value of <25%, between 26% and 75%, and >75% represents low, moderate, and high heterogeneity, respectively ( Ioannidis, 2008 ). The assumption of consistency in the network analysis was verified using a design-by-treatment approach ( Higgins et al., 2012 ). A two-sided p -value of <0.05 was considered statistically significant. Publication bias was assessed by visual inspection of the comparison adjusted funnel plot.

Characteristics of the included studies

A total of 954 records were obtained from the literature search following the elimination of duplicate entries. Subsequent to the evaluation of titles and abstracts, 78 publications were deemed suitable for full text review, of which 31 were further excluded, resulting in 47 studies for inclusion in this network meta-analysis ( Agrawal et al., 2022 ; Akizawa et al., 2019a ; Akizawa et al., 2020a ; Akizawa et al., 2019b ; Akizawa et al., 2019c ; Akizawa et al., 2019d ; Akizawa et al., 2021a ; Akizawa et al., 2021b ; Akizawa et al., 2020b ; Akizawa et al., 2017 ; Akizawa et al., 2021c ; Bailey et al., 2019 ; Barratt et al., 2021a ; Barratt et al., 2021b ; Brigandi et al., 2016 ; Charytan et al., 2021 ; Chen et al., 2019a ; Chen et al., 2019b ; Chen et al., 2017 ; Chertow et al., 2021 ; Coyne et al., 2021 ; Coyne et al., 2022 ; Csiky et al., 2021 ; Eckardt et al., 2021 ; Fishbane et al., 2021 ; Fishbane et al., 2022 ; Gang et al., 2022 ; Holdstock et al., 2019 ; Holdstock et al., 2016 ; Hou et al., 2022 ; Martin et al., 2017 ; Meadowcroft et al., 2019 ; Nangaku et al., 2020 ; Nangaku et al., 2021a ; Nangaku et al., 2021b ; Nangaku et al., 2021c ; Parmar et al., 2019 ; Pergola et al., 2016 ; Provenzano et al., 2016 ; Provenzano et al., 2021 ; Shutov et al., 2021 ; Singh et al., 2021 ; Singh et al., 2022 ; Yamamoto et al., 2021b ) ( Figure 1 ).

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Figure 1 . PRISMA flow chart of this network meta-analysis. Abbreviations: CKD, chronic kidney disease; RCT, randomized controlled trial.

All studies were published from the year 2015 onwards. Among these, 43% (20 out of 47) were published in the year 2021. Geographically, the studies were distributed as follows: 23 in Asia, 19 in North America, and five in Europe. 22 studies were conducted in dialysis dependent patients and the other 25 were conducted in non-dialysis dependent patients. The follow up duration ranged widely from 4 to 240 weeks. Among these 47 studies, six studies reported 2 RCTs and one study reported 3 RCTs, adding up to a total number of 55 RCTs for the final comparisons for different outcomes. The detailed characteristics of included studies were shown in Supplementary Table S2 .

Efficacy of HIF-PHIs on hemoglobin

All six HIF-PHIs were compared to either ESA or placebo in the study. There is a lack of direct comparison between the different HIF-PHIs in both dialysis-dependent (DD) and non-dialysis-dependent (NDD) populations ( Figure 2 ). The results of direct comparisons supported the efficacy of HIF-PHIs to elevate hemoglobin over the placebo; however, these advantages were not evidently observed in comparison to ESA treatment ( Supplementary Figure S1 ). Among all the HIF-PHIs that reported an effect on hemoglobin levels, roxadustat had the largest total sample size. Roxadustat demonstrated a non-inferiority in increasing hemoglobin levels compared to ESA in DD populations, and to ESA and placebo in NDD populations. Enarodustat, desidustat, and daprodustat showed non-inferiorities in comparison to placebo in DD populations ( Figure 2 ). Overall, the effects of all HIF-PHIs on hemoglobin levels did not significantly differ from each other. A compiled analysis in both dialysis and non-dialysis dependent populations yielded similar findings ( Supplementary Figure S2 ).

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Figure 2 . Comparison for the efficacy on hemoglobin following different treatments in dialysis and non-dialysis dependent populations. Note: (A and B) In the network of comparisons, the size of nodes is proportional to the total sample size of each treatment, and the width of lines is proportional to the number of studies in each pair of comparison. (C and D) Bayesian ranking panel plots indicate the higher the rank reflected by the area under curve, the superior the treatment to increase the levels of hemoglobin. (E) The league table of pairwise comparison for the effects of different treatments on hemoglobin levels. All treatments are ordered based on efficacy ranking. Abbreviations: DD, dialysis dependent; NDD, non-dialysis dependent; MACE, major adverse cardiac events.

Safety of HIF-PHIs

All studies included in the analysis reported outcomes of any AE and SAE; however, four studies specifically focusing on enarodustat did not provide information on MACE or mortality ( Akizawa et al., 2019c ; Akizawa et al., 2019d ; Akizawa et al., 2021a ; Akizawa et al., 2021b ). As a result, the comparisons of any AE and SAE included six types of HIF-PHIs, while the comparisons of MACE and mortality only involved five types of HIF-PHIs. In terms of both any AE and SAEs, all HIF-PHIs were compared to ESA or placebo. Notably, roxadustat demonstrated the strongest evidence, as indicated by its largest total sample size and the highest number of RCTs ( Figure 3A,B ). There is a lack of direct comparisons between HIF-PHIs. ESA is once again the prevailing reported controlled therapy. In relation to placebo, all HIF-PHI treatments exhibited no significant elevation in the risk of any AE or SAE, and there was no discernible variation in risk between any two categories of HIF-PHIs ( Figure 3C–E ). These findings are corroborated by the direct comparisons ( Supplementary Figure S3 ).

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Figure 3 . Comparison for the risk of any adverse event and severe adverse event following different treatments. Note: (A) (B) In the network of comparisons, the size of nodes is proportional to the total sample size of each treatment, and the width of lines is proportional to the number of studies in each pair of comparison. Bayesian ranking panel plots indicate the higher the rank reflected by the area under curve, the superior the treatment to increase the risk of any AE (C) or SAE (D) . (E) The league table of pairwise comparison for the risk of any AE and SAE following different treatments. All treatments are ordered based on efficacy ranking.

Five types of HIF-PHIs had been compared to ESA or placebo in terms of both MACE and mortality; however, there is still absence of direct comparisons among the different types of HIF-PHIs ( Figure 4A,B ). ESA was the most commonly used controlled therapy in terms of both sample size and number of studies. Similar to the findings for any AE and SAE, the HIF-PHI treatments did not significantly increase the risk of MACE or mortality compared to placebo or ESA. Furthermore, there was no significant difference in risk between any two types of HIF-PHIs ( Figure 4C–E ). The findings are additionally supported by the direct comparisons ( Supplementary Figure S4 ).

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Figure 4 . Comparison for the risk of MACE and mortality following different treatments. Note: (A) (B) In the network of comparisons, the size of nodes is proportional to the total sample size of each treatment, and the width of lines is proportional to the number of studies in each pair of comparison. Bayesian ranking panel plots indicate the higher the rank reflected by the area under curve, the superior the treatment to increase the risk of MACE (C) or mortality (D) . (E) The league table of pairwise comparison for the risk of MACE and mortality following different treatments. All treatments are ordered based on efficacy ranking.

Consistency assessment

Consistency test results demonstrated consistency among the direct and indirect comparisons for the efficacy and all safety outcomes ( Supplementary Table S3 ).

Publication bias

Visual inspections of the funnel plots of the effect on hemoglobin and safety outcomes in the included studies revealed absence of asymmetry for the efficacy and safety outcomes ( Supplementary Figures S5 and S6 ).

Risk of bias assessment

Critical appraisal indicated 15, 34, and 6 RCTs were rated as having low, high, and unclear risk of bias based on Cochrane criteria ( Supplementary Figure S7 ). The domains with the highest proportion of high risk are the performance and detection bias.

The primary findings of this study revealed all six commercially available HIF-PHIs had direct comparisons to ESA and placebo, yet lacked direct comparisons among each other. The reliability of the results from indirect comparisons was confirmed through the consistency test. The network analysis revealed that all six HIF-PHIs effectively increased hemoglobin levels in general CKD patients compared to placebo. However, no significant differences were observed among different HIF-PHIs. These findings were consistent across both the DD and NDD populations. Roxadustat and daprodustat had largest number of reports in terms of adverse events. The overall risk of any AE, SAE, MACE, and mortality did not show an increase when compared to ESA or placebo, and did not vary across different types of HIF-PHIs.

Previous evidence has already demonstrated the effectiveness of HIF-PHIs to treat renal anemia ( Holdstock et al., 2016 ; Zheng et al., 2020 ; Akizawa et al., 2021a ; Yamamoto et al., 2021a ; Fadlalmola et al., 2022 ; Singh et al., 2022 ; Chen et al., 2023 ; Yang et al., 2023 ). Our findings contribute to the existing evidence by providing additional support for the efficacy of these agents and further demonstrating their effectiveness in the general CKD population, as well as across dialysis and non-dialysis dependent populations. Furthermore, a series of systematic reviews ( Li et al., 2021 ; Fatima et al., 2022 ; Guimarães et al., 2023 ; Mohamed et al., 2023 ; Ren et al., 2023 ; Takkavatakarn et al., 2023 ; Zheng et al., 2023 ) have provided compelling evidence for the efficacy of HIF-PHIs. This meta-analysis differs from the literature in several aspects. First, we used network meta-analysis to compare the efficacy and safety of all the commercially available HIF-PHIs so far. Second, this meta-analysis includes a larger number of RCTs and covers the most types of HIF-PHIs in comparison to the published network meta-analysis in this field ( Zheng et al., 2020 ; Fadlalmola et al., 2022 ; Chen et al., 2023 ; Yang et al., 2023 ). Third, compared with this study, the published network meta-analysis either only included DD population ( Zheng et al., 2020 ; Yang et al., 2023 ), did not include safety outcomes ( Chen et al., 2023 ; Yang et al., 2023 ), or only analyzed mortality ( Zheng et al., 2020 ). Fourth, we particularly examined the safety outcomes of HIF-PHIs in response to the concerns raised by FDA but did not identify higher MACE risk for HIF-PHIs in CKD population. However, interpretation of these results should be done with caution since the included RCTs were all non-inferiority test in nature. Future studies and long-term surveillance are needed to provide stronger evidence.

The safety of HIF-PHIs has been a subject of considerable scholarly discourse, with specific attention given to the potential cardiovascular risks and elevated levels of VEGF subsequent to treatment ( Mima, 2021 ); yet there exists a dearth of evidence regarding safety outcomes when comparing various types of HIF-PHIs. This study aims to comprehensively assess the occurrences of any AE, cardiovascular AE, severe AE, and mortality following HIF-PHIs treatments. The findings derived from both direct and indirect comparisons in this network analysis provide evidence that the safety profile of currently available HIF-PHIs in the market is not inferior to that of ESA or placebo, in relation to each of the four safety outcomes examined. Although daprodustat and roxadustat had been reported to be associated with increased risk of thrombosis ( Chen et al., 2023 ), this conclusion is limited by the number of studies, thus requiring further substantiation.

