Cystatin C-based equations: Enhancing accuracy in kidney function tests for type 2 diabetes

Abstract

Approximately 30%-40% of individuals with diabetes develop chronic kidney disease during their lifetime, and patients with type 2 diabetes mellitus have a high risk of developing and progressing to this condition. The two comorbidities represent a lethal combination that exacerbates both diseases. It is crucial to measure the glomerular filtration rate and to monitor and assess the renal functionality of these patients. Serum creatinine, the traditional marker of kidney assessment, has been shown to be susceptible to too many variables that can significantly alter the final estimated glomerular filtration rate outcome. Cystatin C-based formulas appear to have reasonable accuracy in this population and help to ensure better tailored therapy and renal assessment. The purpose of this editorial was to provide an examination of the advantage of using cystatin C as a valid marker for determining estimated glomerular filtration rate, free from any interfering factors, allowing a more accurate assessment of renal function.

Key Words: Diabetes mellitus; Diabetic kidney disease; Cystatin C; Glomerular filtration rate; Chronic kidney disease

Core Tip: It is crucial to accurately determine the correct renal function of patients with type 2 diabetes. The use of creatinine alone has several limitations that can lead to an imprecise evaluation of the estimated glomerular filtration rate. Cystatin C appears to effectively mitigate the biases associated with the traditional determination of renal function using creatinine, and cystatin C-based equations provide a more precise and accurate method for estimating renal function in patients with type 2 diabetes mellitus, particularly in clinical contexts where muscle mass can be a harbinger of doubt and misunderstanding.

INTRODUCTION

Diabetes mellitus has been known for over 3000 years, but only about a century ago its mechanism was understood after discovering insulin produced by the islets of Langerhans in the pancreas, which is fundamental for glucose metabolism and the maintenance of normal blood sugar. Diabetes mellitus is caused by insufficient insulin production (type 1) or insulin resistance (type 2). For millennia, diabetes mellitus has been considered a kidney disease; however, with the understanding of its pathogenesis, it has emerged that diabetic kidney disease (DKD) is a complication of type 2 diabetes mellitus (T2DM) and not a cause. DKD is characterized by an expansion of the mesangial matrix and diffuse thickening of the glomerular and tubular basement membranes, caused by hyperglycemia[1]. The increase in T2DM cases has led to a greater frequency of overlapping diagnoses, making a distinction between DKD and non-DKD necessary. Further complicating the diagnostic issue is the increasing incidence of DKD without significant proteinuria, a common manifestation in patients with T2DM that defies traditional guidelines.

The distinction between diabetes-related and non-diabetes-related forms of kidney disease is not just a semantic issue, as it requires different therapeutic approaches[2]. Diabetes mellitus is a growing problem for global health and the public economy. It can lead to subtle macrovascular and microvascular complications that affect patient quality of life[3]. Once established, DKD slowly progresses to end-stage kidney disease (ESKD)[4]. DKD is the most common cause of chronic kidney disease (CKD) and ESKD, affecting approximately 30%-40% of people with diabetes mellitus[5]. ESKD is on the rise in the United States, with a 41.8% increase in incident cases and a 118.7% increase in prevalent cases between 2000 and 2019. Diabetes and hypertension remain the leading causes. Asian, Hispanic, and Native Pacific Islander populations are most affected[6]. It is estimated that approximately 3% of patients[2] newly diagnosed with T2DM already have established DKD, and a significant percentage develop renal complications over time. Identifying DKD early is essential to reduce mortality and morbidity and delay disease progression.

ASSESSMENT OF KIDNEY FUNCTION

DKD is a global phenomenon that is underestimated[7] because the differential diagnosis between diabetic and non-diabetic disease is made more complex by the increasing incidence of DKD without significant proteinuria and because of the clinical status of patients and their comorbidities. This often requires the use of clinical, laboratory, and imaging criteria. A renal biopsy, although considered the diagnostic gold standard for the diagnosis of DKD, is often not always performed. A renal biopsy should be performed for differential diagnosis in cases where other or overlapping glomerular involvement is suspected. This procedure was underutilized in the past when steroid-based therapy for glomerulonephritis was the norm and diabetes was considered a relative contraindication. The remarkable development of non-steroid based therapies and advances in the treatment of glomerular disease pose a threat to these limitations and may prioritize renal biopsy[2].

