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Evidence reviews for cystatin C based equations to estimate GFR in adults, children and young people

Chronic kidney disease

Evidence review M

NICE Guideline, No. 203

London: National Institute for Health and Care Excellence (NICE); .
ISBN-13: 978-1-4731-4233-6

Cystatin C based equations to estimated GFR

1.1. Review question

What is the accuracy of cystatin C-based equations to estimate GFR as a measurement of kidney function in adults, children and young people?

1.1.1. Introduction

The glomerular filtration rate (GFR) is equal to the sum of the filtration rates in all of the functioning nephrons and is the best index of overall kidney function. Knowledge of GFR is essential for the diagnosis and management of CKD, with a normal GFR being approximately 100 ml/min/1.73 m2.

The gold standard methods of assessing GFR require measurement of an ideal filtration marker, typically using markers such inulin, 51Cr-EDTA, 99mTc-DTPA, 125I-iothalamate and iohexol. However, gold standard methods of assessing GFR are technically demanding, expensive, time-consuming and unsuitable for widespread identification of CKD in the ‘at risk’ population. Estimates of GFR can be obtained using serum creatinine, which is a universally available endogenous test of kidney function. Various equations have been constructed that allow conversion of serum creatinine levels (sometimes along with demographic information such as age and sex) to GFR.

More recently, plasma cystatin-C has been introduced as an alternative endogenous marker. Cystatin C is a 13 kDa cationic protein produced by all nucleated cells and plasma cystatin C concentrations are chiefly determined by GFR. Previous NICE guidance reviewed the evidence for cystatin C equations for adults and recommended that an eGFR measurement using cystatin C should be considered to confirm or rule out CKD in people with an eGFR (according to a creatinine-based equation) of 45-59 ml/min/1.73 m2, sustained for at least 90 days, without proteinuria or other markers of kidney disease. Additionally, NICE recommended that whenever a request for serum cystatin C measurement is made, clinical laboratories should report an estimate of GFR using the CKD-EPI equation. However, this guideline did not look at evidence for children and young people and new cystatin-based eGFR equations have been evaluated in adults, children and young people since this guideline was published and therefore that was the main aim of this review.

1.1.2. Summary of the protocol

Table 1. PICO table for the accuracy of cystatin C-based equations to estimate GFR.

Table 1

PICO table for the accuracy of cystatin C-based equations to estimate GFR.

1.1.3. Methods and process

This evidence review was developed using the methods and process described in Developing NICE guidelines: the manual. Methods specific to this review question are described in the review protocol in Appendix A and the methods section in Appendix B.

Declarations of interest were recorded according to NICE’s conflicts of interest policy.

Protocol deviation

Due to limited data for the outcomes specified in the review protocol, the committee agreed that the included outcomes should be expanded to include P values. P values refer to the percentage of participants with an index test value (eGFR score) sufficiently close to their score on the reference standard (mGFR). P values below P50 were deemed useful for decision making and data were found for P10, P15 and P30 (referring to the percentage of the total sample who had an index test score within 10%, 15% and 30% of their reference standard score, respectively).

Studies have demonstrated that eGFR equations have different levels of accuracy when applied to different ethnic groups. In the previous NICE guideline, studies were excluded if they contained a population of participants considerably different from the UK (for example, studies conducted in China only including Chinese participants). The committee agreed that these studies should also be excluded from the present review.

GRADE was not used in this review because imprecision could not be evaluated using P10, P15, P30 and AUC as minimal clinically important differences could not be used for these accuracy values.

1.1.4. Diagnostic evidence

1.1.4.1. Included studies

A systematic literature search for diagnostic cross-sectional studies and systematic reviews of diagnostic cross-sectional studies was conducted for this review. This returned 2,694 references (see Appendix C for literature search strategy). Based on title and abstract screening against the review protocol, 2,610 references were excluded, and 84 references were ordered for screening based on their full texts.

Of the 84 references screened as full texts, only 5 cross sectional studies met the inclusion criteria specified in the review protocol for this question (Appendix A) and therefore a decision was made to include cohort studies. Nine cohort studies were found (7 retrospective and 2 prospective) bringing the total number of included papers to 14. The clinical evidence study selection is presented as a diagram in 0.

A second set of searches was conducted at the end of the guideline development process for all updated review questions using the original search strategies, to capture papers published whilst the guideline was being developed. This search returned 238 references for this review question, these were screened on title and abstract. Four references were ordered for full text screening. None of these references were included based on their relevance to the review protocol (Appendix A).

See section 1.1.12 References – included studies for a list of references of included studies.

1.1.4.2. Excluded studies

See Appendix K for a list of excluded studies with the primary reason for exclusion.

1.1.5. Summary of studies included in the diagnostic evidence

A summary of the studies included in this review can be found in Table 2 and a summary of the different cystatin c-equations can be found in Table 3.

Table 2. Summary of studies included in this review.

Table 2

Summary of studies included in this review.

See Appendix E for full evidence tables.

Table 3. Summary of cystatin-c equations.

Table 3

Summary of cystatin-c equations.

1.1.6. Summary of the diagnostic evidence

Table 4 was considered to be the most appropriate way to summarise the evidence and as a result, evidence statements have not been written for this evidence. None of the included studies could be combined to produce a pooled effect estimate. Therefore, results are presented per study.

Table 4. Summary of the diagnostic evidence by equation, population and outcomes.

Table 4

Summary of the diagnostic evidence by equation, population and outcomes.

See Appendix G for full GRADE tables for likelihood ratio outcomes.

1.1.7. Economic evidence

A systematic review was conducted to identify economic evaluations for this review question. The search returned 338 records which were sifted against the review protocol and 337 records were excluded based on title and abstract. One record was included after the full text review. Additionally, modelling was undertaken for this review question in the 2014 update of the NICE CKD guideline. This review question was not prioritised for modelling in the 2020 update of the guideline, so this analysis has not been updated. The results of this 2014 model have therefore been included in the guideline in the same way as those from a published journal article.

1.1.7.1. Included studies

A summary of the studies included in the cost-effective review is given below. Detailed information on the studies from the review can be found in Appendix I, and the study selection is described in Appendix H.

In the 2014 update of the NICE CKD guideline it was decided that this review question was important to model. However, in the current update it was decided that the model would not be updated. This is due to the difficulty of modelling the consequences of inaccurate eGFR measurements, and the fact this question was regarded as being of lower priority than the questions on phosphate binders and referral to secondary care. The model in 2014 showed that using eGFRcystatin C was cost saving as it reduces the number of false positives identified compared to using creatinine alone, and this was part of the justification for why the committee decided to introduce the test to the recommendations at that time. However, the 2014 recommendations were tested in a 2017 publication which found that they were not cost saving. The 2014 model also included sensitivity and specificity data that was excluded in the current review, (either due to the population not fitting the current protocol, or it not being clear that the population had CKD). This reduces the confidence in the results of the 2014 analysis, as there is less confidence in the inputs into the model, since we no longer believe the clinical data used are fully applicable. The full model is in Error! Reference source not found..