The mechanisms underlying the effects of HIF-PHIs in addressing anemia involve the inhibition of prolyl hydroxylase-mediated degradation of HIF-α in response to hypoxia, thereby activating the HIF pathway that regulates erythropoiesis at various levels ( Coyne et al., 2011 ; Koury and Haase, 2015 ). These mechanisms differ significantly from those of conventional therapies for renal anemia. In addition, the oral administration of HIF-PHIs might help to improve patient compliance and help to reduce the use of medical consumables compared to the subcutaneous administration of ESA in NDD patients.

There are still a few limitations to be mentioned. First, there is a lack of direct comparisons among individual HIF-PHIs, which might have enhanced the evidence should it existed; however, the indirect comparisons are supported by the results of consistency test. Second, it should be noted that although HIF-PHIs has been shown to have advantages in improving iron metabolism in anemia by reducing the hepatic peptide hepcidin ( Ganz and Nemeth, 2012 ), this study did not provide a comprehensive summary of the impact of HIF-PHIs on iron metabolism. Third, epoetin and darbepoetin alpha were considered as a single group in this meta-analysis. Fourth, the evidence of safety outcomes is not long enough due to the limited time after the launch of the first HIF-PHI agent. More stringent evidence is expected with the ongoing post-market surveillance and clinical research.

In summary, the findings of this systematic review and network meta-analysis suggest that all six commercially available HIF-PHIs effectively increase hemoglobin levels in patients with CKD compared to placebo. No significant differences were observed among the various HIF-PHIs. The overall risk of adverse events, serious adverse events, major adverse cardiovascular events, and mortality did not increase with HIF-PHIs treatment compared to ESA or placebo, and no differences were found among the different types of HIF-PHIs. However, further evidence from long-term studies and the ongoing post-market surveillance is necessary.

Author contributions

SR: Conceptualization, Data curation, Formal Analysis, Software, Writing–original draft. YZ: Conceptualization, Data curation, Investigation, Methodology, Writing–original draft. JW: Data curation, Formal Analysis, Methodology, Writing–original draft. SR: Conceptualization, Data curation, Validation, Writing–review and editing. YF: Conceptualization, Data curation, Methodology, Software, Validation, Visualization, Writing–review and editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2024.1406588/full#supplementary-material

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Keywords: hypoxia-inducible factor-prolyl hydroxylase inhibitor, anemia, chronic kidney disease, efficacy, safety, network meta-analysis

Citation: Ren S, Zhao Y, Wu J, Ren S and Feng Y (2024) Hypoxia-inducible factor-prolyl hydroxylase inhibitors for treatment of anemia in chronic kidney disease: a systematic review and network meta-analysis. Front. Pharmacol. 15:1406588. doi: 10.3389/fphar.2024.1406588

Received: 25 March 2024; Accepted: 24 June 2024; Published: 10 July 2024.

Reviewed by:

Copyright © 2024 Ren, Zhao, Wu, Ren and Feng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yunlin Feng, [email protected] ; Shangqing Ren, [email protected]

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

  • Open access
  • Published: 10 July 2024

A systematic review of the drug-drug interaction between Statins and Quinolones

  • Jifang Zhou 1 ,
  • Lixia Yu 2 &
  • Huimin Xu 3  

BMC Pharmacology and Toxicology volume  25 , Article number:  39 ( 2024 ) Cite this article

Metrics details

Statins are widely used in cardiovascular disease (CVD) as a common lipid-lowering drug, while quinolones are widely used for the treatment of infectious diseases. It is common to see CVD in combination with infectious diseases, therefore it is often the case that statins and quinolones are used in combination. Data suggest combinations of statin and quinolone may be associated with potentially life-threatening myopathy, rhabdomyolysis and acute hepatitis. This systematic review aims to characterize data regarding patients affected by the statin-quinolone interaction.

The purpose of this systematic review was to collect and evaluate the evidence surrounding statin-quinolone drug interactions and to discuss related risk mitigation strategies. The following databases were searched: PubMed (Medline), Embase, Scopus, and Cochrane Library. The systematic electronic literature search was conducted with the following search terms. In this study, three types of search terms were used: statins-related terms, quinolones-related terms, and drug interactions-related terms.

There were 16 case reports that met the criteria for qualitative analysis. Patients were involved in the following adverse reactions: rhabdomyolysis ( n  = 12), acute hepatitis ( n  = 1), muscle weakness ( n  = 1), hip tendinopathy ( n  = 1), or myopathy ( n  = 1). In the included literature, patients vary in the dose and type of statins they take, including simvastatin ( n  = 10) at a dose range of 20–80 mg/d and atorvastatin ( n  = 4) at a dose of 80 mg/d. There were 2 patients with unspecified statin doses, separately using simvastatin and atorvastatin. The quinolones in combination were ciprofloxacin ( n  = 9) at a dose range of 800–1500 mg/d, levofloxacin ( n  = 6) at a dose range of 250–1000 mg/d, and norfloxacin ( n  = 1) in an unspecified dose range. 81% of the case patients were over 60 years of age, and about 1/3 had kidney-related diseases such as diabetic nephropathy, post-transplantation, and severe glomerulonephritis. Nearly two-third of the patients were on concomitant cytochrome P450 3A4 (CYP3A4) inhibitors, P-glycoprotein (P-gp) inhibitors, or organic anion transporting polypeptide 1B1 (OATP1B1) inhibitors.

Patients treated with statin-quinolone combination should be monitored more closely for changes in aspartate aminotransferase or creatine kinase (CK) levels, and muscle symptoms, especially in patients with ciprofloxacin or levofloxacin, with simvastatin and high-dose atorvastatin, over 60 years of age, with kidney-related diseases, and on concomitant CYP3A4 inhibitors.

Peer Review reports

Hydroxymethylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, also known as statins, represent widely prescribed drugs currently available for the reduction of low-density lipoprotein cholesterol, which are widely used as the mainstay therapy for the management of dyslipidaemia, including primary and secondary prevention of cardio-and cerebro-vascular disease [ 1 ]. It is estimated that around 200 million people worldwide are taking statins, which makes up 3% of the global population [ 2 ]. Although considered efficacious and safe, statins are associated with adverse effects, such as skeletal muscle toxicity and hepatic adverse reactions [ 3 ]. Globally, between 5.9 and 7.0% (depending on the diagnostic criteria used) of statin-treated patients experience symptoms of intolerance [ 4 , 5 ]. Risk factors for statin-associated adverse drug reaction include advanced age (especially > 80 years, more common in women), thinness, frailty, multisystem disease (e.g., chronic renal insufficiency, especially due to diabetes), combination of multiple medications, perioperative period, combination of special medications and diet, and excessive statin doses. Certain medications increase the risk, including colchicine, verapamil, diltiazem, fibrates, protease inhibitors, and azoles [ 6 ]. So among all risk factors, drug-drug interactions play an important role and deserve further study.

Quinolones are widely used for the treatment of infectious diseases (e.g., respiratory tract infections, urinary tract infections, bacterial prostatitis, skin and other soft tissue infections, bone and joint infections, gastrointestinal infections) [ 7 ]. Adverse reactions of quinolones have certain commonalities, most commonly tendon and joint pain, and some degree of hepatotoxicity [ 8 ]. It is common to see CVD in combination with infectious diseases, therefore it is often the case that statins and quinolones are used in combination. Data suggest statin and quinolone combination may be associated with potentially life-threatening myopathy, rhabdomyolysis and acute hepatitis.

This systematic review aims to characterize data regarding patients affected by the statin-quinolone interaction, as well as describe potential etiologies, clinical ramifications, and risk-mitigation strategies associated with the drug-drug interaction between statins and quinolones.

Data sources and searches

We conducted a literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. A literature search of the following databases was performed: PubMed (Medline), Embase, Scopus, and Cochrane library. We searched for all synonyms including “statins”, “quinolones” and “drug interactions”, and every statin and quinolone drug name. Search terms used across all databases included all synonyms for “statins”, “quinolones” and “drug interactions”, and every statin and quinolone drug name (for the complete search strategy, see Attachment  1 ), but filters varied depending on the database utilized. All databases were searched for literature up to the end of October 2022. Only articles reporting on original data, including non randomized, randomized studies, observational cohort studies, case series or case reports in adult patients aged 18 years and older were eligible for inclusion.

Exclusion criteria were (1) studies without concurrent statin-quinolone therapy, (2) studies that did not involve statin-quinolone interactions, (3) incomplete outcome reports, and (4) duplicate articles.

This study was reviewed and approved by the Medical Ethics Committee of the First People’s Hospital of Linping District, (approval number: Linping First People’s Hospital Ethics 2022 Paper No. 49).

Data charting and evidences synthesis

In order to map the evidence, the PRISMA template was adapted. We collected data from two authors (JF and LX), then we resolved chart conflicts from a third author (HM). From each study, extract the following information: author (year), study design, patient demographics and comorbidities, statin regimen, statin intensity, quinolones regimen, quinolones dose, quinlones indication, concomitant CYP3A4 inhibitors, concomitant P-gp inhibitors, concomitant OATP1B1 inhibitors, time from quinolones initiation to onset of adverse drug reaction(ADR), hospitalization or not, ADR developed, tests for diagnostic purposes, laboratory examination, presentation, treatment and regression of ADR, time to improvement of symptoms, time to normalization of laboratory indicators, outcomes of patients, and mortality after adverse drug event.

figure 1

PRISMA flow diagram for Statin-Quinolones drug–drug interaction database searching of records

The search retrieved 478 records, of which 387 were screened by investigators. The specific reasons for exclusion were as follows: (1) duplicate records ( n  = 91); (2) Irrelevant when found by the investigator reading the abstract ( n  = 347); (3) Reports which were excluded by full-text search ( N  = 24): no concurrent statin-quinolones therapy ( n  = 9); no statin-quinolones interactions ( n  = 11); incomplete outcome reports ( n  = 3); duplicate articles ( n  = 1). Figure  1 depicts the PRISMA flow diagram for the screening, and ultimately, there were 16 case reports that met the criteria for qualitative analysis (Table  1 ).