Nevertheless, the diagnosis of DKD is often made with the help of clinical and laboratory tests. To this end, it is crucial to ensure the most accurate non-invasive tests possible and to achieve a tailored diagnostic approach. A well-known medical axiom states that although the disease may be constant, each patient is unique. It follows that these tests must have high sensitivity and specificity if they are of such paramount importance. Each person is unique in terms of ethnicity, comorbidities, age, lifestyle, weight, and phenotypic characteristics. Therefore, precisely because of the unique characteristics of each patient, it is necessary to customize the assessment of renal function using different methods to make the determination as accurate as possible.

To perform phenotyping in the determination of renal function, different methods must be used. Among the various methods that can be used to determine kidney function (Table 1), the formula of the CKD Epidemiology Collaboration (EPI), CKD-EPI 2009, played a dominant role alongside the now less used Modification of Diet in Renal Disease (MDRD) and Cockcroft and Gault. Recently, the 2009 CKD-EPI was further improved by eliminating the variable associated with ethnicity[8]. An evidence-based, ethnicity-free method for the estimated glomerular filtration rate (eGFR) was proposed by a working group established in 2020 by the National Kidney Foundation (NKF) and the American Society of Nephrology (ASN). Implementation of the CKD-EPI 2021 for eGFR using creatine and expanding the use of cystatin C testing were recommended in the final report published by the NKF/ASN Task force after a thorough evaluation of over 20 approaches[9].

Table 1 Comparison of estimated glomerular filtration rate equations based on creatinine and/or cystatin C, highlighting biomarkers, clinical variables, advantages, and limitations.

Equation	Biomarkers used	Variables used	Year/version	Advantages	Limitations	Main features
Cockcroft and Gault	Creatinine	Age, weight, sex	1976	Simple, used for drug dosing	Underestimates GFR in slim and overestimates GFR in obese older patients, not accurate for CKD staging, not validated in older population	Estimates creatinine clearance; less precise for eGFR. It has not been expressed using standardized creatinine values. It can overestimate kidney function
4-parameters MDRD	Creatinine	Age, sex, BSA	2002	Standardized, widely used in older studies	Less accurate for high eGFR values	Abstract version of the 1999 expanded formula with 6 variables. The equation has not been validated in patients over 70 years of age, though it is still applied in these subjects
CKD-EPI 2009	Creatinine	Age, sex, race	2009	Improved accuracy over MDRD, widely used	Still affected by muscle mass, not always optimal	Dominant equation; initially included ethnicity
BIS1	Creatinine	Age, sex	2012	Designed for older adults, more accurate	Limited external validation	Developed for elderly populations (BIS)
BIS2	Creatinine + cystatin C	Age, sex	2021	Improved accuracy in elderly, accounts for muscle mass loss	Limited validation outside European cohorts, higher cost	BIS equation combining creatinine and cystatin C; optimized for geriatric populations
FASCr	Creatinine	Age	2017	Applicable to all ages, better performance	Limited validation in elderly with CKD	FAS equation; better for diverse ages/clinical conditions
FASCr-Cys	Creatinine + cystatin C	Age	2017	Optimized for all ages, reliable in CKD	More expensive, not always available	Combined FAS version; versatile across populations
EKFC (creatinine)	Creatinine	Age, sex	2020	Ethnicity-independent, validated in healthy populations	Less accurate in acute kidney injury or extremes of BMI	Ethnicity- and sex-independent; based on mean creatinine in healthy individuals
CKD-EPICr-Cys	Creatinine + cystatin C	Age, sex	2021	Most accurate among different populations	Higher cost, requires additional testing	Combined CKD-EPI equation; recommended for elderly with impaired renal function
CKD-EPI 2021 (creatinine)	Creatinine	Age, sex	2021	Removes race coefficient, more equitable	Slight underestimation in Black individuals	Removed ethnicity factor; improved for multiethnic populations
CKD-EPI 2021 (cystatin C)	Cystatin C	Age, sex	2021	Unaffected by muscle mass, reliable in sarcopenia	Costly, influenced by inflammation/thyroid disorders	Cystatin C-specific CKD-EPI equation; alternative to creatinine
CKD-EPI 2021 (creatinine-cys)	Creatinine + cystatin C	Age, sex	2021	Most accurate among different populations	Higher cost, requires additional testing	Combined equation; recommended by KDIGO 2024 for accuracy
EKFC (cystatin C)	Cystatin C	Age, sex	2023	Ethnicity-independent, validated in multiple regions	Limited data in non-European populations	Cystatin C-specific EKFC equation; validated in Europe, United States, and Africa

GFR: Glomerular filtration rate; eGFR: Estimated glomerular filtration rate; CKD: Chronic kidney disease; MDRD: Modification of Diet in Renal Disease; EPI: Epidemiology collaboration; BMI: Body mass index; BIS: Berlin Initiative Study; FASCr: Full age spectrum from creatinine; BSA: Body surface area; Cys: Cystatin equation; FAS: Full age spectrum; EKFC: European Kidney Function Consortium; EPICr: Epidemiology collaboration equation from creatinine; KDIGO: Kidney disease: Improving global outcomes.