One subsequently published study by Shardlow et al (2017). compared different testing and monitoring approaches. Even though it was a cost consequence (rather than cost-utility) analysis it was included due to it being similar to the analysis done for the 2014 update, and was specifically conducted to estimate the impact of implementing the 2014 NICE recommendations. This study disagreed with the model from the 2014 guideline and found that the cost of monitoring would increase by £23 per person (£25.39 in 2020 prices) if cystatin C-based equations were used. It also found that in an elderly population eGFRcystatin C resulted in a greater number of patients being reclassified to a more severe CKD category.

The 2017 model was conducted to assess the effect of the introduction of the 2014 recommendations. The two models have different populations with the 2014 study using suspected CKD and CKD-EPIcreat eGFR 45-59 mL/min/1.73 m2 and ACR <3; the 2017 study required two results of CKD-EPIcreat eGFR 30-59 mL/min/1.73 m2 90 days apart. The two studies also had different sources for the diagnostics accuracy data, with 2014 from multiple sources including unpublished data for the over 75-year olds, 2017 used cohort data from 32 Derbyshire GP practices. The 2017 study found that using eGFRcystatin C is not cost saving and therefore should not be recommended for use in general practice. The 2017 study found that the cost saving from the reduced numbers diagnosed with CKD was outweighed by the increase costs in monitoring.

1.1.7.2. Excluded studies

There were no excluded studies for this review question.

1.1.8. Summary of included economic evidence

National Clinical Guideline Centre 2014

StudyComparatorsCosts1Percentage correctUncertaintyApplicabilityLimitations

National Clinical Guideline Centre 2014

Cost effectiveness analysis

NHS perspective

Decision Tree

One-year time horizon

CKD-EPICreat:no further testing, diagnosed as CKD stage 3a

CKD-EPICys: eGFR is re-calculated using serum cystatin C and the CKD-EPIcys equation

CKD-EPICreate-cys: eGFR is re-calculated using serum cystatin C and serum creatinine and the combined CKD-EPI equation

Age 75+

CKD-EPICreat: £57.39

CKD-EPICys: £47.27

CKD-EPICreat-cys: £51.40

Age<75 No hypertension

CKD-EPICreat: £57.39

CKD-EPICys: £42.26

CKD-EPICreat-cys: £49.13

Age<75 hypertension

CKD-EPICreat: £65.15

CKD-EPICys: £44.14

CKD-EPICreat-cys: £48.76

Age 75+

CKD-EPICreat: 79.8

CKD-EPICys: 76.6

CKD-EPICreat-cys: 80.5

Age<75 No hypertension

CKD-EPICreat: 67

CKD-EPICys: 75

CKD-EPICreat-cys: 81

Age<75 hypertension

CKD-EPICreat: 70

CKD-EPICys: 79

CKD-EPICreat-cys: 79

Probabilistic sensitivity analysis was done around the input parameter point estimates. Prices were kept deterministic. When changing drug and management costs to 5 years rather than 1 year, it increased the costs but CKD-EPIcys was still the most cost-effective result. Other sensitivity analyses did not have a large effect.Partially applicablePotentially serious limitations
1

Costs inflated from sterling 2014 to sterling 2020 using the EPPI Centre cost converter accessed 22/10/2020, inflation factor 1.11.

Shardlow 2017

StudyComparatorsCosts differences1Total increase per patientUncertaintyApplicabilityLimitations

Shardlow 2017

Cost consequence analysis

NHS perspective

5-year time horizon

Implementing cystatin C testing and 12 months of monitoring using eGFRcystatin C£14,180.11£25.39No sensitivity analysis was donePartially ApplicablePotentially serious limitations
Implementing cystatin C testing and 12 months of monitoring using eGFRcreatinine and cystatin C£3,561.87£8.83
1

Costs inflated from sterling 2015 to sterling 2020 using the EPPI Centre cost converter accessed 22/10/2020, inflation factor 1.10.

1.1.9. Economic model

No original health economic modelling was done for this review question in the 2020 update of the guideline.

1.1.10. The committee’s discussion and interpretation of the evidence

1.1.10.1. The outcomes that matter most

Cystatin-C equations to estimate GFR (eGFR) have the potential to be used to diagnose people with CKD without those people having to undergo more rigorous and invasive methods of measuring GFR. It is important that any measurement of GFR is accurate and does not produce too many false negative or false positive results.

False positive results would result in a person without CKD receiving a diagnosis and undergoing unnecessary treatment. False negative results would result in a person being incorrectly told that they do not have CKD, which would result in them not receiving needed treatment.

It is also important that the estimate of GFR obtained using cystatin-c equations is sufficiently close to the measured GFR value to ensure that people with CKD receive accurate staging. This is particularly important when cystatin-c measures are combined with creatinine-based measures to stratify the stage of CKD. For example, the equation may correctly identify someone with CKD but may give a value indicative of having early stage disease when their measured GFR suggests later stage disease.

The committee valued sensitivity (and negative likelihood ratios which are most affected by sensitivity) over specificity (and positive likelihood ratios) as it is more important that people with CKD do not go underdiagnosed. However, sensitivity and specificity were only reported by 2 studies. P30 was reported by almost all studies, fewer studies reported P15, P10 and AUC. Minimal clinically important differences could not be used for these accuracy values which made harder to use them for decision making.

1.1.10.2. The quality of the evidence

The committee agreed that there were serious limitations with the quality of the evidence available and this was a primary driver in their decision to no longer recommend that cystatin-c equations be considered during diagnosis of CKD. Previous recommendations were also based on very limited evidence. See the section of ‘benefits and harms’ for a discussion about the committee decision for no longer recommending cystatin-c equations.

The risk of bias associated with the studies was mainly moderate due to being retrospective studies, having an important time difference between cystatin-c and reference standard measurements, and having selection bias.

Selection bias was seen in several retrospective studies in which all people with cystatin-c on record were included in the analysis, this has the potential for selection bias if cystatin-c is not routinely measured during diagnosis of CKD in the participating centre(s) as the included participants would have had certain clinical features which warranted measurement of cystatin-c. Studies with any issues were downgraded.

Most studies rely on the use of P30 values to measure the diagnostic accuracy of the cystatin-c equations. A P30 value informs the percentage of participants with an eGFR within 30% of their mGFR value. This measure is of limited usefulness as a 30% deviation from the mGFR is still a potentially large difference. Additionally, it does not inform as to whether the actual estimated value is above or below the measured value and does not inform of the risk of false negative and false positive results.