ADRs in the included literature were rhabdomyolysis ( n  = 12) [ 9 , 10 , 11 , 13 , 15 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ], acute hepatitis ( n  = 1) [ 17 ], muscle weakness ( n  = 1) [ 16 ], tendinopathy of hip ( n  = 1) [ 12 ], and myopathy ( n  = 1) [ 14 ] (Table  2 ). CK was reported in 81% ( n  = 13) of the case reports with a range between 183 and 816,000 units/L, which all above the normal value for CK [ 9 , 10 , 11 , 14 , 15 , 16 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. All patients were given statins, including simvastatin ( n  = 10) [ 11 , 12 , 13 , 17 , 18 , 20 , 21 , 22 , 23 , 24 ] at a dose range of 20–80 mg/day and 66.7% of the remaining patients received 80 mg/day of oral atorvastatin ( n  = 4) [ 9 , 15 – 16 , 19 ]. And there were 2 patients with unspecified statin doses, separately using simvastatin and atorvastatin. Different types of quinolone antibiotics for the patients involved, including ciprofloxacin ( n  = 9), levofloxacin ( n  = 6), and norfloxacin ( n  = 1). Among the included articles, the drug combinations which showed ADRs were simvastatin and ciprofloxacin ( n  = 6), simvastatin and levofloxacin ( n  = 4), atorvastatin and ciprofloxacin ( n  = 3), atorvastatin and levofloxacin ( n  = 2), and simvastatin and norfloxacin ( n  = 1). The dose of quinolones is heterogeneous among the studies. Seven case reports reported ciprofloxacin doses between 400 and 750 mg twice daily [ 9 , 14 , 15 , 16 , 18 , 22 , 24 ] and 2 case reports did not report ciprofloxacin doses [ 20 , 24 ]. Six case reports reported levofloxacin doses between 250 to 1000 mg/d [ 10 , 11 , 12 , 17 , 19 , 21 ]. It was unclear from 1 case report about the norfloxacin dosage [ 13 ]. In the included literature, the majority of patients’ adverse reactions occurred between 1 and 19 days of combined statin and quinolone use. Only one patient was readmitted for myopathy 3 months after the combination, but the exact timing of the ADR was not clear [ 14 ]. High-intensity statins were implicated in 5 case reports [ 9 , 15 – 16 , 19 , 21 ], with four patients taking 80 mg per day of atorvastatin and one patient using 80 mg per day of simvastatin, while moderate-intensity statins in 9 case reports [ 11 , 13 , 15 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. It was unclear from two case reports about the statin dosage, one involving atorvastatin and one involving simvastatin [ 10 , 13 ]. Approximately 63% of the case report patients were male [ 9 , 11 , 12 , 15 , 17 , 19 , 20 , 21 , 24 ] and 81% of the patients were over 60 years old [ 9 , 10 , 11 , 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 24 ]. Most patients presented with comorbidities, with the most common being hypertension (56%, n  = 9), coronary artery disease (56%, n  = 9), dyslipidemia (44%, n  = 7), diabetes (19%, n  = 3) and renal abnormalities (31.25%, n  = 5). Two cases identified solid organ transplant patients who were taking concomitant immunosuppressants, specifically cyclosporine [ 11 , 14 ]. Ten case reports (62.5% of all studies) reported patients were taking concomitant CYP3A4, P-gp and/or OATP1B1 inhibitors. Four case reports identified patients taking with amiodarone (a concurrent CYP3A4 and P-gp inhibitor) [ 10 , 15 , 17 , 23 ]. Four cases reported patients used amlodipine (a CYP3A4 inhibitor) [ 10 , 17 , 20 , 24 ]. Three cases report identified patients taking concomitant cyclosporine (a CYP3A4, P-gp and OATP1B1 inhibitor) [ 11 , 14 , 20 ]. Two cases described patients taking clarithromycin (a CYP3A4 and P-gp inhibitor) [ 14 , 22 ]. One case reported the patient with a concurrent ticagrelor (a concurrent CYP3A4 and P-gp inhibitor) [ 16 ].

All of the 16 adverse reactions reported by this systematic review required hospitalization. Seven case reports (44%) managed the ADR by discontinuing both the statin and quinolones [ 9 , 11 , 16 , 19 , 21 – 22 , 24 ], 4 cases (25%) discontinued the statin alone [ 12 , 13 , 14 , 18 ] and 2 case (12.5%) discontinued the quinolones alone [ 10 , 17 ]. One case (6%) managed the ADR by switching to another statin [ 15 ]. Seven cases (44%) managed the ADR by hydrating with intravenous fluids [ 9 , 16 , 17 , 18 , 19 , 20 , 21 ], and 2 case (12.5%) were treated with dialysis [ 9 , 23 ], while 2 patients (12.5%) treated with alkalinised urine [ 20 – 21 ]. In the included literature, all cases were improved after relevant treatment. Patients’ symptoms of adverse reactions improved after 3–28 days. None of the patients experienced death as a result of the statin and quinolone combination.

In this systematic review, 16 patients experienced ADRs related to the combination of statins and quinolones. These reported ADRs included rhabdomyolysis ( n  = 12), acute hepatitis ( n  = 1), muscle weakness ( n  = 1), hip tendinopathy ( n  = 1) or myopathy ( n  = 1), with the vast majority (81%) of these symptoms being associated with CK elevation. The drug combinations presenting with ADRs were, in order of frequency, simvastatin and ciprofloxacin ( n  = 6), simvastatin and levofloxacin ( n  = 4), atorvastatin and ciprofloxacin ( n  = 3), atorvastatin and levofloxacin ( n  = 2), and simvastatin and norfloxacin ( n  = 1). In summarising the most common characteristics of patients affected by statin-quinolone interactions described in this systematic review, 10 subjects (62.5% of all patients) were combined with other drugs such as CYP3A4 inhibitor, P-gp inhibitor, OATP1B1 inhibitor, 13 subjects (81.25% of all patients) were over 60 years of age; 14 (88% of all studies) reported patients taking medium to high intensity statins and 5 subjects (31.25% of all patients) identified patients with comorbid renal disease. On average, ADRs occurred after 15 days of combined statin and quinolone therapy. All patients were hospitalised for the aforementioned adverse reactions, 13 patients chose to discontinue the drug, seven of them discontinuing both statin and quinolone, 4 patients discontinuing only the statin and two discontinuing only the quinolone; 7 patients used hydration, 2 patients underwent dialysis; and 1 patient adjusted the type of statin. In addition, genetic analysis was performed in only one of the 16 cases to clarify possible factors for the development of ADR. All patients improved after appropriate treatment.

Through this systematic review, we found the types of the statins and quinolones were risk factors for ADR following the combination of statins and quinolones. Statins can be grouped according to differences in enzymatic metabolism, for example simvastatin and atorvastatin are mainly metabolised by CYP3A4 isoenzymes, whereas fluvastatin and pravastatin are mainly metabolised by CYP2C9 enzymes [ 25 ]. In the included reports, the types of statins were dominated by simvastatin ( n  = 11) and atorvastatin ( n  = 5), and the types of quinolones were ciprofloxacin ( n  = 9), levofloxacin ( n  = 6) and norfloxacin ( n  = 1), which are all CYP3A4 inhibitors. Therefore, combination of statins and quinolones metabolised by CYP3A4 are at greater risk of drug interactions. Secondly, the dose of the statin was also a risk factor for ADR following the combination of statins and quinolones. In this systematic review, statin doses were mentioned in 14 of the 16 cases, all at moderate to high intensity statins. Atorvastatin had an ADR risk only at the highest dose (80 mg/d), whereas simvastatin had a risk at all doses (dose range fluctuated from 20 to 80 mg/d). However, the dose and treatment duration of quinolones may not affect the ADRs that occur after the combination of statin and quinolone. Quinolone doses were mentioned in 13 of the 16 cases, with seven cases reporting ciprofloxacin doses between 400 and 750 mg twice daily and six cases reporting levofloxacin doses between 250 and 1000 mg/day. Only 4 of the 16 cases used levofloxacin at a dose slightly above the usual dose. Quinolone treatment duration were mentioned in 9 of 16 case reports, with specific durations ranging from 4 days to 3 months. Thirdly, the combined medications were risk factors for ADR following the combination of statins and quinolones. In 16 publications, 10 patients were combined with CYP3A4 inhibitors, P-gp inhibitors, and OATP1B1 inhibitors that affect statin metabolism, such as amiodarone, amlodipine, cyclosporine, clarithromycin and ticagrelor. Amiodarone is an inhibitor of the pharmacological enzyme P450 3A4 and P-gp, which affects simvastatin and atorvastatin, with the most adverse reactions reported in combination with simvastatin. Amlodipine is known to have a competitive inhibitory effect on the metabolic activity of CYP3A4/5. Pharmacokinetic modelling has shown that 10 mg amlodipine significantly increases the bioavailability and decreases the clearance of simvastatin when it is combined with simvastatin [ 26 , 27 ]. In addition, combination therapy with cyclosporine A and simvastatin increased the area under the curve of simvastatin by eightfold by competing for the drug binding site of the cytochrome P450 3A4 enzyme [ 28 , 29 , 30 ]. Also cyclosporine A is a potent inhibitor of P-glycoprotein and prolongs levofloxacin concentrations in tissues. Clarithromycin is an inhibitor of organic anion transporter polypeptide 1B1 (OATP1B1), a transporter involved in the metabolic pathway of all statins, including those not metabolised by CYP3A4 [ 31 ]. Ticagrelor is metabolised by cytochrome P4503A4, which, like most statins, competitively inhibits CYP3A4 isoenzymes, leading to the accumulation of statins metabolised by CYP3A4. Finally, patients with creatinine clearance below 30 ml/min and older patients were all reported increasing risks of statin-related myopathy [ 26 , 27 , 28 , 29 , 30 ]. In this systematic review, we also found that elderly patients and renal insufficiency are all factors that contribute to the increased risk of combining statins and quinolones. We found 13 patients (81.25% of all patients) were over 60 years of age and 5 patients (31.25% of all patients) were with combined renal insufficiency.

In general, the first step after an ADR is to stop the suspected drug. According to the relevant guidelines, the main treatment principle for rhabdomyolysis is to promote the excretion of myoglobin from the kidneys and protect renal function, which is divided into the following four options: (1) hydration: saline infusion is recommended; (2) alkalinize the urine: apply sodium bicarbonate to alkalize the urine; (3) correction of electrolyte disturbances caused by rhabdomyolysis, such as low blood calcium and high blood potassium; (4) dialysis at the appropriate time [ 32 , 33 ]. Faced with ADRs from the combination of statins and quinolones, 13 patients discontinued their medication, of whom 7 discontinued both statins and quinolones, 4 discontinued only statins, 2 discontinued only quinolones and 1 adjusted the type of statin; 7 patients chose to rehydrate and 2 went on dialysis; all patients subsequently showed improvement. We found a significant effect regardless of whether statins or quinolones were discontinued. Regarding the choice of hydration medication, some chose 0.9% sodium chloride injection, some chose intravenous crystalloid, some chose intravenous crystalloid hypotonic solution, and 2 patients combined catheterisation or the diuretic furosemide as an adjunct to diuresis. In the early stages of ADR, fluid replacement, diuresis and active correction of electrolyte disturbances are the mainstays, and sodium bicarbonate can be used to alkalinise the urine. If severe kidney damage has been caused or if symptoms of oliguria or anuria develop, haemodialysis or haemofiltration treatment can be administered. In most cases, doctors were able to detect ADRs caused by the combination of statins and quinolones and treated them as recommended, and the prognosis was generally good.

Conclusions

In this systematic review, 16 cases reported ADRs while receiving a statin-quinolone combination. The pharmacokinetic and pharmacodynamic properties of quinolones and statins, the combination of CYP3A4 isoenzymes and P-gp inhibitors and OATP1B1 inhibitors, reduced renal function and advanced age are all factors that contribute to adverse reactions following the combination of quinolones and statins. Therefore, patients treated with statin-quinolone combinations should be monitored intensively for changes in liver function and muscle enzymes and if ADRs develops, it can be reversed by timely drug discontinuation, hydration, diuresis and dialysis.