The most equitable approach was to remove ethnicity from the methodology for assessing kidney function. Blacks and African Americans, Hispanics and Latinos, and other racial and ethnic minorities are already disproportionately affected by diabetes, hypertension, and kidney disease; the inclusion of ethnicity in clinical algorithms has exacerbated these disparities. In addition, there are major disparities in kidney care for these same people, including poorer access to nephrology services, home dialysis, and kidney transplants[10].

The current Kidney Disease: Improving global outcomes (KDIGO) 2024 guidelines recommend the use of serum creatinine (sCr) as the first step in eGFR[8]. Unfortunately, creatinine-based estimation of eGFR may systematically mystify renal function. This is because creatinine, the traditional marker, may be affected by muscle wasting, which is common in patients who have been critically ill for a long time. Creatinine is influenced by factors such as endogenous metabolism and muscle mass as well as age, gender, ethnicity, height, or weight. This also applies to elderly, fragile patients par excellence in whom organ aging, vascular calcification, and sarcopenia coexist. In this category of patients, the relatively frequent loss of muscle mass in the geriatric population can lead to an overestimation of the creatinine value and thus the eGFR.

In this context, the introduction of two eGFR equations specifically developed for older cohorts, namely the Berlin Initiative Study and the full age spectrum (FAS) equations, could help to bridge the problem. Among the creatinine-based equations, the Berlin Initiative Study 1 and FAS creatinine (FASCr) performed better than the CKD epidemiology collaboration equation from sCr in older adults in primary care, with FASCr potentially better suited to different clinical conditions[11,12]. The integration of cystatin C with creatinine in the glomerular filtration rate (GFR) equations improved the applicability of the estimates.

Cystatin C is a low molecular weight protein (a member of the cystatin superfamily of cysteine protease inhibitors) that is filtered in the glomerulus and is not reabsorbed and metabolized in the tubules[8]. Elevated cystatin C levels are indicative of an underlying renal problem[13]. Among the combined equations, the FASCr cystatin equation proved to be versatile in different conditions. For older adults with impaired renal function, the CKD, epidemiology collaboration equation from creatinine and cystatin equation was the more appropriate choice[12]. However, further research is needed to develop GFR estimation equations with greater precision[14].

KDIGO 2024 guidelines[8] also suggest the use of cystatin C, which has been shown to be a more accurate indicator of true renal function, as it does not appear to be affected by the muscle mass loss associated with prolonged critical illness, as a further improvement in the estimation of renal function profile. This makes cystatin C a particularly useful alternative biomarker and a more reliable indicator for patients with a history of critical illness[15].

A prospective cohort study of over 26000 patients in the United States has shown that eGFRcys significantly improves the risk categorization for renal failure and mortality compared to eGFRcr and albuminuria alone[16]. In the study of Lees et al[17], eGFRcys correlated with cardiovascular disease risk across the eGFR spectrum and improved cardiovascular disease risk prediction in a comparable manner to recognized risk variables, including lipids. Recent studies show that GFR values estimated with cystatin C and creatinine can predict renal damage in patients with diabetes mellitus[18]. This information opens up new research scenarios that are expected to yield important results in many areas, including other comorbidities commonly associated with chronic renal failure such as heart failure. Further studies in large populations will need to confirm this hypothesis[19].

The European Kidney Function Consortium (EKFC) has developed a novel eGFR equation that uses sex-specific and age-specific mean creatinine levels in healthy individuals to estimate the GFR of individuals across the age spectrum[20]. Recently, an EKFC eGFR-cystatin C-based equation was published that is independent of ethnicity and gender. This equation is based on the same mathematical principle as the creatinine-based EKFC equation and is more accurate than the equations routinely used in cohorts from Europe, the United States, and Africa[21].

