MétaCan
Menu
Back to cohort
Record W4391934434 · doi:10.1016/j.xkme.2024.100806

Beyond Creatinine: Is Cystatin C the New Global Standard for Estimated Glomerular Filtration Rate Evaluation?

2024· editorial· en· W4391934434 on OpenAlex
Gregory L. Hundemer, Manish M. Sood, Ayub Akbari

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKidney Medicine · 2024
Typeeditorial
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsRenal functionCystatin CCreatinineUrologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Accurate assessment of kidney function plays an essential role in routine clinical practice by serving multiple purposes including diagnosis, prognostication, risk stratification, medication dosing, and guidance surrounding therapeutic decisions. Measured glomerular filtration rate (GFR), the gold standard for kidney function assessment,1Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work GroupKDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.Kidney inter., Suppl. 2013; 3: 1-150Abstract Full Text Full Text PDF Google Scholar can be determined via clearance of exogenous filtration markers such as inulin, iothalamate, iohexol, diethylenetriaminepentaacetic acid (DTPA), or ethylenediaminetetraacetic acid (EDTA). However, routine measurement of GFR is impractical as it is complex, cumbersome, time-consuming, and expensive. Instead, estimated GFR (eGFR) is generally utilized as it allows for an efficient and inexpensive method by which to assess kidney function using endogenous filtration markers. Traditionally, creatinine has been the endogenous filtration marker used in eGFR equations; however, cystatin C is an emerging alternative that can be measured in isolation or in combination with creatinine. Over the past 50 years, a number of eGFR equations focusing primarily on creatinine were developed and implemented to varying degrees into clinical practice.2Levey A.S. Bosch J.P. Lewis J.B. Greene T. Rogers N. Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.Ann Intern Med. 1999; 130: 461-470Crossref PubMed Google Scholar, 3Cockcroft D.W. Gault M.H. Prediction of creatinine clearance from serum creatinine.Nephron. 1976; 16: 31-41Crossref PubMed Google Scholar, 4Levey A.S. Stevens L.A. Schmid C.H. et al.A new equation to estimate glomerular filtration rate.Ann Intern Med. 2009; 150: 604-612Crossref PubMed Scopus (18353) Google Scholar, 5Inker L.A. Schmid C.H. Tighiouart H. et al.Estimating glomerular filtration rate from serum creatinine and cystatin C.N Engl J Med. 2012; 367: 20-29Crossref PubMed Scopus (2868) Google Scholar, 6Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.N Engl J Med. 2021; 385: 1737-1749Crossref PubMed Scopus (993) Google Scholar, 7Pottel H. Bjork J. Courbebaisse M. et al.Development and Validation of a Modified Full Age Spectrum Creatinine-Based Equation to Estimate Glomerular Filtration Rate : A Cross-sectional Analysis of Pooled Data.Ann Intern Med. 2021; 174: 183-191Crossref PubMed Scopus (136) Google Scholar, 8Pottel H. Bjork J. Rule A.D. et al.Cystatin C-Based Equation to Estimate GFR without the Inclusion of Race and Sex.N Engl J Med. 2023; 388: 333-343Crossref PubMed Scopus (33) Google Scholar The eGFR value most commonly reported by clinical laboratories comes from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation,4Levey A.S. Stevens L.A. Schmid C.H. et al.A new equation to estimate glomerular filtration rate.Ann Intern Med. 2009; 150: 604-612Crossref PubMed Scopus (18353) Google Scholar, 5Inker L.A. Schmid C.H. Tighiouart H. et al.Estimating glomerular filtration rate from serum creatinine and cystatin C.N Engl J Med. 2012; 367: 20-29Crossref PubMed Scopus (2868) Google Scholar, 6Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.N Engl J Med. 2021; 385: 1737-1749Crossref PubMed Scopus (993) Google Scholar which is recommended by the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines.1Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work GroupKDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.Kidney inter., Suppl. 2013; 3: 1-150Abstract Full Text Full Text PDF Google Scholar Notably, the CKD-EPI equations were updated in 2021 to omit a race-based “correction term” from their calculations.6Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.N Engl J Med. 2021; 385: 1737-1749Crossref PubMed Scopus (993) Google Scholar Other eGFR equations, such as those from the European Kidney Function Consortium (EKFC), have similarly followed suit.8Pottel H. Bjork J. Rule A.D. et al.Cystatin C-Based Equation to Estimate GFR without the Inclusion of Race and Sex.N Engl J Med. 2023; 388: 333-343Crossref PubMed Scopus (33) Google Scholar While creatinine-based eGFR equations were historically utilized in routine clinical practice, the powerful recent initiative to eliminate race from eGFR calculations greatly strengthened the motivation to adopt new markers in eGFR equations that are race-independent, such as cystatin C.9Delgado C. Baweja M. Crews D. et al.A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease.J Am Soc Nephrol. 2021; Google Scholar Given the evolving landscape of eGFR equations, questions surrounding the accuracy of creatinine- versus cystatin C-based eGFR values naturally emerge along with what (if any) clinical implications these potential inaccuracies may bear. As such, multiple recent population-based observational studies have aimed to address eGFRCr versus eGFRCysC differences.10Carrero J.J. Fu E.L. Sang Y. et al.Discordances Between Creatinine- and Cystatin C-Based Estimated GFR and Adverse Clinical Outcomes in Routine Clinical Practice.Am J Kidney Dis. 2023; 82: 534-542Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar, 11Kim H. Park J.T. Lee J. et al.The difference between cystatin C- and creatinine-based eGFR is associated with adverse cardiovascular outcome in patients with chronic kidney disease.Atherosclerosis. 