Data availability

The dataset used and/or analysed during the current study is available from the corresponding author on reasonable request.

Abbreviations

Cardiovascular disease

Cytochrome P450 3A4

P-glycoprotein

Organic anion transporting polypeptide 1B1

Creatine kinase

Hydroxymethylglutaryl coenzyme A

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Adverse drug reaction

Ventilator-associated pneumonia

Creatine Kinase

Lactate dehydrogenase

Aspartate transaminase

Alanine amiotransferase

Creatine Kinase, MB Form

Serum creatinine

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We collected data from two authors (JF and LX), then we resolved chart conflicts from a third author (HM). Contributed to conception and design: JF and HM. Contributed to acquisition of data: JF and LX. Contributed to analyses of data: all authors. Contributed to interpretation of data: all authors. Drafting the work: all authors. Revising the paper for important intellectual content: all authors. Final approval of the version submitted: all authors. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: all authors. All authors read and approved the final manuscript.

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Zhou, J., Yu, L. & Xu, H. A systematic review of the drug-drug interaction between Statins and Quinolones. BMC Pharmacol Toxicol 25 , 39 (2024). https://doi.org/10.1186/s40360-024-00760-8

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Economic Modelling of Chronic Kidney Disease: A Systematic Literature Review to Inform Conceptual Model Design

Affiliations.

  • 1 Health Economics and Outcomes Research Limited, Rhymney House, Unit A Copse Walk, Cardiff Gate Business Park, Cardiff, CF23 8RB, UK. [email protected].
  • 2 Health Economics and Outcomes Research Limited, Rhymney House, Unit A Copse Walk, Cardiff Gate Business Park, Cardiff, CF23 8RB, UK.
  • 3 AstraZeneca, Gothenburg, Sweden.
  • PMID: 31571136
  • PMCID: PMC6892339
  • DOI: 10.1007/s40273-019-00835-z

Background: Chronic kidney disease (CKD) is a progressive condition that leads to irreversible damage to the kidneys and is associated with an increased incidence of cardiovascular events and mortality. As novel interventions become available, estimates of economic and clinical outcomes are needed to guide payer reimbursement decisions.

Objective: The aim of the present study was to systematically review published economic models that simulated long-term outcomes of kidney disease to inform cost-effectiveness evaluations of CKD treatments.

Methods: The review was conducted across four databases (MEDLINE, Embase, the Cochrane library and EconLit) and health technology assessment agency websites. Relevant information on each model was extracted. Transition and mortality rates were also extracted to assess the choice of model parameterisation on disease progression by simulating patient's time with end-stage renal disease (ESRD) and time to ESRD/death. The incorporation of cardiovascular disease in a population with CKD was qualitatively assessed across identified models.

Results: The search identified 101 models that met the criteria for inclusion. Models were classified into CKD models (n = 13), diabetes models with nephropathy (n = 48), ESRD-only models (n = 33) and cardiovascular models with CKD components (n = 7). Typically, published models utilised frameworks based on either (estimated or measured) glomerular filtration rate (GFR) or albuminuria, in line with clinical guideline recommendations for the diagnosis and monitoring of CKD. Generally, two core structures were identified, either a microsimulation model involving albuminuria or a Markov model utilising CKD stages and a linear GFR decline (although further variations on these model structures were also identified). Analysis of parameter variability in CKD disease progression suggested that mean time to ESRD/death was relatively consistent across model types (CKD models 28.2 years; diabetes models with nephropathy 24.6 years). When evaluating time with ESRD, CKD models predicted extended ESRD survival over diabetes models with nephropathy (mean time with ESRD 8.0 vs. 3.8 years).

Discussion: This review provides an overview of how CKD is typically modelled. While common frameworks were identified, model structure varied, and no single model type was used for the modelling of patients with CKD. In addition, many of the current methods did not explicitly consider patient heterogeneity or underlying disease aetiology, except for diabetes. However, the variability of individual patients' GFR and albuminuria trajectories perhaps provides rationale for a model structure designed around the prediction of individual patients' GFR trajectories. Frameworks of future CKD models should be informed and justified based on clinical rationale and availability of data to ensure validity of model results. In addition, further clinical and observational research is warranted to provide a better understanding of prognostic factors and data sources to improve economic modelling accuracy in CKD.

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Conflict of interest statement

DS, TW, SR and PM are employees of Health Economics and Outcomes Research Ltd. and received funding from AstraZeneca to undertake the research outlined in this study. HVH is an employee of AstraZeneca.

PRISMA (Preferred Reporting Items for…

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram showing the model-selection…

Example of the core model…

Example of the core model structure of chronic kidney disease models. CKD chronic…

Example of the core model structure of the nephropathy component of diabetes models…

Predicted time to end-stage renal…

Predicted time to end-stage renal disease (ESRD) or death and with ESRD. CKD…

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  • Published: 09 July 2024

Effectiveness of educational programs for patients with diabetic kidney disease: a systematic review and meta-analysis

  • Takashi Kemmochi   ORCID: orcid.org/0000-0003-0584-9516 1 , 2 ,
  • Michiyo Oka 2 ,
  • Ayako Inokuma 2 ,
  • Natsumi Shirato 2 &
  • Ryotaro Totsuka 2  

Renal Replacement Therapy volume  10 , Article number:  38 ( 2024 ) Cite this article

Metrics details

To prevent the progression of diabetic nephropathy, educational programs to improve self-management are important. However, the effectiveness of educational programs to prevent worsening of diabetic kidney disease on renal function and quality of life is under characterised.

The purpose of this study was to conduct a systematic review and meta-analysis to identify effective educational programs for diabetic kidney disease and the impact of educational programs on improving renal function and quality of life in patients with diabetic kidney disease.

The study design is a systematic review and meta-analysis.

We systematically collected research papers, and two authors independently selected papers and evaluated them according to the inclusion criteria. The extracted data were entered into Review Manager 5.4, and the standardised mean difference of the delta estimated glomerular filtration rate (ml/min/1.73m 2 /year) was calculated using a random effect size model for the renal function evaluation.

Overall, 207 articles were retrieved from five electronic databases and three studies were shortlisted. Data from the two studies on delta estimated glomerular filtration rate (ml/min/1.73 m 2 /year) were combined, but the results were not significant. The effect on quality of life was observed in only one of the three studies, so they could not be pooled.

Conclusions

Effective educational programs for self-management of diabetic kidney disease could not be identified because of the small number of studies included. Educational programs reviewed also lacked a significant effect on kidney function, likely related to their short durations. The effect of the education programs on quality of life is unknown because studies could not be pooled.

Approximately 40% of patients with diabetes develop diabetic kidney disease (DKD), the leading cause of chronic kidney disease (CKD) worldwide [ 1 ]. At least half of all patients with type 2 diabetes mellitus and one-third of those with type 1 diabetes develop kidney disease due to their disease or other comorbidities, including hypertension, dyslipidaemia, obesity, intrarenal vascular disease, glomerular atherosclerosis, renal ischaemia and ageing-related nephron loss [ 2 ]. To prevent the progression of diabetic nephropathy, educational programs to improve self-management are important.

Literature review

Several meta-analyses have reported that education programs for people with diabetes improve glycated haemoglobin levels [ 3 , 4 , 5 , 6 , 7 , 8 ]. Furthermore, studies have reported that individuals with diabetes improve their quality of life (QoL) by participating in diabetes education programs [ 9 ]. Previous studies have reported that educational programs for people with DKD improve their knowledge about diabetes and are effective in improving self-efficacy, treatment effectiveness and patients’ beliefs about personal control, leading to behavioural changes. However, owing to heterogeneity and quality issues, no meta-analysis has been conducted [ 10 ].

A systematic review and meta-analysis was conducted on the multidisciplinary management of people with DKD in 2016. The control group had a significant decrease in estimated glomerular filtration rate (eGFR) than that in the intervention group. However, the report indicates that the inclusion of studies with small sample sizes and regular follow-up of patients in the control group with the same standard of care as the intervention group led to a bias in the results [ 11 ]. Thus, there is insufficient evidence on the effects of educational programs to prevent the worsening of DKD on renal function and QoL. Furthermore, a meta-analysis evaluating the effects of educational programs for people with DKD on renal function and QoL will enable the development and implementation of optimal evidence-based educational programs. Therefore, this study aimed to identify effective DKD education programs and conduct a systematic review and meta-analysis to identify the impact of education programs on improving renal function or QoL in people with DKD.

Search strategy and selection criteria

Five electronic databases, including the Cochrane Library (CENTRAL) (2010 to 31 December 2021), MEDLINE (EBSCOHOST) (2010 to 31 December 2021), EMBASE (2010 to 31 October 2020), CINAHL (EBSCOHOST) (2010 to 31 December 2021) and PsycINFO (2010 to 31 December 2021), were used in the study. Terms related to patient education, self-care, health behaviours, diabetes and kidney disease were included in the search (Supporting Information: Appendix A ). The MeSH term was used as a keyword, and referring to previous research and the use of extended words was chosen as necessary. Because the controlled vocabulary used differed depending on the search database, some search keywords were modified on the basis of the database. The database was limited to randomised controlled trials (RCTs) and a web-based search was conducted.

Inclusion criteria for the studies were (1) participants aged ≥ 18 years, (2) participants with type 1 or type 2 diabetes and CKD, (3) a series of deliberate and planned educational activities by healthcare workers to slow DKD progression and (4) comparison of the educational programs with the usual care.

The exclusion criteria were (1) studies without primary outcomes, (2) conference abstracts or protocols and (3) only non-educational interventions. The primary outcomes were renal function data (delta eGFR) and QoL measures (SF-36, HDQOL), with no secondary outcomes. The study designs included RCTs, quasi-RCTs and randomised crossover trials. Grey literature was not searched, and only studies written in English were included.

The protocol was registered with PROSPERO (CRD42022383144) for review. It was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement, an updated guideline for reporting systematic reviews [ 12 ].

Study selection and screening

Search results were shared among reviewers using Endnote X9, literature management software. After the search results were collated and duplicates were removed, the titles and abstracts were reviewed independently by two reviewers; all studies were reviewed by T.K., and the studies were reviewed independently by other reviewers (A.I., N.S., R.T.). The full texts of potentially relevant studies were then obtained, and the studies were peer-reviewed for compliance with the inclusion criteria. All studies were reviewed by T.K, as were titles and abstracts, and the studies were independently reviewed by other reviewers (A.I., N.S., R.T.). Discordance between reviewers was resolved through discussion. To assess the quality of the literature, we conducted a risk assessment of bias using the Cochrane Risk of Bias Tool 2 (ROB2) [ 13 ].

Data analysis

The mean and standard deviation of delta eGFR (ml/min/1.73 m 2 /year) in the intervention and control groups and the number of data points were extracted. The data were then entered into Revman5.4, and a meta-analysis of the standardised mean difference in delta eGFR (ml/min/1.73 m 2 /year) was performed using a random-effect size model for the evaluation of renal function.