The CKD-EPI-GFR estimating equations recommended by KDIGO 2024 are also based on both cystatin C and creatinine[8]. Like the 2021 CKD-EPI-creatinine equation, the assessment of renal function using cystatin C was developed using the 2021 CKD-EPI-creatinine-cystatin C equation without a term for race[22]. The 2021 CKD-EPI cystatin C and creatinine-cystatin C equations were developed to overcome the limitations of creatinine-based GFR estimation, particularly in populations where muscle mass variations significantly impact sCr levels. Comparative studies indicate that cystatin C-based equations generally exhibit higher sensitivity in detecting early kidney function decline, especially in patients with DKD[23]. However, specificity may vary depending on patient characteristics, with non-GFR determinants of cystatin C influencing its accuracy[24].

A study by Inker et al[22] comparing the performance of CKD-EPI equations found that the creatinine-cystatin C equation provides the most accurate estimates of measured GFR, with an improved ability to correctly classify CKD stages. This is particularly relevant in patients with diabetes, where early and accurate detection of CKD can guide treatment decisions and prevent complications[22]. However, in specific patient populations, such as those with chronic inflammatory conditions or endocrine disorders, cystatin C alone may not offer significant advantages over creatinine-based estimates[25].

THE USE OF CYSTATIN C-BASED EQUATIONS IN PATIENTS WITH T2DM

Repeated measurements of albuminuria and eGFR are currently the two most important clinical markers used for the diagnosis of DKD. According to the latest guidelines from the American Diabetes Association, all patients with T2DM and those with T1DM who have had the disease for more than 5 years should have their albuminuria checked annually by an albumin/creatinine ratio spot urine test. Depending on the stage of CKD, patients with established CKD should have their albumin/creatinine ratio checked one to four times a year.

As an important diagnostic sign, albuminuria has some disadvantages including not providing a clear indication of kidney disease or DKD. In addition, in the early stages of glomerulopathy, the 24-h microalbuminuria usually fluctuates[26]. In fact, a significant percentage of patients, especially those with T2DM, develop CKD with a sharp drop in GFR and no or only slightly increased albuminuria. Moreover about 30% of patients with diabetes with kidney damage do not have albuminuria[27]. As just discussed in the previous paragraphs, numerous factors are likely to have an influence on serum as well as urine creatinine concentration[28]. Urine creatinine is influenced not only by glomerular filtration but also by excretion from the renal tubules. Therefore, the GFR estimate based on creatinine clearance may be overestimated[29].

The search for non-invasive diagnostic markers with high sensitivity and specificity is therefore the goal of the development path of clinical nephrology. It is necessary to search for non-invasive markers that have a therapeutic and prognostic effect as the number of patients with DKD increases. This type of patient requires a more precise and feasible biomarker for eGFR, and cystatin-C has been shown to be an accurate method for measuring renal function.

In patients with DKD, cystatin C has demonstrated superior accuracy in estimating kidney function compared to creatinine. A significant limitation of creatinine-based GFR estimation in diabetes is its dependence on muscle mass, which can lead to overestimation of kidney function in patients with sarcopenia or advanced disease. In contrast, cystatin C is unaffected by muscle mass and provides a more reliable assessment of kidney function across different stages of DKD[1]. Beyond its diagnostic role, cystatin C has emerged as a valuable prognostic biomarker. Studies have shown that higher baseline levels of cystatin C and a rapid increase over time are associated with an elevated risk of DKD progression, cardiovascular complications, and mortality[2,3]. Unlike creatinine, which may remain stable in the early stages of DKD despite significant renal impairment, cystatin C can detect subtle declines in kidney function earlier, enabling timely interventions[4]. Since the kidney is the only organ responsible for excreting cystatin C from the bloodstream, GFR is an important regulator of serum cystatin C concentrations. Cystatin C has gained increasing attention as a superior biomarker for estimating kidney function, offering an alternative to traditional creatinine-based equations. Its independence from muscle mass makes it particularly valuable in specific populations, such as the elderly, patients with sarcopenia, or individuals with chronic illnesses affecting muscle metabolism.

Despite its advantages cystatin C is not devoid of limitations, and a critical appraisal of its potential confounding factors is essential for accurate clinical interpretation. One of the most significant concerns is its role as an acute-phase reactant, which makes its levels susceptible to fluctuations in response to systemic inflammation[20]. Conditions such as infections, autoimmune disorders, and chronic inflammatory states can lead to artificially elevated cystatin C levels, potentially resulting in an overestimation of kidney dysfunction[24].