Relatively few studies reported P10 and P15 values. These measures are more suitable for assessing eGFR as they allow for a smaller margin of error. Several equations were identified as having P10-15 values of over 50%. However, there was remaining uncertainty surrounding these equations due to evidence coming from single studies, with small to moderate sample sizes. Additionally, it is unclear how much variance there was for those participants with eGFR that was more than 10-15% different from their mGFR, it is therefore possible that using these equations in practice would result in a large number of participants receiving inaccurate estimates.

Some studies assessed the sensitivity and specificity of cystatin-c equations. As GFR is continuous, the estimates had to be dichotomised, with GFR estimates of 60 or less being positive and those over 60 being negative. These data were reported for the simple cystatin-c equation however evidence from P30 values for this equation suggested that it was not sufficiently accurate.

Finally, meta-analysis of the data was not possible. There were 12 different cystatin-c equations evaluated across 12 different studies. There were only a limited number of equations with data from multiple studies and among these, differences in study design (retrospective or prospective cohort studies, or cross-sectional studies) or population (children/young people, adults or the elderly) meant that it was unsuitable to combine the data in meta-analysis.

1.1.10.3. Benefits and harms

The committee noted that the recommendations in the previous guideline were based on very limited evidence and agreed that these recommendations have seen little implementation in everyday practice, noting the uncertainty surrounding their evidence and the costs associated with these tests and added complexity of laboratory processes as potential reasons for this.

The evidence used in the previous guideline was from studies with limitations on populations (CKD population could not be separated from overall cohort; suspected or confirmed CKD was not a requirement for inclusion into the study) and study design (derivation study without external validation). These studies were not included in the update of the evidence because of these limitations (see Appendix L for more details on reasons for excluding these studies: Inker 2012; Kilbride 2013; Schaeffner 2012).

The committee agreed that the quality of the evidence meant that they could not be confident in the accuracy of cystatin-c based estimates of GFR. In particular, most studies relied on P30 values to measure diagnostic accuracy, which allows to an unacceptable degree of variation between the estimated and measured values, particularly in the lower stages of disease. Results showed that P30 values ranged from 6 to 100%, P15 values were around 50% and P10 values were from 21 to 60%. P values also do not inform whether the eGFR was an overestimate or an underestimate. This is important clinically as it means that there is uncertainty as to the risk posed by these equations for producing false positive and false negative results, particularly when used in people with lower stage kidney disease. Results showed that AUC values were 0.9 and higher which is considered to be outstanding. However, having only AUC values lacks clinical interpretability because AUC represents the performance of cystatin-c across all GFR thresholds and there was very limited evidence on sensitivity and specificity which reports on specific clinical thresholds (for example, GFR ≤60 mL/min/1.73 m2). The committee also highlighted that cystatin-c has not been widely used in clinical practice and that not longer recommending its use would not have an impact on daily practice where creatinine is used to estimate GFR.

The lack of meta-analysis meant that each equation typically relied on evidence from a single study, many of which had small sample sizes. There are now numerous different cystatin-c based equations, for which there is uncertain diagnostic accuracy.

The committee agreed that the issues in the evidence meant that there is remaining uncertainty surrounding the risks associated with using these equations in the diagnostic pathway and they should not be recommended as a result. Further research is needed to determine whether or not these equations are useful and so the committee made a research recommendation (see Appendix M).

1.1.10.4. Cost effectiveness and resource use

The committee noted that the evidence was contradictory (with the modelling from the 2014 guideline suggesting using cystatin equations would be cost-effective, whilst the Shardlow study suggested it would increase costs) and therefore it was difficult to feel confident in making a recommendation. Both studies were rated as being of a similar quality, with different limitations. The committee agreed it was not appropriate to regard false negatives as having no adverse consequences, as was done in the 2014 modelling. In contrast, the committee agreed that the population in Shardlow 2017 did not fully fit the review question as it contained patients with an eGFR of less than 45 mL/min/1.73 m2, whilst the recommendations were only for it to be used in people with an eGFR between 45 and 60 mL/min/1.73 m2. The committee also agreed that evaluating cystatin equations using a single data point is not fully relevant, as many patients in the real world get more than one test. The committee noted that the majority of laboratories do not measure GFR using cystatin-c at present, and therefore keeping the recommendation would still represent a change in practice, as it has not been widely adopted. Stopping measuring GFR using cystatin-c may reduce resource use from the few laboratories that do measure GFR using cystatin-c. The committee agreed that it was not possible to make any recommendations in this area and that it was appropriate to remove the recommendation made in 2014.

1.1.11. Recommendations supported by this evidence review

This evidence review supports the research recommendation on the diagnostic accuracy of cystatin C equations (see Appendix M for further details about the research recommendation). No recommendations were made from this evidence review.