A total of 207 studies were retrieved from five electronic databases. Of these 21 duplicate studies were excluded. On the basis of previous studies [ 10 ], studies published from January 2010 were included in the study. Hence, of the remaining 107 studies, 72 were excluded by two reviewers. Moreover, 20 studies not involving patients with DKD were excluded, 7 studies were not eligible based on interventions, 2 studies were not RCTs and 1 study did not compare the information with usual care. Additionally, one retracted paper, one protocol paper and one conference abstract were excluded. Finally, three studies were included in the study; two assessed delta eGFR (ml/min/1.73 m 2 /year) as an outcome and one also assessed QoL measures (Fig.  1 ).

figure 1

Study selection flow diagram

Risk of bias assessment

The risk of bias in the three studies was assessed for eGFR by using ROB2 (Fig.  2 ). There was some concern about the risk of bias due to domain 1, that is, bias arising from the randomisation process in the Fogelfeld et al. study [ 14 ] with allocation concealed and assignment order unknown. There was some concern about the risk of bias due to deviation from domain 2, that is, bias due to deviations from the intended interventions in all studies with the interventions not blinded. There was a high risk of bias due to missing domain 3, that is, bias due to missing outcome data in the Helou et al. study [ 15 ], with eight of the 32 patients dropping out. There was a low risk of bias in the measurement of domain 4, that is, bias in the measurement of the outcome because all studies were objective measures of blood sampling and were appropriately measured. There was some concern about the risk of bias in the selection of domain 5, that is, bias in the selection of the reported result in all studies with lack of information. Thus, in terms of bias, all three studies were of low quality because the risk of overall bias was of some concern in the Fogelfeld et al. and Kobe et al. studies [ 14 , 16 ], and was high in the Helou et al. study [ 15 ].

figure 2

Risk of bias assessment (delta eGFR). D1 – randomisation process, D2 – deviations from the intended interventions, D3 – missing outcome data, D4 – measurement of the outcome, D5 – selection of the reported result

Characteristics of included studies

Participants.

Fogelfeld and Hart [ 14 ] conducted a single-centre proof-of-concept study in patients with type 2 diabetes and CKD stages 3–4. They screened 1365 patients, of which 1245 were excluded and 120 patients who met the inclusion criteria were enrolled and randomised. The dropout rate was 17.5%, with 23% in the intervention group and 12% in the control group. These patients were included in the analysis using their last observation. The mean ages of participants in the intervention and non-intervention groups were 56.27 ± 7.46 and 58.69 ± 7.46 years, respectively, and the percentage of men included was 60% and 56.7%, respectively. The duration of diabetes at baseline was 15 years in both groups, and the baseline eGFR was 37.95 ± 10.74 ml/min/1.73 m 2 and 37.18 ± 13.00 ml/min/1.73 m 2 in the intervention and non-intervention group, respectively. Overall, 31.7%, 38.7% and 30% of the participants had stage 3A, 3B and 4 CKD, respectively, in the intervention group, while 31.7%, 33% and 35% of the participants had stage 3A, 3B and 4 CKD, respectively, in the non-intervention group, not including patients with end-stage renal disease (ESRD). All baseline characteristics were similar between the two groups.

In the Kobe and Diamantidis [ 16 ], study, 18–75 year olds with type 2 diabetes and diabetic nephropathy visited primary care providers at least twice in the previous 3 years. The target sample size was 300 (150 per group), for a total of 281 participants (125 non-African Americans and 156 African Americans); 138 were randomised to the intervention group and 143 to the control group. At baseline, participants had a mean age of 61.9 years and 56% were African American. Most participants had graduated from high school and had a household income of less than $60,000. Participants 18 years or older with a clinical diagnosis of DKD, no cognitive deficit, no terminal illness and not on dialysis were included; 84 individuals were found to be eligible for recruitment. A total of 32 (mean age 67.8 ± 10.8 years; 90.6% men) agreed to participate. On average, the participants had 3.5 comorbidities. The eGFR (mL/min/1.73 m 2 ) ranged from 15–108 mL/min/1.73 m 2 with a mean of 41.3 ± 21.5 mL/min/1.73 m 2 and a median of 35 mL/min/1.73 m 2 .

In the Helou and Talhouedec [ 15 ] study, five participants withdrew. These withdrawals occurred in two sequences which did not start with the intervention directly at enrolment. One participant with stage 4 DKD was excluded from the study because his renal function declined, and he started haemodialysis. Two participants died during the study period.

Intervention

In the Fogelfeld and Hart [ 14 ] study, the intervention was led by a team of endocrinologists, nephrologists, nurse practitioners, registered dietitians and integrated intensive diabetes–renal care with behavioural/dietary and pharmacological interventions. The patients were randomised into eGFR strata on the basis of the baseline estimated eGFRs. The three strata were CKD 3A (eGFR 46–59 ml/min/1.73 m 2 ), CKD 3B (eGFR 30–45 ml/min/1.73 m 2 ) and CKD 4 (eGFR 15–29 ml/min/1.73 m 2 ). A total of 20 consenting patients each were randomised into the following multifactorial–multidisciplinary intervention and control groups: CKD 3A, CKD 3B and CKD 4, resulting in a total of 60 participants in the intervention group and 60 in the control group. The intervention began with group diet instruction based on the guidelines for managing diabetes, dyslipidaemia and renal disease, followed by individual visits with the entire study staff (the endocrinologist, nephrologist, nurse practitioners, certified diabetes educator/dietitian and research coordinator). In addition to the study visits, case management and additional follow-ups were scheduled on the basis of need to promote target achievement.

In the Kobe et al. [ 16 ] study, participants underwent monthly telephone medication evaluations for 36 months and discussed major risk factors for DKD progression, including side effects, communication skills, health behaviours, health knowledge and diabetes self-management.

In the Helou and Talhouedec [ 15 ] study, the intervention group alternated nursing and dietary care with usual nephrology and diabetology consultations to ensure direct or telephone contact every 2 weeks with a healthcare professional. In each intervention period, the participants received two dietary consultations, three nursing consultations at their home or at the ambulatory clinic, and two nursing telephone follow-ups. Each nursing and dietary consultation lasted 1 h, except for the first nursing consultation of each intervention group, which lasted 1.5 h. The advanced practice nurse was responsible for ensuring evidence-based nursing, managing the intervention and coordinating care between healthcare professionals. The nursing intervention was structured on the basis of the self-care deficit nursing theory (SCDNT). It was built using specific nursing assessments, follow-up documentation and educational materials adapted for the purpose of the study. The diabetes-specialised nurse conducted a comprehensive initial clinical and psychosocial assessment of the participant and an evaluation of medication safety; assisted the participant in setting a priority treatment goal and signing a self-management contract to achieve this goal; developed a collaborative care plan and delivered nursing interventions to help the participants meet the set goals; guided participants in symptom monitoring and problem-solving techniques; helped the participants develop their self-care abilities, identify and use their resources, engage in discussions about medication, and follow an exercise regimen (walking at least 90 min per week) and dietary recommendations; monitored the participants’ progress towards the set goals; and provided psychosocial support and education for diabetes and kidney protection. The dietician adopted a self-management approach and established an individualised dietary plan.

Study results

In the Fogelfeld and Hart [ 14 ] study, the primary efficacy endpoint was the development of ESRD defined as eGFR < 15 ml/min/1.73 m 2 that persisted in subsequent tests. Rates of developing ESRD were lower in the intervention group (13%) but higher in the control group (28%). In both groups, ESRD occurred most frequently in patients with baseline CKD ≥ 4 in the control group (33% versus 57%). Moreover, 25 patients with ESRD as compared with the 95 ESRD-free patients had lower baseline eGFR (28.2 ± 10.8 versus 40.0 ± 10.9 ml/min/1.73 m 2 , p  < 0.05) and greater annual median eGFR decline (13.0 versus 3.0 ml/min/year, p  < 0.05); 5.78 (0.1–11.36) 5.2 (1.19–10.17).

In a study by Kobe and Diamantidis [ 16 ], African Americans had a higher eGFR than non-African Americans. African Americans receiving the intervention had a slower mean rate of annual decline in eGFR than that of the control participants [−2.5 mL/min/1.73 m 2 , 95% confidence interval (CI) −3.5, −1.4 versus −4.0 mL/min/1.73 m 2 , 95% CI −5.1, −2.9], while non-African Americans receiving the intervention had a faster decline than the control participants (−3.4 mL/min/1.73 m 2 , 95% CI −4.6, −2.3 versus −1.8 mL/min/1.73 m 2 , 95% CI −2.9, −0.6). There was evidence of a differential intervention effect over time between racial subgroups ( p  = 0.005).

Helou and Talhouedec [ 15 ] assessed QoL, the primary outcome of the study, using the Audit of Diabetes-Dependent Quality of Life (ADDQoL). The intervention group had an improved general QoL of individuals with DKD as compared with the control group, with the highest significant mean rank (52.49 versus 41.01; p  = 0.026, 95% CI), considering a 20% improvement as a clinically significant absolute difference. There were no significant differences in the clinical indicators related to renal function between the intervention and control groups.

The included studies had different intervention durations, and data were pooled using delta eGFR (ml/min/1.73 m 2 /year) to assess its impact on renal failure progression.

In one study, delta eGFR (ml/min/1.73 m 2 /year) could not be extracted and could not be obtained from the authors; therefore, data from two studies where delta eGFR (ml/min/1.73 m 2 /year) could be extracted (201 in the active arm and 200 in the inactive arm, making a total of 401 patients) were statistically pooled (Fig.  3 ).

figure 3

Delta eGFR forest plot for education programs intervention and control groups

The two studies were combined to create a forest plot (Fig.  3 ). When combined, I 2 was 75%, with high heterogeneity in the individual studies in terms of delta eGFR (ml/min/1.73 m 2 /year). The effect size was 0.06, with a confidence interval of –0.34 to 0.45, which was not significant.

Renal function data

In this study, three educational programs for patients with DKD were identified. A meta-analysis of two studies with delta eGFR (ml/min/1.73 m 2 /year) as an outcome showed no significant improvement with educational interventions.

Effect of intervention period

In a study by Fogelfeld and Hart [ 14 ], the 2-year intervention was evaluated every 6 months, and fewer patients in the intervention group (13%) developed ESRD than that in the non-intervention group (28%). However, no statistical differences were observed in eGFR at the end or in the rate of decline in eGFR per year between the intervention and control groups. One of the factors that may have contributed to the lack of effectiveness of the intervention was the duration of the intervention; the three studies had durations from 3 months to 36 months, and no significant differences in eGFR were observed in the studies with a duration of up to 24 months. However, in a study by Kobe et al. [ 16 ], the intervention for African Americans showed a significant difference between eGFR values at baseline and at 36 months, even when no significant difference was observed between the groups at 12 months and 24 months. A previous study [ 11 ] also combined the results of two other studies [ 17 , 18 ] on eGFR, but both had 12- and 24-month intervention periods, and none had more than 36 months of intervention. Educational programs for people with DKD often lead to behavioural changes in patients with DKD, which may result in changes in indicators, such as eGFR. However, it has been suggested that differences in eGFR may take time to develop, and that reductions in renal function decline accumulate over time [ 16 ], suggesting that long-term interventions may be required before the effects of educational programs result in changes in eGFR. Therefore, studies with at least 36 months of long-term intervention may be needed for significant differences to be observed in eGFR change after intervention. Moreover, only three studies on eGFR were eligible, and subgroup analyses by intervention type and duration were not possible; thus, more results are needed to conduct a more detailed analysis.