2021; 335: 53-61Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar, 12Chen D.C. Shlipak M.G. Scherzer R. et al.Association of Intra-individual Differences in Estimated GFR by Creatinine Versus Cystatin C With Incident Heart Failure.Am J Kidney Dis. 2022; 80: 762-772 e761Abstract Full Text Full Text PDF PubMed Scopus (8) Google Scholar, 13Chen D.C. Shlipak M.G. Scherzer R. et al.Association of Intraindividual Difference in Estimated Glomerular Filtration Rate by Creatinine vs Cystatin C and End-stage Kidney Disease and Mortality.JAMA Netw Open. 2022; 5e2148940Crossref Scopus (15) Google Scholar, 14Potok O.A. Katz R. Bansal N. et al.The Difference Between Cystatin C- and Creatinine-Based Estimated GFR and Incident Frailty: An Analysis of the Cardiovascular Health Study (CHS).Am J Kidney Dis. 2020; 76: 896-898Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar, 15Potok O.A. Ix J.H. Shlipak M.G. et al.The Difference Between Cystatin C- and Creatinine-Based Estimated GFR and Associations With Frailty and Adverse Outcomes: A Cohort Analysis of the Systolic Blood Pressure Intervention Trial (SPRINT).Am J Kidney Dis. 2020; 76: 765-774Abstract Full Text Full Text PDF PubMed Scopus (39) Google Scholar It appears, on average, that eGFRCysC is lower than eGFRCr. Furthermore, approximately 30% of individuals with both an eGFRCr and eGFRCysC measure demonstrated a discrepancy of 15 mL/min/1.73m2 or more. Those individuals with the most substantial decrease in eGFR when transitioning from creatinine-based equations to cystatin C-based equations were older with greater albuminuria and more comorbid conditions. These differences were not trivial as adverse outcomes including acute kidney injury (AKI), end-stage kidney disease, major adverse cardiovascular events, and death were more common in those with a greater discrepancy. Therefore, identifying discordance between eGFRCr and eGFRCysC appears to be of major clinical relevance. These common, and often prominent, inter-individual differences between eGFRCr and eGFRCysC suggest that there are likely non-GFR-related variables at play that must be considered. For instance, perhaps the most well-known and reported factor is race, as historical observational data reported that Black individuals had higher average serum creatinine levels compared to non-Black individuals.16Lewis J. Agodoa L. Cheek D. et al.Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate.Am J Kidney Dis. 2001; 38: 744-753Abstract Full Text Full Text PDF PubMed Google Scholar This was the driving rationale for the inclusion of a race-based “correction term” that, for any given serum creatinine level, results in a higher eGFR value for Black versus non-Black individuals. Ultimately, these race “correction terms” have largely gone by the wayside given that race is a social (rather than biological) construct that ignores the wide genetic diversity within individuals who self-identify as Black.9Delgado C. Baweja M. Crews D. et al.A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease.J Am Soc Nephrol. 2021; Google Scholar An advantage of cystatin C-based eGFR equations was the apparent limited variation between races, thus supporting their more widespread adoption as a true “global” endogenous filtration marker. Notably, other important factors beyond race may contribute to measurement discrepancies including muscle mass, obesity, diet, physical activity, smoking, and medications/substances that influence tubular secretion.17Liu X. Foster M.C. Tighiouart H. et al.Non-GFR Determinants of Low-Molecular-Weight Serum Protein Filtration Markers in CKD.Am J Kidney Dis. 2016; 68: 892-900Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar,18Knight E.L. Verhave J.C. Spiegelman D. et al.Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement.Kidney Int. 2004; 65: 1416-1421Abstract Full Text Full Text PDF PubMed Scopus (840) Google Scholar However, an enhanced understanding of the relative importance of each of these factors to eGFR discrepancy would better facilitate interpretation. In this issue of Kidney Medicine, Chen et al conducted a large observational study using the UK Biobank to assess the prevalence and predictors of discordance between creatinine- and cystatin C-based eGFR equations.19Chen D.C. Lu K. Scherzer R. et al.Cystatin C- and Creatinine-based Estimated GFR Difference: Prevalence and Predictors in the UK Biobank.Kidney Med. 2024; (In Press)Abstract Full Text Full Text PDF PubMed Google Scholar The UK Biobank comprehensively collects data on a wide range of sociodemographic, lifestyle, comorbidity, medication, physical, and laboratory non-GFR factors that facilitated multivariable modeling methods to examine differences between eGFRCr and eGFRCysC. The study included nearly 500,000 adults aged 40 to 69 years with a mean eGFR of ∼90 mL/min/1.73m2Levey A.S. Bosch J.P. Lewis J.B. Greene T. Rogers N. Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.Ann Intern Med. 1999; 130: 461-470Crossref PubMed Google Scholar at the time of enrollment (2006 to 2010) who underwent standardized health and lifestyle assessments along with same day measurements of serum creatinine and cystatin C. eGFRCr was calculated using the 2021 CKD-EPICr equation6Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.N Engl J Med. 2021; 385: 1737-1749Crossref PubMed Scopus (993) Google Scholar while eGFRCysC was calculated using the 2012 CKD-EPICysC equation.5Inker L.A. Schmid C.H. Tighiouart H. et al.Estimating glomerular filtration rate from serum creatinine and cystatin C.N Engl J Med. 2012; 367: 20-29Crossref PubMed Scopus (2868) Google Scholar The mean eGFRCysC (88 mL/min/1.73m2) was lower on average than eGFRCr (95 mL/min/1.73m2), consistent with prior studies.19Chen D.C. Lu K. Scherzer R. et al.Cystatin C- and Creatinine-based Estimated GFR Difference: Prevalence and Predictors in the UK Biobank.Kidney Med. 2024; (In Press)Abstract Full Text Full Text PDF PubMed Google Scholar Similarly, 30% of individuals had an eGFRCr and eGFRCysC difference of 15 mL/min/1.73m2 or greater comprised of 25% with eGFRCysC lower than eGFRCr by 15 mL/min/1.73m2 or more and 5% with eGFRCr lower than eGFRCysC by 15 mL/min/1.73m2 or more. In multivariable analysis, prominent predictors of eGFRCysC being lower than eGFRCr included older age, male sex, South Asian ethnicity, smoking, lower socioeconomic status, comorbidities (e.g., diabetes, hypertension, cancer, thyroid disease, etc.), glucocorticoid use, waist circumference, body fat percent, and greater albuminuria. Prominent predictors of eGFRCr being lower than eGFRCysC included Black race (OR 7.32 [95% CI 6.80-7.89]), dietary meat consumption, and use of trimethoprim-containing medications. The investigators also developed and tested three prediction models for identifying likely eGFRCr versus eGFRCysC discordance: 1) an all-encompassing model, 2) excluding race/ethnicity, and 3) a simplified clinical model restricted to only variables collected as part of routine practice. All models demonstrated fair-to-good discrimination (C-statistic in the 0.70-0.75 range) along with good calibration. Several limitations with this study should be taken into consideration. Most notably, the lack of measured GFR does not allow for the determination of whether serum creatinine or cystatin C was the primary source of bias in cases of wide eGFR discordance. Moreover, the reliance on single-day serum creatinine and cystatin C values does not account for the day-to-day variability in these measurements that can impact eGFR calculation and potentially the discordance between creatinine- and cystatin C-based results.20Thoni S. Keller F. Denicolo S. Buchwinkler L. Mayer G. Biological variation and reference change value of the estimated glomerular filtration rate in humans: A systematic review and meta-analysis.Front Med (Lausanne). 2022; 91009358PubMed Google Scholar Nevertheless, this study provides a nice addition to the literature in assessing the non-GFR factors that may explain differences between creatinine- and cystatin C-based eGFR values. Encountering eGFR differences will become increasingly frequent with more widespread adoption of cystatin C measurements. As opposed to simply looking at single factors in isolation, the present study used expansive multivariable models to comprehensively identify independent associations between a host of variables and eGFRCr versus eGFRCysC discordance. Does this study suggest that cystatin C is ready for widespread adoption and to be crowned the new king of eGFR? It is not that clear cut. First, it hints at a broader spectrum of race/ethnicity contributions to eGFR discordance which historically focused solely on Black versus non-Black comparisons. While not only did the study find that Black individuals had over 7-fold higher odds for having lower eGFRCr, it found that South Asians had 60% higher odds for having lower eGFRCysC. This illustrates and complicates the optimal filtration marker in racially and ethnically diverse populations. Second, cystatin C is significantly more expensive than serum creatinine thereby limiting its use in resource-limited settings. Certainly, the costs of widespread measurements of cystatin C may not be feasible in all locations. Therefore, there may be instances where the need for cystatin C may be determined on a case-by-case basis rather than for the whole of the population. Identifying specific sub-populations where a wide discrepancy between creatinine- and cystatin C-based eGFR measures would be expected due to non-GFR factors may help to better prioritize these finite testing resources. Finally, as nephrologists will increasingly need to compare creatinine- and cystatin C-based eGFR results, standardized creatinine values traceable to isotope dilution mass spectrometry (IDMS) and standardized cystatin C values traceable to the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) should exclusively be employed. This will allow for a more reliable, standardized approach in both clinical practice and future research studies by which to compare eGFR results. Cystatin C- and Creatinine-based Estimated GFR Differences: Prevalence and Predictors in the UK BiobankKidney MedicinePreviewLarge differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) occur commonly. A comprehensive evaluation of factors that contribute to these differences is needed to guide the interpretation of discrepant eGFR values. Full-Text PDF Open Access

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.370
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it