1.1.12. References – included studies

    1.1.12.1. Diagnostic
    • Bevc, Sebastjan, Hojs, Nina, Hojs, Radovan et al. (2017) Estimation of Glomerular Filtration Rate in Elderly Chronic Kidney Disease Patients: Comparison of Three Novel Sophisticated Equations and Simple Cystatin C Equation. Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy 21(2): 126–132 [PubMed: 28296256]
    • Bevc, Sebastjan, Hojs, Radovan, Ekart, Robert et al. (2012) Simple cystatin C formula compared to serum creatinine-based formulas for estimation of glomerular filtration rate in patients with mildly to moderately impaired kidney function. Kidney & blood pressure research 35(6): 649–54 [PubMed: 23095576]
    • Bevc, Sebastjan, Hojs, Radovan, Ekart, Robert et al. (2011) Simple cystatin C formula compared to sophisticated CKD-EPI formulas for estimation of glomerular filtration rate in the elderly. Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy 15(3): 261–8 [PubMed: 21624073]
    • Deng, F., Finer, G., Haymond, S. et al. (2015) Applicability of estimating glomerular filtration rate equations in pediatric patients: Comparison with a measured glomerular filtration rate by iohexol clearance. Translational Research 165(3): 437–445 [PMC free article: PMC4346435] [PubMed: 25445208]
    • Du, Yue, Sun, Ting-Ting, Hou, Ling et al. (2015) Applicability of various estimation formulas to assess renal function in Chinese children. World journal of pediatrics : WJP 11(4): 346–51 [PubMed: 25447632]
    • Fan, Li, Inker, Lesley A, Rossert, Jerome et al. (2014) Glomerular filtration rate estimation using cystatin C alone or combined with creatinine as a confirmatory test. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 29(6): 1195–203 [PMC free article: PMC4471437] [PubMed: 24449101]
    • Hari, Pankaj, Ramakrishnan, Lakshmy, Gupta, Ruby et al. (2014) Cystatin C-based glomerular filtration rate estimating equations in early chronic kidney disease. Indian pediatrics 51(4): 273–7 [PubMed: 24825263]
    • Hojs, R, Bevc, S, Ekart, R et al. (2011) Kidney function estimating equations in patients with chronic kidney disease. International journal of clinical practice 65(4): 458–64 [PubMed: 21401834]
    • Hojs, Radovan, Bevc, Sebastjan, Ekart, Robert et al. (2010) Serum cystatin C-based formulas for prediction of glomerular filtration rate in patients with chronic kidney disease. Nephron. Clinical practice 114(2): c118–26 [PubMed: 19887832]
    • Inker, Lesley A, Levey, Andrew S, Tighiouart, Hocine et al. (2018) Performance of glomerular filtration rate estimating equations in a community-based sample of Blacks and Whites: the multiethnic study of atherosclerosis. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 33(3): 417–425 [PMC free article: PMC6018782] [PubMed: 28505377]
    • Lemoine, Sandrine, Panaye, Marine, Pelletier, Caroline et al. (2016) Cystatin C-Creatinine Based Glomerular Filtration Rate Equation in Obese Chronic Kidney Disease Patients: Impact of Deindexation and Gender. American journal of nephrology 44(1): 63–70 [PubMed: 27400282]
    • Ng, Derek K, Schwartz, George J, Schneider, Michael F et al. (2018) Combination of pediatric and adult formulas yield valid glomerular filtration rate estimates in young adults with a history of pediatric chronic kidney disease. Kidney international 94(1): 170–177 [PMC free article: PMC6015546] [PubMed: 29735307]
    • Salvador, C.L., Tondel, C., Rowe, A.D. et al. (2019) Estimating glomerular filtration rate in children: evaluation of creatinine- and cystatin C-based equations. Pediatric Nephrology 34(2): 301–311 [PubMed: 30171354]
    • Teo, Boon Wee, Xu, Hui, Wang, Danhua et al. (2012) Estimating glomerular filtration rates by use of both cystatin C and standardized serum creatinine avoids ethnicity coefficients in Asian patients with chronic kidney disease. Clinical chemistry 58(2): 450–7 [PubMed: 22205693]
    • Werner, Karin, Pihlsgard, Mats, Elmstahl, Solve et al. (2017) Combining Cystatin C and Creatinine Yields a Reliable Glomerular Filtration Rate Estimation in Older Adults in Contrast to beta-Trace Protein and beta2-Microglobulin. Nephron 137(1): 29–37 [PubMed: 28407629]
    • White, Christine A, Allen, Celine M, Akbari, Ayub et al. (2019) Comparison of the new and traditional CKD-EPI GFR estimation equations with urinary inulin clearance: A study of equation performance. Clinica chimica acta; international journal of clinical chemistry 488: 189–195 [PubMed: 30445029]
    1.1.12.2. Economic
    • Shardlow, Adam, McIntyre, Natasha J, Fraser, Simon D. S et al. (2017) The clinical utility and cost impact of cystatin C measurement in the diagnosis and management of chronic kidney disease: A primary care cohort study. PLoS Med 14(10): e1002400. [PMC free article: PMC5634538] [PubMed: 29016597]

Appendices

Appendix B. Methods

Diagnostic test accuracy evidence (PDF, 288K)

Health economics (PDF, 153K)

Appendix C. Literature search strategies

Background to the search

A NICE information specialist conducted the literature searches for the evidence review. The searches were originally run between the 27th to the 30th of September 2019 and updated on the 2nd of September 2020. This search report is compliant with the requirements of PRISMA-S.

The principal search strategy was developed in MEDLINE (Ovid interface) and adapted, as appropriate, for use in the other sources listed in the protocol, taking into account their size, search functionality and subject coverage.

The MEDLINE strategy below was quality assured (QA) by trained NICE information specialist. All translated search strategies were peer reviewed to ensure their accuracy. Both procedures were adapted from the 2016 PRESS Checklist.

The search results were managed in EPPI-Reviewer v5. Duplicates were removed in EPPI-R5 using a two-step process. First, automated deduplication is performed using a high-value algorithm. Second, manual deduplication is used to assess ‘low-probability’ matches. All decisions made for the review can be accessed via the deduplication history.

English language limits were applied in adherence to standard NICE practice and the review protocol.

Limits to exclude conferences in Embase were applied in adherence to standard NICE practice and the review protocol.

The limit to remove animal studies in the searches was the standard NICE practice, which has been adapted from: Dickersin, K., Scherer, R., & Lefebvre, C. (1994). Systematic Reviews: Identifying relevant studies for systematic reviews. BMJ, 309(6964), 1286 [PMC free article: PMC2541778] [PubMed: 7718048].

Clinical searches

Download PDF (406K)

Cost-effectiveness searches

Download PDF (330K)

Appendix D. Diagnostic evidence study selection

Download PDF (147K)

Appendix E. Diagnostic evidence tables

Download PDF (681K)

Appendix F. Forest plots

None of the included studies could be combined to produce a pooled effect estimate.

Appendix G. GRADE tables

GRADE tables were not used for P values and AUC.

Likelihood ratio outcomes (PDF, 156K)

Appendix H. Economic evidence study selection

Download PDF (135K)

Appendix I. Economic evidence tables

Download PDF (268K)

Appendix J. Health economic model

No health economic modelling was undertaken for this review question.

Appendix K. 2014 Health economic model

The model described below was developed in 2014 for the update of the CKD guideline conducted then. This review question was not prioritised for modelling in the 2020 update of the guideline, so this analysis has not been updated. The results of this 2014 model have therefore been included in the guideline in the same way as those from a published journal article. (see Appendix I).

Cost-effectiveness analysis: cystatin C testing in the diagnosis of CKD (PDF, 664K)

References

  • Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. New England Journal of Medicine. 2012; 367(1):20–29 [PMC free article: PMC4398023] [PubMed: 22762315]
  • Kilbride HS, Stevens PE, Eaglestone G, Knight S, Carter JL, Delaney MP et al. Accuracy of the MDRD (Modification of Diet in Renal Disease) Study and CKD-EPI (CKD Epidemiology Collaboration) Equations for Estimation of GFR in the Elderly. American Journal of Kidney Diseases. 2013; 61(1):57–66 [PubMed: 22889713]
  • Inker LA, Fan L, Okparavero AA, Gudnason V, Eriksdottir G, Andresdottir MB et al. Comparing cystatin C and creatinine for estimating measured GFR and CKD prevalence in a community based sample of the elderly. Journal of the American Society of Nephrology. 2013; 24:164A