Only one of the three studies were eligible for examination of the impact of educational programs for patients with DKD on QoL. Hence, the study data could not pooled. Helou and Talhouedec [ 15 ], reported that interventions based on SCDNT improved general QoL. Patients with DKD have been reported to be mainly engaged in QoL and daily self-management. Moreover, implementation of educational programs to support coping with uncertainty improves physical and emotional living conditions [ 15 ]. The effect of an educational program for type 2 diabetes also showed a change in QoL only on the diabetes-specific scale (ADDQoL) and not on the general scale (SF-36), which indicates that in a study of self-management interventions, a general scale such as SF-36 may not be sensitive enough. Furthermore, educational programs have been reported to not improve QoL in the treatment group but prevent the deterioration in the non-treatment group [ 19 ]. Therefore, educational program interventions for patients with DKD may lead to improved QoL, but using ADDQoL as a QoL measure rather than a general scale, such as SF-36, may measure the effect of the interventions. The Kidney Disease Quality of Life-36 Questionnaire (KDQOL-36) is also used as a QoL measure for kidney disease. The KDQOL-36 is used as a QoL measure for dialysis and peritoneal dialysis patients but was not included in this study. Some studies [ 20 ] recommend the use of KDQOL-36 for patients with CKD before dialysis because of its internal consistency and validity, and it may be beneficial to use KDQOL-36 as a QoL measure for patients with DKD. There are few RCTs using QoL as an outcome in patients with DKD, and further studies and meta-analyses are needed to show that educational programs lead to improved QoL.

Contents to be considered in the development of educational programs

Frequency of intervention.

In three studies [ 14 , 15 , 16 ], the frequency of interventions varied from once every 2 weeks to once every month. Therefore, no effective intervention frequency was identified. In a study by Dong and Li [ 21 ], albumin creatinine ratio continued to improve with biweekly interventions, but worsened with monthly interventions, suggesting that more frequent interventions may be more effective.

In two studies [ 14 , 15 ], multi-professional interventions were performed; in one study [ 16 ], interventions were performed only by pharmacists. Although we were unable to identify the effect of interventions by different intervenors, multi-professional and team interventions may be effective.

Content of intervention (effect of remote intervention)

Two of the three studies involved remote interventions via telephone. Kobe et al. [ 16 ] found that monthly telephone educational interventions resulted in an improvement in the eGFR in African Americans at 36 months. In the Fogelfeld et al. study [ 14 ], frequent telephone contact and case management by researchers resulted in less ESRD in the intervention group (13%) than that in the non-intervention group (28%) among patients who required intensive follow-up. Prior research on remote interventions included an RCT comparing a self-management education program for patients with diabetic nephropathy in a face-to-face interview group and a remote tablet-based interview group. The self-management behaviour score at 12 months after enrolment was higher than that at the time of enrolment. Furthermore, the effect of the intervention on behaviour modification was observed before and after the intervention in each group, and differences were observed on the basis of interview methods [ 22 ]. El-Gayar, Ofori and Nawar [ 23 ] reported that the meta-analysis using a mobile health app with patients with diabetes identified 21 studies, wherein interventions using mobile health apps were more likely to lead to improvements in participants’ HbA1c levels as compared with those with standard care. Joboshi and Oka [ 24 ] conducted a RCT on the effectiveness of the EASE program in patients with CKD. In addition to monthly interviews, patients received support by phone or e-mail once a week to once every 2 weeks. If the interval between outpatient visits was longer than 1 month, the patients were evaluated by phone or e-mail. The results showed improvements in self-efficacy awareness and self-management behaviours. Without continuous supervision and management, it is difficult to change unhealthy lifestyles, and effective supervision is important to maintain changes in patients’ lifestyles [ 21 ]. Therefore, it is useful to establish a comprehensive program that provides information, guidance and continuous support. In addition to face-to-face interviews, the combination of remote interventions, such as phone calls, videophones and mobile health apps, provides ongoing support with less burden on both patients and healthcare professionals, promotes patients behaviour change and may lead to improvements in eGFR and QoL.

Strengths and limitations

The strength of this study is that it addresses the content of the educational programs, including the duration and frequency of interventions, utility of remote intervention and QoL measures, for the development of an effective educational program for people with DKD.

Limitations of the study include that grey literature was not searched and the possibility that unpublished literature was not included. The small number of included studies did not allow for evaluation of publication bias by funnel plots, data extraction and bias evaluation were performed by one person and may have resulted in bias, and the small number of references identified in this study did not allow for subgroup analysis. In addition, it is difficult to derive consistent results owing to the diversity of intervention methods in the literature identified in this study. In the future, as the number of studies increases and subgroup analyses become available, it may be possible to analyse the effects of different interventions.

The systematic review and meta-analysis was conducted according to the PRISMA 2020 statement using Revman5.4 and sensitivity analysis. Two RCTs and one randomised crossover trial were eligible; of these, two studies with delta eGFR (ml/min/1.73 m 2 /year) as an outcome were pooled using a meta-analysis, which showed high statistical heterogeneity, but sensitivity analysis using a random-effects model showed no significant effect with a pooled effect size of 0.06 (−0.34 to 0.45; 95% CIs). The effect on QoL was observed in only one of the three studies; hence, they could not pooled. The lack of significant results in terms of eGFR may have been due to the short duration of the intervention, suggesting that an intervention of at least 36 months is required to improve eGFR with an educational program. For QoL outcomes, using the ADDQoL and KDQOL-36 as disease-specific measures may provide sufficient sensitivity. In the future, as the number of studies increases, we may be able to evaluate effective educational programs through subgroup analyses such as the duration and frequency of the interventions.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the repository, [ https://www.sciencedirect.com/science/article/abs/pii/S1056872716309783?via%3Dihub ], [ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408890/ ], [ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7572637/ ].

Abbreviations

Audit of diabetes-dependent quality of life

Confidence interval

Chronic kidney disease

  • Diabetic kidney disease
  • Estimated glomerular filtration rate

End-stage renal disease

Kidney disease quality of life-36 questionnaire

Randomised controlled trials

Cochrane risk of bias tool 2

Self-care deficit nursing theory

  • Quality of life

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This work was supported by JSPS KAKENHI Grant Number 20K10707. The authors would like to thank the staff who supported this study

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Kemmochi, T., Oka, M., Inokuma, A. et al. Effectiveness of educational programs for patients with diabetic kidney disease: a systematic review and meta-analysis. Ren Replace Ther 10 , 38 (2024). https://doi.org/10.1186/s41100-024-00554-y

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Diet and Kidney Function: a Literature Review

A. c. van westing.

Division of Human Nutrition and Health, Wageningen University, Stippeneng 4, 6708 WE Wageningen, The Netherlands

L. K. Küpers

J. m. geleijnse, associated data, purpose of review.

The burden of chronic kidney disease (CKD) is increasing worldwide. For CKD prevention, it is important to gain insight in commonly consumed foods and beverages in relation to kidney function.

Recent Findings

We included 21 papers of prospective cohort studies with 3–24 years of follow-up. We focused on meat, fish, dairy, vegetables, fruit, coffee, tea, soft drinks, and dietary patterns. There was convincing evidence that a healthy dietary pattern may lower CKD risk. Plant-based foods, coffee, and dairy may be beneficial. Unhealthy diets and their components, such as red (processed) meat and sugar-sweetened beverages, may promote kidney function loss. For other foods and beverages, associations with CKD were neutral and/or the number of studies was too limited to draw conclusions.

Healthy dietary patterns are associated with a lower risk of CKD. More research is needed into the effects of specific food groups and beverages on kidney function.

Electronic supplementary material

The online version of this article (10.1007/s11906-020-1020-1) contains supplementary material, which is available to authorized users.

Introduction

Chronic kidney disease (CKD) is a major public health burden [ 1 , 2 ], with a global prevalence of ~ 11% in the general adult population [ 1 ]. If left untreated, CKD slowly progresses to end-stage renal disease, which requires dialysis or kidney transplant [ 2 , 3 ]. CKD is bidirectionally associated with cardiovascular diseases (CVD) [ 4 , 5 ]. Hypertension [ 6 ] and type 2 diabetes mellitus (T2DM) [ 7 , 8 ] are independent risk factors for CKD [ 6 , 7 ], and their global prevalences are increasing [ 9 , 10 ], which will likely impact CKD. Worldwide, a 31.7% increase of CKD mortality was observed over the last decade [ 11 ].

Lifestyle factors, including smoking [ 12 ], alcohol use [ 13 ], and physical inactivity [ 14 ], could promote CKD. Apart from that, there is increasing scientific interest in the potential role of diet [ 15 , 16 ]. High salt intake is an established risk factor for kidney function decline [ 17 , 18 ], mainly through its adverse effect on blood pressure and vascular health [ 19 – 21 ]. Less is known about other dietary factors. Therefore, we reviewed the current evidence on foods, beverages, and overall dietary quality in relation to the risk of incident CKD using data from prospective cohort studies.

We performed a comprehensive search in PubMed of papers published until August 2019 describing prospective cohort studies, supplemented by manual searches of reference lists from appropriate studies. The review is based on prospective cohort studies with at least 3 years of follow-up that reported on the relation between food groups, beverages, and dietary patterns and kidney function in populations free from CKD (defined as mean estimated glomerular filtration rate (eGFR) > 60 ml/min/1.73 m 2 ).

Foods of interest were red (processed) meat, poultry, fish, dairy, vegetables, legumes, nuts, and fruits. Beverages included coffee, tea, sugar-sweetened beverages (SSBs), and diet beverages. Dietary patterns included adherence to the Dietary Approach to Stop Hypertension (DASH) diet, Mediterranean diet, and other healthy dietary patterns. Unhealthy diets were high fat, high sugar diets, and diets with a high acid load.

Concerning kidney function, we selected studies with data on the eGFR, derived from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [ 22 , 23 ] and Modification of Diet in Renal Disease (MDRD) [ 24 ].

Reasons for exclusion of articles were studies with (1) follow-up less than 3 years, (2) study design other than prospective cohort study, (3) study population with T2DM and analgesic use, (4) no full-text available, and (5) focus on end-stage renal disease. The selection process is shown in eFig. 1 .

From selected papers, we extracted data on population characteristics, study design, intakes of foods and/or beverages, kidney function outcomes, risk estimates for diet-kidney function associations, and potential confounders.

The primary outcome for this review was “incident CKD” based on eGFR cutoff criteria, described in eTable 1 . Associations between foods, beverages, and incident CKD in different studies were expressed as odds ratios (OR), obtained from logistic regression analysis, or hazard ratios (HR), obtained from Cox proportional hazard analysis with corresponding 95% confidence intervals (CI). In this review, OR and HR are both denoted as relative risks (RRs). Continuous associations between food groups, beverages, and change in eGFR are expressed as beta regression coefficients, obtained from multivariable linear regression.