Cystatin C facilitates the processing of pro-granzymes and other compounds in immune cells, promotes antigen presentation, enhances the maturation of dendritic cells, controls integrin activity, and is involved in building the skin barrier, which serves as the primary defense mechanism of the body[30]. Consequently, inflammatory conditions can increase the synthesis of cystatin C, leading to high blood levels despite normal kidney function. The ubiquity of inflammation in various diseases, particularly cardiovascular disease or obesity, complicates the use of cystatin C as a prognostic biomarker. Thus, the correlation between cystatin C levels and negative results may be more strongly influenced by the underlying inflammatory disease[31].

Additionally, thyroid dysfunction can potentially affect cystatin C concentrations, with hyperthyroidism leading to lower values and hypothyroidism causing increased levels, independent of renal clearance[25]. These alterations highlight the need for caution when interpreting eGFR values in patients with endocrine disorders.

Another critical factor is the influence of corticosteroids, which may contribute to a dose-dependent increase in cystatin C levels, which could affect the eGFR in patients on long-term glucocorticoid therapy or receiving high doses of this therapy[32]. Given these confounding variables, the use of the 2021 CKD-EPI creatinine-cystatin C equation has been advocated as a means of mitigating these biases, leveraging the combined strengths of both biomarkers to enhance eGFR accuracy[23].

Despite these limitations, cystatin C remains a valuable tool, particularly when used in conjunction with creatinine. However, in cases where non-GFR determinants are suspected to be significantly altering cystatin C levels, direct GFR measurement using exogenous markers such as iohexol or iothalamate clearance should be considered as a confirmatory test[8]. Future research should focus on refining eGFR equations by integrating additional clinical parameters to further optimize the precision of kidney function assessment[22]. According to several meta-analysis, serum cystatin C has a remarkable diagnostic performance for DKD. However, serum cystatin C has not been shown to be a better indicator of GFR in patients with diabetes than creatinine[33-35]. Rather, the combined sCr-cystatin C equation appears to be a superior method to fulfill the need for accurate GFR calculation and risk assessment for CKD progression in patients with diabetes[36].

Recently Tran et al[37] investigated the efficacy of cystatin C-based equations in elderly patients with age-related decline in renal function. Compared to the creatinine-based equations, the cystatin C-based equations showed lower eGFRs. The 2021 CKD-EPI creatinine-cystatin C equation and the MDRD showed good agreement. The authors emphasized that treatment adjustment and tailored therapy depending on the patient’s renal status may be possible if cystatin C-based equations are used to detect early loss of renal function in elderly patients. The authors suggested that the MDRD equation, which shows strong agreement with cystatin C-based equations, can be considered in situations where cystatin C cannot be detected.

According to a recent study, people with T2DM who had high baseline levels of cystatin C and a large increase in cystatin C had a higher risk of developing DKD later in life[36]. It is important to note that both the United States NKF and the ASN have strongly advocated routine cystatin C screening[38]. Two recent studies have shown that the combined creatinine-cystatin C eGFR equation performs better than equations based on either marker, which is consistent with this recommendation. These studies also emphasized the need for more frequent cystatin C measurements in the clinical context[39,40].

A mendelian randomization study reported that higher levels of cystatin C represent a risk factor for DKD independent of body mass index and systolic blood pressure in DM patients[41]. He et al[42] proposed the evaluation of the difference between cystatin C-based and creatinine-based eGFR to stratify the risk of developing microvascular complications in adult patients with T2DM. In their prospective cohort study, they found that a large eGFR was independently associated with the risk of diabetic microvascular complications and their subtypes.

The application of cystatin C-based equations in patients with DKD has been an area of growing interest due to their potential to enhance risk stratification. Patients with DKD often present comorbid cardiovascular disease, obesity, and metabolic syndrome, all of which can influence GFR estimation[8]. Several studies have indicated that cystatin C-based equations better predict cardiovascular events and mortality in patients with DKD compared to creatinine-based equations[32]. This suggests that cystatin C may reflect not only kidney function but also the broader metabolic and inflammatory burden of these patients, reinforcing its role as a biomarker for cardiovascular risk stratification.