Appendix L. Excluded studies

Diagnostic studies

StudyReason for exclusion
Andersen, Trine Borup, Jodal, Lars, Boegsted, Martin et al. (2012) GFR prediction from cystatin C and creatinine in children: effect of including body cell mass. American journal of kidney diseases : the official journal of the National Kidney Foundation 59(1): 50–7 [PubMed: 22037490] - Could not separate CKD population from overall cohort
Andersen, Trine Borup, Jodal, Lars, Erlandsen, Erland J et al. (2013) Detecting reduced renal function in children: comparison of GFR-models and serum markers. Pediatric nephrology (Berlin, Germany) 28(1): 83–92 [PubMed: 22945867]

- Derivation study without external validation

results are only available for the models derived in this study. Although this study did test existing equations, these were only used to inform their model and results were not presented

Aydin, Funda, Budak, Evrim Surer, Demirelli, Serkan et al. (2015) Comparison of Cystatin C and beta-Trace Protein Versus 99mTc-DTPA Plasma Sampling in Determining Glomerular Filtration Rate in Chronic Renal Disease. Journal of nuclear medicine technology 43(3): 206–13 [PubMed: 26111707] - Outcomes are not reported in a format meeting the protocol
Bacchetta, Justine, Cochat, Pierre, Rognant, Nicolas et al. (2011) Which creatinine and cystatin C equations can be reliably used in children?. Clinical journal of the American Society of Nephrology : CJASN 6(3): 552–60 [PMC free article: PMC3082413] [PubMed: 21115623]

- Could not separate CKD population from overall cohort

population consisted of >10% renal transplant patients.

Barr, Elizabeth Lm, Maple-Brown, Louise J, Barzi, Federica et al. (2017) Comparison of creatinine and cystatin C based eGFR in the estimation of glomerular filtration rate in Indigenous Australians: The eGFR Study. Clinical biochemistry 50(6): 301–308 [PubMed: 27894952] - Population did not meet that specified by the protocol
Berg, Ulla B, Nyman, Ulf, Back, Rune et al. (2015) New standardized cystatin C and creatinine GFR equations in children validated with inulin clearance. Pediatric nephrology (Berlin, Germany) 30(8): 1317–26 [PubMed: 25903639] - Could not separate CKD population from overall cohort
Bevc, Sebastjan, Hojs, Nina, Knehtl, Masa et al. (2019) Cystatin C as a predictor of mortality in elderly patients with chronic kidney disease. The aging male : the official journal of the International Society for the Study of the Aging Male 22(1): 62–67 [PubMed: 29912597] - Outcome to be predicted do not match that specified in the protocol
Bjork, Jonas, Back, Sten Erik, Ebert, Natalie et al. (2018) GFR estimation based on standardized creatinine and cystatin C: a European multicenter analysis in older adults. Clinical chemistry and laboratory medicine 56(3): 422–435 [PubMed: 28985182] - Participants were not required to have suspected or confirmed CKD
Bjork, Jonas, Grubb, Anders, Larsson, Anders et al. (2015) Accuracy of GFR estimating equations combining standardized cystatin C and creatinine assays: a cross-sectional study in Sweden. Clinical chemistry and laboratory medicine 53(3): 403–14 [PubMed: 25274955] - Internal validation study
Bukabau, J.B., Yayo, E., Gnionsahe, A. et al. (2019) Performance of creatinine- or cystatin C-based equations to estimate glomerular filtration rate in sub-Saharan African populations. Kidney International 95(5): 1181–1189 [PubMed: 30910379] - Could not separate CKD population from overall cohort
Cha, Ran-Hui, Lee, Chung Sik, Lim, Youn-Hee et al. (2010) Clinical usefulness of serum cystatin C and the pertinent estimation of glomerular filtration rate based on cystatin C. Nephrology (Carlton, Vic.) 15(8): 768–76 [PubMed: 21175963] - Population did not meet that specified by the protocol
Chi, Xiao-Hua, Li, Gui-Ping, Wang, Quan-Shi et al. (2017) CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equation seems more suitable for Chinese patients with chronic kidney disease than other equations. BMC nephrology 18(1): 226 [PMC free article: PMC5504640] [PubMed: 28693441] - Population did not meet that specified by the protocol
Corrao, A M, Lisi, G, Di Pasqua, G et al. (2006) Serum cystatin C as a reliable marker of changes in glomerular filtration rate in children with urinary tract malformations. The Journal of urology 175(1): 303–9 [PubMed: 16406933] - Study does not contain any relevant index tests
Dart, A B, McGavock, J, Sharma, A et al. (2019) Estimating glomerular filtration rate in youth with obesity and type 2 diabetes: the iCARE study equation. Pediatric nephrology (Berlin, Germany) 34(9): 1565–1574 [PubMed: 31049718]

- Unclear whether participants were suspected of CKD

Validation cohort were 26 youth with BMI >85th percentile without diabetes

den Bakker, Emil, Gemke, Reinoud, van Wijk, Joanna A E et al. (2018) Combining GFR estimates from cystatin C and creatinine-what is the optimal mix?. Pediatric nephrology (Berlin, Germany) 33(9): 1553–1563 [PubMed: 29774462] - Could not separate CKD population from overall cohort
Donmez, Osman, Korkmaz, Huseyin Anil, Yildiz, Nalan et al. (2015) Comparison of serum cystatin C and creatinine levels in determining glomerular filtration rate in children with stage I to III chronic renal disease. Renal failure 37(5): 784–90 [PubMed: 25707515]

- 2×2 not reported / calculable

P15/30 also not available

Du, Yue, Sun, Ting-Ting, Hou, Ling et al. (2015) Applicability of various estimation formulas to assess renal function in Chinese children. World journal of pediatrics : WJP 11(4): 346–51 [PubMed: 25447632] - Population did not meet that specified by the protocol
Fan, Li, Inker, Lesley A, Rossert, Jerome et al. (2014) Glomerular filtration rate estimation using cystatin C alone or combined with creatinine as a confirmatory test. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 29(6): 1195–203 [PMC free article: PMC4471437] [PubMed: 24449101] - Population did not meet that specified by the protocol
Feng, Jia-fu, Qiu, Ling, Zhang, Lin et al. (2013) Multicenter study of creatinine- and/or cystatin C-based equations for estimation of glomerular filtration rates in Chinese patients with chronic kidney disease. PloS one 8(3): e57240 [PMC free article: PMC3602457] [PubMed: 23526939] - Population did not meet that specified by the protocol
Filler, G., Foster, J., Acker, A. et al. (2005) The Cockcroft-Gault formula should not be used in children. Kidney International 67(6): 2321–2324 [PubMed: 15882274] - Could not separate CKD population from overall cohort
Filler, G, Priem, F, Vollmer, I et al. (1999) Diagnostic sensitivity of serum cystatin for impaired glomerular filtration rate. Pediatric nephrology (Berlin, Germany) 13(6): 501–5 [PubMed: 10452278] - Study does not contain any relevant index tests
Filler, Guido and Lepage, Nathalie (2003) Should the Schwartz formula for estimation of GFR be replaced by cystatin C formula?. Pediatric nephrology (Berlin, Germany) 18(10): 981–5 [PubMed: 12920638]