RRs and betas from fully adjusted models are reported in tables with potential confounders. When these models included possible intermediates (i.e., factors could play a role in the biological pathway), risk estimates from less adjusted models are given. Two-sided P values < 0.05 for risk estimates were considered statistically significant.

An overview of studies of foods, beverages, and dietary patterns and their associations with incident CKD is presented in eTable 1 . Studies that focused on eGFR change, albuminuria, or hyperuricemia are described in eTable 2 and eTable 3 . Graphical displays of the point estimates with 95% CI related to incident CKD using forest plots are presented in Figs.  1 , ​ ,2, 2 , and ​ and3 3 .

An external file that holds a picture, illustration, etc.
Object name is 11906_2020_1020_Fig1_HTML.jpg

Forest plot for associations between commonly consumed foods and incident chronic kidney disease

An external file that holds a picture, illustration, etc.
Object name is 11906_2020_1020_Fig2_HTML.jpg

Forest plot for associations between commonly consumed beverages and incident chronic kidney disease. SSB, sugar-sweetened beverages

An external file that holds a picture, illustration, etc.
Object name is 11906_2020_1020_Fig3_HTML.jpg

Forest plot for associations between dietary patterns and incident chronic kidney disease. DASH, Dietary Approach to Stop Hypertension

Two studies evaluated the consumption of red (processed) meat and poultry in relation to incident CKD (Fig.  1 ) [ 25 ••, 26 ••]. Red meat intake in these studies varied between 0.17 to 0.34 servings per day (low intake) and 1.15 to 2.52 servings per day (high intake). In the Atherosclerosis Risk in Communities (ARIC) study of ~ 12,000 US participants with 23 years of follow-up, a total of 2632 participants developed CKD [ 25 ••]. In this population, the HR for high versus low intake of red meat and CKD risk was 1.19 (95% CI, 1.03; 1.36; Fig.  1 ) [ 25 ••]. In a study of 4881 Iranian participants followed for 3 years, 613 participants developed CKD with an OR of 1.73 (95% CI, 1.33; 2.24) for high versus low red meat intake (Fig.  1 ) [ 26 ••]. Findings for processed meat were similar to those for red meat in both studies, and no significant associations with kidney function were found for poultry (Fig.  1 ) [ 25 ••].

Two studies evaluated the association between fish consumption and incident CKD (Fig.  1 ) [ 25 ••, 27 ]. The Strong Heart Study among American Indians followed 2261 participants for 5.4 years of whom 4% developed CKD. Fish intake was analyzed in four categories ranging from 0 to > 15 g per day [ 27 ]. No significant associations were found with an OR of 1.46 (95% CI, 0.65; 3.26) for high versus zero fish intake [ 27 ]. In the ARIC study [ 25 ••], fish intake was analyzed in quintiles ranging from 0.07 to 0.64 servings per day. A borderline significant HR of 0.89 (95% CI, 0.78; 1.01) was found in the upper versus lower quintile of intake (Fig.  1 ) [ 25 ••].

Dairy consumption and incident CKD were examined in the ARIC study among US individuals (Fig.  1 ) [ 25 ••]. Intake of low-fat dairy ranged from 0.00 to 2.04 servings per day and intake of high-fat dairy from 0.13 to 1.61 servings per day [ 25 ••]. A significantly lower risk of CKD was found for low-fat dairy intake, with a HR of 0.75 (95% CI, 0.65; 0.85) for high versus low intake. High-fat dairy intake was also inversely associated with CKD, albeit non-significant (Fig.  1 ) [ 25 ••].

We found 3 studies of vegetable intake and CKD risk (Fig.  1 ) [ 28 •, 29 ••, 30 ]. In a study of 1780 Iranians from the Tehran Lipid Glucose Study (TLGS), followed for 6 years, 319 participants developed CKD [ 28 •]. Allium vegetable intake was analyzed in tertiles ranging from 1 to 39 g per week [ 28 •]. A significant inverse association with CKD risk was found, with a HR of 0.68 (95% CI, 0.48; 0.98) in the upper versus lower tertiles of intake [ 28 •]. In 9229 participants from the Korean Genome and Epidemiology Study, 1741 incident CKD cases were reported during 8.2 years [ 29 ••]. Intake of non-fermented vegetables ranged from 49 to 222 g per day, and intake of fermented vegetables from 164 to 227 g per day [ 29 ••]. Non-fermented vegetables were inversely related to CKD risk, with a HR of 0.86 (95% CI, 0.76; 0.98) for high versus low intake (Fig.  1 ) [ 29 ••]. For fermented vegetables, an inverse but non-significant association was found (Fig.  1 ) [ 29 ••]. In the abovementioned TLGS, nitrate-containing vegetable intake ranged from 146 to 428 g per day [ 30 ]. No significant association with CKD risk was found after 3 years of follow-up (Fig.  1 ) [ 30 ].

Legumes and Nuts

In the ARIC study with 23 years of follow-up, legume intake ranged from 0.07 to 0.68 servings per day and nut intake ranged from 0.03 to 0.86 servings per day [ 25 ••]. Both legumes and nuts were significantly associated with lower risks of CKD, with HRs of 0.83 (95% CI, 0.72; 0.95) and 0.81 (95% CI, 0.72; 0.92) for high versus low intakes, respectively (Fig.  1 ) [ 25 ••].

One study in 9229 South Koreans, followed for 8.2 years, reported on fruit consumption and incident CKD [ 29 ••]. Fruit intake ranged from 143 to 345 g per day and showed no association with incident CKD (HR of 1.00) (Fig.  1 ) [ 29 ••].

Three studies examined coffee consumption and incident CKD (Fig.  2 ) [ 31 – 33 ]. The Iranian TLGS compared coffee drinkers (median intake 8.3 ml per day) to non-drinkers [ 31 ]. In the ARIC study in the USA [ 32 ] and the Korean Genome and Epidemiology Study in South Korea [ 33 ], those drinking at least 3 cups [ 32 ] or at least 2 cups [ 33 ] were compared with non-coffee drinkers. In the Iranian study, a non-significant direct association between coffee and CKD was found [ 31 ], whereas in the US and Korean studies, significant inverse associations were observed in those with higher coffee intakes, with HR of 0.84 [ 32 ] and 0.80 [ 33 ], respectively (Fig.  2 ).

The Iranian TLGS also reported on tea consumption, ranging from < 250 ml (low intake) to > 750 ml per day (high intake) (Fig.  2 ) [ 31 ]. Unfortunately, data on the type of tea and its preparation method was not collected [ 31 ]. However, a previous study reported that in Iran, black tea is often consumed [ 34 ] with added sweets and sugar, including a variety of additives [ 31 ]. No significant association with incident CKD was found (Fig.  2 ) [ 31 ].

Soft Drinks

Three studies reported on SSBs and incident CKD (Fig.  2 ) [ 35 – 37 ], of which one American study also reported on diet beverages (Fig.  2 ) [ 36 ]. In the ARIC study with 9 years of follow-up, consumption of SSB (cutoff 1 drink per day) was not significantly associated with CKD risk [ 35 ]. In the Jackson Heart Study (3003 participants, 185 CKD cases) with 8 years of follow-up, a direct, non-significant association of SSB with CKD risk was found [ 36 ]. In the Iranian TLGS, SSB consumption ranged from < 0.5 to > 4 servings per week [ 37 ]. A significantly elevated risk of CKD was found when comparing high with low intakes, with an OR (95% CI) of 1.92 (1.05; 3.48) (Fig.  2 ) [ 37 ]. Diet beverages were studied in the Jackson Heart Study and showed no significant association with CKD risk (Fig.  2 ) [ 36 ].

Dietary Patterns

Healthy diets.

A number of studies examined healthy dietary patterns and incident CKD [ 38 , 39 , 40 •, 41 , 42 ••, 43 , 44 ], including the DASH diet [ 39 , 40 •, 41 ], Mediterranean diet [ 38 , 42 ••], and other healthy dietary patterns [ 42 ••, 43 , 44 ], for which findings are shown in Fig.  3 . The DASH diet was examined in the Healthy Aging in Neighborhoods of Diversity across the Life Span cohort with 5 years of follow-up [ 40 •], in the ARIC study with 23 years of follow-up [ 41 ] and in the Iranian TLGS with 6.1 years of follow-up [ 39 ]. All studies suggested a beneficial effect of the DASH diet, with RRs between 0.41 and 0.86 for high versus low adherence (Fig.  3 ). The association was statistically significant for 2 studies [ 39 , 41 ].

Mediterranean diet scores were examined in the Northern Manhattan Study [ 38 ] and ARIC study [ 42 ••], with 6.9 years [ 38 ] and 24 years [ 42 ••] of follow-up, respectively. Reduced RRs of 0.50 [ 38 ] and 0.89 [ 42 ••] were found for high versus low adherence, which were significant for both studies (Fig.  3 ).

The ARIC study also examined [ 42 ••] adherence to healthy dietary patterns assessed using the Healthy Eating Index-2015 (HEI-2015) and the alternative HEI-2010 [ 42 ••]. The HEI-2015 was designed to assess adherence to US Dietary Guidelines for Americans [ 45 ], while the alternative HEI-2010 was designed to identify key components associated with chronic diseases [ 46 ]. For both diet quality scores, significantly lower risks of CKD were found for higher adherence, with RRs of 0.86 and 0.81, respectively (Fig.  3 ) [ 42 ••].

In the ARIC study with 22 years of follow-up, the Healthy Diet Score based on American Heart Association’s Life’s Simple 7 was studied, which appeared not to be associated with incident CKD [ 43 ]. In the Framingham Offspring cohort followed for 6.6 years (1802 participants, 171 CKD cases), the Dietary Guidelines Adherence Index was borderline significantly inversely associated with CKD risk [ 44 ].

Healthy dietary patterns were also beneficially associated with other renal function outcomes, such as rapid eGFR decline [ 40 •, 44 ] and ≥ 25% eGFR decline [ 40 •] (Supplementary material; eTable 1 ).

Unhealthy Diets

Two studies reported on unhealthy dietary patterns and incident CKD (Fig.  3 ) [ 47 , 48 ]. In the TLGS, a high-fat, high-sugar diet was related to a significantly higher risk of CKD, with OR of 1.46 [ 47 ]. In participants of the ARIC study, an increased HR of 1.13 was found for a diet with a high acid load (12.2 to 100.7 mEq per day), which is characterized by high levels of salt, animal protein, and phosphorus, compared with a low acid load (− 119.1 to − 3.2 mEq per day).

This review of 21 prospective cohort studies among individuals with (relatively) normal kidney function shows a consistently lower risk of CKD in those adhering to a healthy dietary pattern [ 38 , 39 , 40 •, 41 , 42 ••, 43 , 44 ]. For individual food groups and beverages, the observed associations were more variable and weaker. We found adverse associations for red (processed) meat and SSBs in some studies and beneficial associations for dairy, vegetables, legumes, and nuts.