COST, ACCESSIBILITY, AND LOGISTICAL CHALLENGES OF CYSTATIN C TESTING

While cystatin C is increasingly recognized as a valuable biomarker for estimating kidney function, its routine implementation in clinical practice faces several challenges, particularly related to cost, accessibility, and logistical feasibility. The cost of cystatin C testing remains significantly higher than that of creatinine measurement, limiting its widespread adoption in many healthcare settings. Cystatin C tests can be performed on standard analyzers available in most laboratories, resulting in comparable labor costs for cystatin C and sCr tests. Nevertheless, prices for cystatin C reagents are approximately $5-$10 per test, while the cost of sCr testing in the United States is approximately $0.50 per test; this cost differential is expected to decrease as cystatin C testing becomes more widely available[43]. A cost-effectiveness analysis suggested that incorporating cystatin C into routine kidney function assessment could be beneficial for specific high-risk populations, such as individuals with CKD and diabetes, where improved risk stratification could lead to better outcomes[44]. However, routine use in general clinical practice remains economically challenging.

Another major limitation is accessibility, particularly in low-income and middle-income countries. In these settings, laboratory infrastructure is often limited, and access to cystatin C testing may be restricted to specialized centers[45]. Additionally, variability in assay standardization across laboratories further complicates its routine use[23]. From a logistical perspective, many clinical laboratories do not yet perform cystatin C testing as a routine analysis due to the need for calibrated immunoassays and automated analyzers, which may not be available in all institutions[32]. Moreover, turnaround times for cystatin C results are often longer compared to creatinine, potentially delaying clinical decision-making in acute settings[8]. To overcome these barriers, future research should focus on the cost-effectiveness of cystatin C testing, assay standardization, and its integration into routine laboratory workflows. Additionally, healthcare policies should consider subsidizing cystatin C testing in high-risk populations, where its use could lead to significant clinical and economic benefits.

FUTURE DIRECTIONS

Cystatin C use may have a role in artificial intelligence (AI). Advanced algorithms are producing many new, promising ways to improve DKD diagnosis as AI innovation continues to quicken. Machine learning models can find patterns that human practitioners might miss when the models analyze large datasets. Algorithms that include variables like cystatin C levels along with other health indicators can pinpoint disease risk more accurately and efficiently. AI, when combined with multiple biomarkers, like cystatin C, has the potential for a complete shift toward precision medicine, where all treatments are customized for every patient[46]. This synergy can therefore increase patient outcomes. As researchers refine AI algorithms in addition to improving our knowledge of renal biomarkers, integrated healthcare solutions may become more possible; furthermore, these advanced technologies will likely become standard practice, changing how DKD is managed as well as giving patients new hope. The merging of AI with biomarker science points out large progress in the continuing fight against long-term diseases, signaling a truly meaningful shift toward greatly improved healthcare.

CONCLUSION

Determining early deterioration of eGFR and associated factors would help clinicians to take appropriate measures to improve kidney function, especially among certain categories of frail patients such as patients with diabetes and the elderly. The evaluation of eGFR using cystatin C allows us to improve the accuracy of the evaluation, overcoming the distortions traditionally linked to muscle mass. Specific recommendations should include: (1) Routine cystatin C-based eGFR assessment in high-risk populations, such as patients with diabetes and cardiovascular disease and the elderly, in whom creatinine-based equations may be less reliable; (2) Integration of cystatin C into clinical decision-making to optimize risk stratification, particularly for guiding treatment modifications in DKD and CKD patients; (3) Use of the combined creatinine-cystatin C equation in routine nephrology practice, as recommended by the KDIGO guidelines, to improve GFR estimation accuracy and reduce misclassification of kidney disease severity; and (4) Further research to establish cost-effective models for implementing cystatin C testing in routine practice, ensuring accessibility even in resource-limited settings.

By refining the approach to kidney function assessment, particularly in vulnerable populations, the clinical utility of cystatin C-based equations can be maximized to improve patient outcomes and enhance precision medicine in nephrology. To increase the validity and reliability of the results and make them clinically useful, the study of the relationship between cystatin C and the diagnosis of DKD requires a large sample, a randomized and blinded research design, the use of a uniform gold standard, and a uniform classification of diseases.

Further research is needed to comprehensively evaluate the clinical effectiveness of cystatin C-based equations by comparing their predictive value for the development of CKD, cardiovascular events, and mortality in different populations. Research should also focus on formulating various adjustment factors encompassing all non-GFR determinants of cystatin C in different patient populations, carefully evaluating the temporal variations of cystatin C relative to creatinine with the progression of kidney disease and the implementation of therapeutic interventions and comprehensively investigating the cost-effectiveness of cystatin C measurement in standard clinical practice considering its advantages over creatinine-based assessments.