- 2×2 not reported / calculable

p30 also not reported

Gabutti, Luca, Ferrari, Nicola, Mombelli, Giorgio et al. (2004) Does cystatin C improve the precision of Cockcroft and Gault’s creatinine clearance estimation?. Journal of nephrology 17(5): 673–8 [PubMed: 15593034] - Reference standard in study does not match that specified in protocol
Gotoh, Y., Uemura, O., Ishikura, K. et al. (2018) Validation of estimated glomerular filtration rate equations for Japanese children. Clinical and Experimental Nephrology 22(4): 931–937 [PubMed: 29372471] - Population did not meet that specified by the protocol
Grubb, A, Bjork, J, Lindstrom, V et al. (2005) A cystatin C-based formula without anthropometric variables estimates glomerular filtration rate better than creatinine clearance using the Cockcroft-Gault formula. Scandinavian journal of clinical and laboratory investigation 65(2): 15362 [PubMed: 16025838] - Derivation study without external validation
Guan, Changjie, Liang, Ming, Liu, Riguang et al. (2018) Assessment of creatinine and cystatin C-based eGFR equations in Chinese older adults with chronic kidney disease. International urology and nephrology 50(12): 2229–2238 [PubMed: 29948865]

- Assessment tool do not match that specified in the protocol

only compared Cystatin and creatinine combined equations

Guo, Xiuzhi, Qin, Yan, Zheng, Ke et al. (2014) Improved glomerular filtration rate estimation using new equations combined with standardized cystatin C and creatinine in Chinese adult chronic kidney disease patients. Clinical biochemistry 47(1314): 1220–6 [PubMed: 24886770] - Population did not meet that specified by the protocol
Hojs, R, Bevc, S, Ekart, R et al. (2008) Serum cystatin C-based equation compared to serum creatinine-based equations for estimation of glomerular filtration rate in patients with chronic kidney disease. Clinical nephrology 70(1): 10–7 [PubMed: 18793543] - Derivation study without external validation
Huang, Shih-Han S, Macnab, Jennifer J, Sontrop, Jessica M et al. (2011) Performance of the creatinine-based and the cystatin C-based glomerular filtration rate (GFR) estimating equations in a heterogenous sample of patients referred for nuclear GFR testing. Translational research : the journal of laboratory and clinical medicine 157(6): 357–67 [PubMed: 21575920] - Participants were not required to have suspected or confirmed CKD
Inker, Lesley A, Schmid, Christopher H, Tighiouart, Hocine et al. (2012) Estimating glomerular filtration rate from serum creatinine and cystatin C. The New England journal of medicine 367(1): 20–9 [PMC free article: PMC4398023] [PubMed: 22762315]

- 2×2 not reported / calculable

P30 available

- Could not separate CKD population from overall cohort

Jeong, Tae-Dong, Lee, Woochang, Yun, Yeo-Min et al. (2016) Development and validation of the Korean version of CKD-EPI equation to estimate glomerular filtration rate. Clinical biochemistry 49(9): 713–719 [PubMed: 26968101] - Could not separate CKD population from overall cohort
Jonsson, A-S, Flodin, M, Hansson, L-O et al. (2007) Estimated glomerular filtration rate (eGFRCystC) from serum cystatin C shows strong agreement with iohexol clearance in patients with low GFR. Scandinavian journal of clinical and laboratory investigation 67(8): 801–9 [PubMed: 17852801] - Derivation study without external validation
Kilbride, Hannah S, Stevens, Paul E, Eaglestone, Gillian et al. (2013) Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. American journal of kidney diseases : the official journal of the National Kidney Foundation 61(1): 57–66 [PubMed: 22889713]

- Unclear whether participants had CKD

although subgroup analyses included people with GFR <60, suspected or confirmed CKD was not a requirement for inclusion into the study

Kumaresan, R. and Giri, P. (2012) A comparison between serum Creatinine and cystatin C-based formulae: Estimating glomerular filtration rate in chronic kidney disease patients. Asian Journal of Pharmaceutical and Clinical Research 5(suppl1): 42–44

- 2×2 not reported / calculable

P30 not available

Lamb, Edmund J, Brettell, Elizabeth A, Cockwell, Paul et al. (2014) The eGFR-C study: accuracy of glomerular filtration rate (GFR) estimation using creatinine and cystatin C and albuminuria for monitoring disease progression in patients with stage 3 chronic kidney disease--prospective longitudinal study in a multiethnic population. BMC nephrology 15: 13 [PMC free article: PMC3898236] [PubMed: 24423077] - methods/rationale only
Levey AS, Coresh J, Greene T et al. (2006) Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Annals of internal medicine 145(4): 247–254 [PubMed: 16908915] - Study does not contain any relevant index tests
Li, Hai-xia, Xu, Guo-bin, Wang, Xue-jing et al. (2010) Diagnostic accuracy of various glomerular filtration rates estimating equations in patients with chronic kidney disease and diabetes. Chinese medical journal 123(6): 745–51 [PubMed: 20368098] - Population did not meet that specified by the protocol
Liu, Xun, Ma, Huijuan, Huang, Hui et al. (2013) Is the Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin C equation useful for glomerular filtration rate estimation in the elderly?. Clinical interventions in aging 8: 1387–91 [PMC free article: PMC3797613] [PubMed: 24143084] - Population did not meet that specified by the protocol
Luis-Lima, S., Escamilla-Cabrera, B., Negrin-Mena, N. et al. (2019) Chronic kidney disease staging with cystatin C or creatinine-based formulas: Flipping the coin. Nephrology Dialysis Transplantation 34(2): 287–294 [PubMed: 29762739]

- Could not separate CKD population from overall cohort

most of the participants were not recruited due to suspected or confirmed CKD. Additionally, the study include renal transplant and pre-dialysis patients

Major, R.W.; Shepherd, D.; Brunskill, N.J. (2018) Reclassification of chronic kidney disease stage, eligibility for cystatin-c and its associated costs in a UK primary care cohort. Nephron 139(1): 39–46 [PubMed: 29566373]