Two recent reviews have indicated that healthy dietary patterns may prevent incident CKD [ 15 , 16 ]. Ajjarapu et al. included 26 prospective cohort studies and found that adherence to a DASH or Mediterranean diet may be useful to prevent CKD [ 16 ]. Similar results were found in a meta-analysis of 15 prospective and retrospective cohort studies performed by Bach et al. [ 15 ]. A low animal/vegetable protein ratio is often considered an indicator of a healthy dietary pattern. In this regard, the ARIC study [ 25 ••] showed that after 23 years of follow-up, high (> 22.8 g per day) versus low (< 12.1 g per day) intake of vegetable protein was significantly associated with lower risk of CKD, whereas no association was found for high (> 69.6 g per day) versus low (< 36.4 g per day) intake of animal protein [ 25 ••]. Similar results on animal protein intake were found in 1135 participants with normal renal function (defined as eGFR > 80 ml/min/1.73 m 2 ) from the Nurses’ Health Study [ 49 ].

A lower risk of incident CKD for those consuming more vegetables and legumes may partly be attributable to fiber, as shown in a study among Iranian TLGS participants, with 6.1 years of follow-up [ 50 ]. Consumption of whole grains has also been linked to less kidney function decline in the Doetinchem Study in The Netherlands, with 15 years of follow-up [ 51 ]. In a study of vegetables and fruit intake in relation to kidney function decline, assessed by the annual change in eGFR, inverse associations were found [ 51 ] (Supplementary material; eTable 2 ), which strengthens our findings on healthy dietary patterns.

We found no association of CKD with fish intake, which is often considered part of a healthy diet. This was confirmed in another study among American Indians with 5.4 years of follow-up, where fish intake was not related to change in kidney function [ 27 ] (Supplementary material; eTable 2 ). For poultry, we could only include one study, and more research is needed.

Our results for coffee, indicating a potentially protective effect, are also in line with the results from a study on kidney function change [ 52 ] (Supplementary material; eTable 2 ). In this study, the coffee was mainly caffeinated [ 52 ] and likely to be filtered. The Iranian study suggested an increased, albeit non-significant, risk of CKD, which could be attributable to the regularly consumed unfiltered type of coffee in this country [ 31 ]. However, more information regarding the type of coffee and its preparation methods is needed, including amounts of added sugar and other condiments, before results can be correctly interpreted. We found no beneficial associations for tea and incident CKD, which was in line with the results from a Dutch study on kidney function decline [ 52 ] (Supplementary material; eTable 2 ). However, our review included only one study on incident CKD from Iran [ 31 ]. More information about the types of tea in relation to kidney function, including amounts of added sugar, is needed before drawing conclusions.

For low-fat dairy products and incident CKD, we found some evidence for a potentially protective effect on kidney function, though based on only one study [ 25 ••]. This is in line with a study in Dutch participants in which less kidney function loss was found during 15 years of follow-up who consumed more milk and low-fat dairy [ 53 ] (Supplementary material; eTable 2 ).

With regard to other kidney function outcomes (Supplementary material; eTable 3 ), studies on the risk of albuminuria [ 27 , 35 , 54 , 55 ] and hyperuricemia [ 35 ] were in accordance with those for CKD. A higher, albeit non-significant risk of hyperuricemia was found for high versus low SSB consumption [ 35 ]. Also, a good versus poor diet quality, based on eight fundamental DASH diet components, was associated with a lower risk of incident microalbuminuria [ 55 ], and fruit intake was related to a lower risk of albuminuria [ 54 ]. Fish intake was not associated with albuminuria [ 27 , 56 ].

To summarize, this review shows that a healthy dietary pattern may help prevent kidney function decline and lower the risk of CKD. The number of studies of individual foods and beverages in this field, however, is limited and most of the evidence comes from a limited number of cohorts. More research on the components of healthy (and unhealthy) diets and indicators of kidney health in different populations is needed to fill these knowledge gaps.

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The research presented in this paper has been funded by the Jaap Schouten Foundation (JSF_SU_10_2018).

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    ImportanceChronic kidney disease (CKD) is the 16th leading cause of years of life lost worldwide. Appropriate screening, diagnosis, and management by primary care clinicians are necessary to prevent adverse CKD-associated outcomes, including cardiovascular disease, end-stage kidney disease, and death. ObservationsDefined as a persistent ...

  11. Global Prevalence of Chronic Kidney Disease

    Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking ...

  12. Treatment of chronic kidney disease in older populations

    Liyanage, T. et al. Worldwide access to treatment for end-stage kidney disease: a systematic review. Lancet 385 , 1975-1982 (2015). Article PubMed Google Scholar

  13. A Systematic Review of the Literature on Chronic Kidney Disease

    Chronic kidney disease (CKD) is a serious comorbidity affecting liver transplant recipients (LTRs). Calcineurin inhibitor dosing minimization protocols and everolimus use purportedly increased from 2010, potentially impacting CKD development. This systematic literature review was designed to identify CKD incidence in adult LTRs, focusing on ...

  14. Treatments for Chronic Kidney Disease: A Systematic Literature Review

    Delaying disease progression and reducing the risk of mortality are key goals in the treatment of chronic kidney disease (CKD). New drug classes to augment renin-angiotensin-aldosterone system (RAAS) inhibitors as the standard of care have scarcely met their primary endpoints until recently. This systematic literature review explored treatments evaluated in patients with CKD since 1990 to ...

  15. A Narrative Review of Chronic Kidney Disease in Clinical Practice

    Chronic kidney disease (CKD) is a complex disease which affects approximately 13% of the world's population. Over time, CKD can cause renal dysfunction and progression to end-stage kidney disease and cardiovascular disease. Complications associated with CKD may contribute to the acceleration of disease progression and the risk of cardiovascular-related morbidities. Early CKD is asymptomatic ...

  16. A Systematic Review of the Literature on Chronic Kidney Disease

    Background. Chronic kidney disease (CKD) is one of the main comorbidities affecting liver transplant recipients [].Kidney disease is diagnosed in 20-25% of patients with liver disease [] and can be due to pathological conditions affecting both the kidney and the liver (eg, sarcoidosis or diabetes), or a complication of certain liver diseases, such as hepatitis B, hepatitis C, or alcoholic ...

  17. [PDF] Association between Proton Pump Inhibitor Use and Risk of

    Our study aimed to investigate the relationship between PPI use and the incidence of chronic kidney disease using a systematic review and meta-analysis. Methods: We performed a comprehensive literature search in PubMed, Embase, and Cochrane databases from their inception until March 2024 for relevant studies.

  18. Health related quality of life utility weights for economic evaluation

    Chronic kidney disease (CKD) has a substantial impact on patients' health and life expectancy. CKD has been estimated to affect between 10 and 15% of the population in the U.S. and Canada [1, 2].CKD can be a progressive disease and the leading causes include diabetes (38%), high blood pressure (26%), and glomerulonephritis (16%) [].Progression to end-stage renal disease (ESRD) leaves the ...

  19. Targeted Literature Review of the Burden of Illness in Patients ...

    Chronic kidney disease in US adults with type 2 diabetes: an updated national estimate of prevalence based on Kidney Disease: Improving Global Outcomes (KDIGO) staging. BMC Res Notes . 2014;7:415 ...

  20. Managing Heart Failure in Chronic Kidney Disease: A Review of Current

    DOI: 10.1007/s11936-024-01048- Corpus ID: 270952644; Managing Heart Failure in Chronic Kidney Disease: A Review of Current Literature @article{Lidgard2024ManagingHF, title={Managing Heart Failure in Chronic Kidney Disease: A Review of Current Literature}, author={Benjamin Lidgard and Nisha Bansal}, journal={Current Treatment Options in Cardiovascular Medicine}, year={2024}, url={https://api ...

  21. Comparative efficacy of exercise modalities for general risk factors

    Background: Exercise therapy can effectively manage chronic kidney disease (CKD) risk factors and improve renal function and physical fitness, but the challenge lies in choosing the right exercise type tailored to patients' condition. Methods: An electronic search of databases including PubMed, The Cochrane Library, EMBASE, Web of Science, VIP, WanFang, and CNKI was performed.

  22. PDF Treatments for Chronic Kidney Disease: A Systematic Literature Review

    of chronic kidney disease (CKD). New drug classes to augment renin-angiotensin-aldos-terone system (RAAS) inhibitors as the standard of care have scarcely met their primary end-points until recently. This systematic literature review explored treatments evaluated in patients with CKD since 1990 to understand what contemporary data add to ...

  23. Treatments for Chronic Kidney Disease: A Systematic Literature Review

    This systematic literature review explored treatments evaluated in patients with CKD since 1990 to understand what contemporary data add to the treatment landscape.

  24. Full article: Comparative efficacy of exercise modalities for general

    Literature screening process and basic characteristics of the included RCTs. The initial search yielded 2,186 publications, ... Thompson S, Wiebe N, Padwal RS, et al. The effect of exercise on blood pressure in chronic kidney disease: a systematic review and meta-analysis of randomized controlled trials. PLoS One. 2019;14:e0211032. doi: ...

  25. Frontiers

    We conducted a systematic literature search according to the Preferred Reporting Items for Systematic ... (2024) Hypoxia-inducible factor-prolyl hydroxylase inhibitors for treatment of anemia in chronic kidney disease: a systematic review and network meta-analysis. Front. Pharmacol. 15:1406588. doi: 10.3389/fphar.2024.1406588. Received: 25 ...

  26. A systematic review of the drug-drug interaction between Statins and

    This systematic review aims to characterize data regarding patients affected by the statin-quinolone interaction. ... guidelines for systematic reviews. A literature search of the following databases was performed: PubMed (Medline), Embase, Scopus, and Cochrane library. ... a report from the managing Dyslipidemias in Chronic Kidney Disease Work ...

  27. Economic Modelling of Chronic Kidney Disease: A Systematic Literature

    Background: Chronic kidney disease (CKD) is a progressive condition that leads to irreversible damage to the kidneys and is associated with an increased incidence of cardiovascular events and mortality. As novel interventions become available, estimates of economic and clinical outcomes are needed to guide payer reimbursement decisions.

  28. Effectiveness of educational programs for patients with diabetic kidney

    To prevent the progression of diabetic nephropathy, educational programs to improve self-management are important. However, the effectiveness of educational programs to prevent worsening of diabetic kidney disease on renal function and quality of life is under characterised. The purpose of this study was to conduct a systematic review and meta-analysis to identify effective educational ...

  29. Predict, diagnose, and treat chronic kidney disease with machine

    Introduction. Chronic Kidney Disease (CKD) is a state of progressive loss of kidney function ultimately resulting in the need for renal replacement therapy (dialysis or transplantation) [].It is defined as the presence of kidney damage or an estimated glomerular filtration rate less than 60 ml/min per 1.73 m 2, persisting for 3 months or more []. ...

  30. Diet and Kidney Function: a Literature Review

    Introduction. Chronic kidney disease (CKD) is a major public health burden [1, 2], with a global prevalence of ~ 11% in the general adult population [].If left untreated, CKD slowly progresses to end-stage renal disease, which requires dialysis or kidney transplant [2, 3].CKD is bidirectionally associated with cardiovascular diseases (CVD) [4, 5]. ...