- Assessment tool do not match that specified in the protocol

Cystatin-C equation not evaluated

Masaebi, F., Looha, M.A., Wang, Z. et al. (2020) Evaluation of neutrophil gelatinase-associated lipocalin and cystatin C in early diagnosis of chronic kidney disease in the absence of the Gold Standard. Galen Medical Journal 9: e1698 [PMC free article: PMC8343785] [PubMed: 34466571] - Study does not contain any relevant index tests
Mohammed, R.A.-A., El-Shazely, A., Haridy, M.A.M.A. et al. (2019) Diagnostic values of serum cystatin C and urinary fetuin-A as early biochemical markers in predicting diabetic nephropathy among patients with type 2 diabetes mellitus. Research Journal of Pharmaceutical, Biological and Chemical Sciences 10(6): 237–244 - Study does not contain any relevant index tests
Mousavinasab, N. and Jalalzadeh, M. (2017) A comparison of estimated GFRs based on formulas of serum cystatin C and serum creatinine. Nephro-Urology Monthly 9(3): e46569

- 2×2 not reported / calculable

P30 also not reported

Narvaez-Sanchez, Raul, Gonzalez, Luz, Salamanca, Alba et al. (2008) Cystatin C could be a replacement to serum creatinine for diagnosing and monitoring kidney function in children. Clinical biochemistry 41(78): 498–503 [PubMed: 18280806]

- Assessment tool do not match that specified in the protocol

serum cystatin only (no equation used)

Neirynck, Nathalie, Eloot, Sunny, Glorieux, Griet et al. (2012) Estimated glomerular filtration rate is a poor predictor of the concentration of middle molecular weight uremic solutes in chronic kidney disease. PloS one 7(8): e44201 [PMC free article: PMC3432070] [PubMed: 22952928]

- Reference standard in study does not match that specified in protocol

reference standard was based on eGFR

Ng, Derek K, Schwartz, George J, Warady, Bradley A et al. (2017) Relationships of Measured Iohexol GFR and Estimated GFR With CKD-Related Biomarkers in Children and Adolescents. American journal of kidney diseases : the official journal of the National Kidney Foundation 70(3): 397–405 [PMC free article: PMC5572310] [PubMed: 28549535]

- Assessment tool do not match that specified in the protocol

only looked at an equation which contained both Creatinine and Cystatin C

Padala S, Tighiouart H, Inker LA et al. (2012) Accuracy of a GFR estimating equation over time in people with a wide range of kidney function. American journal of kidney diseases : the official journal of the National Kidney Foundation 60(2): 217–224 [PMC free article: PMC3399947] [PubMed: 22495467] - Derivation study without external validation the study used data from derivation studies
Pei, Xiao-Hua, He, Juan, Liu, Qiao et al. (2012) Evaluation of serum creatinine- and cystatin C-based equations for the estimation of glomerular filtration rate in a Chinese population. Scandinavian journal of urology and nephrology 46(3): 223–31 [PubMed: 22376289] - Participants were not required to have suspected or confirmed CKD
Pei, Xiaohua, Bao, Lihua, Xu, Zhaoqiang et al. (2013) Diagnostic value of cystatin C and glomerular filtration rate formulae in Chinese nonelderly and elderly populations. Journal of nephrology 26(3): 476–84 [PubMed: 22878979] - Population did not meet that specified by the protocol
Ramanathan, K. and Padmanabhan, G. (2017) Comparison of chronic kidney disease epidemiology collaboration equations with other accepted equations for estimation of glomerular filtration rate in Indian chronic kidney disease patients. Bangladesh Journal of Medical Science 16(2): 238–244 - Population did not meet that specified by the protocol
Rowe, C., Sitch, A.J., Barratt, J. et al. (2019) Biological variation of measured and estimated glomerular filtration rate in patients with chronic kidney disease. Kidney International 96(2): 429–435 [PubMed: 31084924]

- 2×2 not reported / calculable

P30 calculation also not possible.

Salek, T. and Palicka, V. (2014) Comparison of creatinine clearance and estimated glomerular filtration rate in patients with chronic kidney disease. Klinicka Biochemie a Metabolismus 22(3): 123–126 - Reference standard in study does not match that specified in protocol
Scarr, D., Bjornstad, P., Lovblom, L.E. et al. (2019) Estimating GFR by Serum Creatinine, Cystatin C, and beta2-Microglobulin in Older Adults: Results From the Canadian Study of Longevity in Type 1 Diabetes. Kidney International Reports 4(6): 786–796 [PMC free article: PMC6551543] [PubMed: 31194091] - Participants were not required to have suspected or confirmed CKD
Schaeffner, Elke S, Ebert, Natalie, Delanaye, Pierre et al. (2012) Two novel equations to estimate kidney function in persons aged 70 years or older. Annals of internal medicine 157(7): 471–81 [PubMed: 23027318] - Derivation study without external validation
Serezlija, Elma; Serdarevic, Nafija; Begic, Lejla (2017) The Estimation of Glomerular Filtration Rate Based on the Serum Cystatin C and Creatinine Values. Clinical laboratory 63(7): 1099–1106 [PubMed: 28792695]

- Unclear whether participants had CKD

participants were recruited based on GFR but subgroup analysis according to level of GFR is not available.

Shardlow, Adam, McIntyre, Natasha J, Fraser, Simon D S et al. (2017) The clinical utility and cost impact of cystatin C measurement in the diagnosis and management of chronic kidney disease: A primary care cohort study. PLoS medicine 14(10): e1002400 [PMC free article: PMC5634538] [PubMed: 29016597] - Reference standard in study does not match that specified in protocol
Sharma, Ajay P, Yasin, Abeer, Garg, Amit X et al. (2011) Diagnostic accuracy of cystatin C-based eGFR equations at different GFR levels in children. Clinical journal of the American Society of Nephrology : CJASN 6(7): 1599–608 [PubMed: 21700821] - Population did not meet that specified by the protocol
Stevens LA, Claybon MA, Schmid CH et al. (2011) Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney international 79(5): 555–562 [PMC free article: PMC4220293] [PubMed: 21107446]

- Participants were not required to have suspected or confirmed CKD

Datasets included around 15% of participants who were kidney donors (without CKD), additionally, of the participants with CKD in the external validation set, 29% were transplant recipients.

Sun, Yanhong, Jiang, Tang, Zeng, Zhijie et al. (2010) Performance evaluation of a particle-enhanced turbidimetric cystatin C assay using the Abbott Aeroset analyser and assessment of cystatin C-based equations for estimating glomerular filtration rate in chronic kidney disease. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 25(5): 1489–96 [PubMed: 20037185] - Population did not meet that specified by the protocol
Trimarchi, Hernan, Muryan, Alexis, Martino, Diana et al. (2012) Creatinine- vs. cystatin C-based equations compared with 99mTcDTPA scintigraphy to assess glomerular filtration rate in chronic kidney disease. Journal of nephrology 25(6): 1003–15 [PubMed: 22322818] - Data not reported in a format specified in the protocol
Trimarchi, Hernan, Muryan, Alexis, Toscano, Agostina et al. (2014) Proteinuria, (99m) Tc-DTPA Scintigraphy, Creatinine-, Cystatin- and Combined-Based Equations in the Assessment of Chronic Kidney Disease. ISRN nephrology 2014: 430247 [PMC free article: PMC4045439] [PubMed: 24977136] - Outcomes are not reported in a format meeting the protocol
Uemura, Osamu, Nagai, Takuhito, Ishikura, Kenji et al. (2014) Cystatin C-based equation for estimating glomerular filtration rate in Japanese children and adolescents. Clinical and experimental nephrology 18(5): 718–25 [PubMed: 24253614]

- Outcomes are not reported in a format meeting the protocol

p30 / 2×2 table are only available for the derived tool (which did not undergo any validation in this study).

van Deventer, Hendrick E, Paiker, Janice E, Katz, Ivor J et al. (2011) A comparison of cystatin C- and creatinine-based prediction equations for the estimation of glomerular filtration rate in black South Africans. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 26(5): 1553–8 [PMC free article: PMC3108353] [PubMed: 20961892] - Population did not meet that specified by the protocol
Vega, Almudena, Garcia de Vinuesa, Soledad, Goicoechea, Marian et al. (2014) Evaluation of methods based on creatinine and cystatin C to estimate glomerular filtration rate in chronic kidney disease. International urology and nephrology 46(6): 1161–7 [PubMed: 24265040]

- 2×2 not reported / calculable

not all participants underwent the index tests so 2×2 table is not possible. P50 value is available but no P30.

Xun L, Cheng W, Hua T et al. (2010) Assessing glomerular filtration rate (GFR) in elderly Chinese patients with chronic kidney disease (CKD): a comparison of various predictive equations. Archives of gerontology and geriatrics 51(1): 13–20 [PubMed: 19615764] - Study does not contain any relevant index tests
Yang, M., Zou, Y., Lu, T. et al. (2019) Revised Equations to Estimate Glomerular Filtration Rate from Serum Creatinine and Cystatin C in China. Kidney and Blood Pressure Research 44(4): 553–564 [PubMed: 31256154] - Population did not meet that specified by the protocol
Yang, Min, Xu, Guang, Ling, Lilu et al. (2017) Performance of the creatinine and cystatin C-based equations for estimation of GFR in Chinese patients with chronic kidney disease. Clinical and experimental nephrology 21(2): 236–246 [PubMed: 27125433] - Population did not meet that specified by the protocol
Yang, S.-K., Liu, J., Zhang, X.-M. et al. (2016) Diagnostic Accuracy of Serum Cystatin C for the Evaluation of Renal Dysfunction in Diabetic Patients: A Meta-Analysis. Therapeutic Apheresis and Dialysis 20(6): 579–587 [PubMed: 27921376] - Study does not contain any relevant index tests
Ye, Xiaoshuang, Liu, Xun, Song, Dan et al. (2016) Estimating glomerular filtration rate by serum creatinine or/and cystatin C equations: An analysis of multi-centre Chinese subjects. Nephrology (Carlton, Vic.) 21(5): 372–8 [PubMed: 26427030] - Participants were not required to have suspected or confirmed CKD
Ye, Xiaoshuang, Wei, Lu, Pei, Xiaohua et al. (2014) Application of creatinine- and/or cystatin C-based glomerular filtration rate estimation equations in elderly Chinese. Clinical interventions in aging 9: 1539–49 [PMC free article: PMC4166349] [PubMed: 25246780] - Could not separate CKD population from overall cohort
Yong, Zhenzhu, Li, Fen, Pei, Xiaohua et al. (2019) A comparison between 2017 FAS and 2012 CKD-EPI equations: a multi-center validation study in Chinese adult population. International urology and nephrology 51(1): 139–146 [PubMed: 30357600] - Participants were not required to have suspected or confirmed CKD
Zappitelli, Michael, Parvex, Paloma, Joseph, Lawrence et al. (2006) Derivation and validation of cystatin C-based prediction equations for GFR in children. American journal of kidney diseases : the official journal of the National Kidney Foundation 48(2): 221–30 [PubMed: 16860187]

- Could not separate CKD population from overall cohort

contained all children undergoing iothalamate GFR testing, unclear how many had CKD or reason for testing (so suspected CKD cannot be confirmed either)

Zhang, Min, Chen, Yunshuang, Tang, Li et al. (2014) Applicability of chronic kidney disease epidemiology collaboration equations in a Chinese population. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 29(3): 580–6 [PubMed: 24335503] - Population did not meet that specified by the protocol
Zou, L.-X., Sun, L., Nicholas, S.B. et al. (2020) Comparison of bias and accuracy using cystatin C and creatinine in CKD-EPI equations for GFR estimation. European Journal of Internal Medicine [PubMed: 32522444] - Population did not meet that specified by the protocol

Appendix M. Research recommendations – full details

M.1.1. Research recommendation

What is the diagnostic accuracy of cystatin C-based equations to estimate GFR as a measurement of kidney function in adults, children and young people in the UK?

M.1.2. Why this is important

The committee agreed that there were serious limitations with the quality of the available evidence and that previous recommendations were also based on very limited evidence. Therefore, the committee decided to no longer recommend that cystatin-c equations be considered during diagnosis of CKD. This meant that there was remaining uncertainty surrounding the risks associated with using these equations in the diagnostic pathway. Further research is needed to determine whether or not these equations are useful.

M.1.3. Rationale for research recommendation

Download PDF (190K)

M.1.4. Modified PICO table

Download PDF (199K)

Final

Evidence reviews underpinning research recommendation on the diagnostic accuracy of cystatin C equations in the NICE guideline

These evidence reviews were developed by NICE Guideline Updates Team

Disclaimer: The recommendations in this guideline represent the view of NICE, arrived at after careful consideration of the evidence available. When exercising their judgement, professionals are expected to take this guideline fully into account, alongside the individual needs, preferences and values of their patients or service users. The recommendations in this guideline are not mandatory and the guideline does not override the responsibility of healthcare professionals to make decisions appropriate to the circumstances of the individual patient, in consultation with the patient and/or their carer or guardian.

Local commissioners and/or providers have a responsibility to enable the guideline to be applied when individual health professionals and their patients or service users wish to use it. They should do so in the context of local and national priorities for funding and developing services, and in light of their duties to have due regard to the need to eliminate unlawful discrimination, to advance equality of opportunity and to reduce health inequalities. Nothing in this guideline should be interpreted in a way that would be inconsistent with compliance with those duties.

NICE guidelines cover health and care in England. Decisions on how they apply in other UK countries are made by ministers in the Welsh Government, Scottish Government, and Northern Ireland Executive. All NICE guidance is subject to regular review and may be updated or withdrawn.

Copyright © NICE 2021.
Bookshelf ID: NBK574725PMID: 34672494

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