Chronic kidney disease (CKD) has emerged as a major global public health burden, contributing to substantial morbidity, mortality, and healthcare expenditure. Global Burden of Disease estimates indicate that CKD affected roughly 9.1% of the world's population in 2017 and was responsible for approximately 1.2 million deaths that year, with the burden disproportionately affecting low- and middle-income countries, including India [1]. The Kidney Disease: Improving Global Outcomes (KDIGO) 2012 guidelines classify CKD by cause, glomerular filtration rate (GFR) category, and albuminuria category, providing a standardized framework for staging and risk stratification [2].

Serum creatinine-based eGFR remains the cornerstone of CKD diagnosis and staging, but it is influenced by muscle mass, age, sex, and dietary intake, and typically becomes abnormal only after substantial nephron loss has already occurred. To improve accuracy, cystatin C-based and combined creatinine–cystatin C equations have been developed and validated, demonstrating superior precision, particularly in populations where creatinine-based estimates are less reliable [3]. Because Cystatin C production is largely independent of muscle mass and is freely filtered and almost completely reabsorbed by the proximal tubule, it is considered a more sensitive marker of early GFR decline than creatinine.

Beyond filtration markers, disturbances in mineral metabolism appear early in the course of CKD. FGF-23, a phosphaturic hormone secreted by osteocytes, rises progressively from the earliest stages of CKD, well before overt hyperphosphatemia develops, and has been consistently associated with increased risk of mortality and end-stage renal disease independent of conventional mineral markers [4]. Its co-receptor, soluble Klotho, an anti-ageing protein predominantly expressed in renal tubular cells, declines reciprocally as CKD advances; Klotho deficiency is now recognized as an early and potentially causal event in the FGF-23–Klotho axis dysregulation that characterizes CKD-mineral and bone disorder (CKD-MBD) [5,6].

Clinical prediction models such as the Kidney Failure Risk Equation, which incorporates age, sex, eGFR, and urine albumin-to-creatinine ratio (UACR), have been validated across diverse populations for predicting progression to kidney failure [7,8]. However, these models rely exclusively on conventional parameters and may not capture the biological heterogeneity of CKD progression, particularly the contribution of mineral metabolism disturbances and cellular senescence pathways. Incorporating novel biomarkers into multivariable prediction models has the potential to improve discrimination and enable earlier, targeted intervention.

Despite growing global interest in novel CKD biomarkers, data from Indian tertiary care settings — where the aetiological profile of CKD (diabetic and hypertensive nephropathy predominating) and the pace of disease progression may differ from Western cohorts — remain limited. This study was therefore designed to characterize serum Cystatin C, FGF-23, soluble Klotho, and hs-CRP across the full spectrum of CKD stages in an Indian population, to examine their correlation with conventional renal function parameters, and to develop and validate a multimarker panel for prediction of 12-month CKD progression and associated clinical outcomes.

Study design and setting: This was a prospective, observational, hospital-based cohort study conducted jointly by the Departments of Biochemistry and Nephrology/General Medicine at Index Medical College, Hospital and Research Centre, Indore, Madhya Pradesh, a tertiary care teaching hospital with dedicated nephrology, dialysis, and NABL-accredited biochemistry and immunoassay laboratory facilities. The total study duration was 24 months, comprising protocol finalization and ethics approval (6 months), recruitment and follow-up (12 months), and laboratory/statistical analysis (6 months). Participants: Participants were recruited from the Nephrology outpatient department, inpatient nephrology ward, and renal replacement therapy unit. CKD patients aged 18–70 years with KDIGO-defined CKD stages 1–5, stable renal function for ≥3 months, and willingness to attend follow-up were included. Age- and sex-matched healthy controls (eGFR >90 mL/min/1.73m², UACR <10 mg/g, no diabetes/hypertension) were recruited from hospital staff and attendants. Exclusions comprised maintenance dialysis, transplant recipients, acute kidney injury, active infection, pregnancy, malignancy, and immunosuppressive or corticosteroid therapy. Sample size: Using the correlation-coefficient method (expected r = 0.40 between biomarker level and 12-month progression, α = 0.05, power = 80%), a minimum of 47 participants per group was calculated; this was expanded to accommodate stage-wise sub-analysis and 20% attrition, yielding a total target of 280 participants (30 each in CKD stage 1 and 2, 60 each in stage 3 and 4, 40 in stage 5, and 60 controls). Sample collection and biochemical assays: After overnight fasting, venous blood (~20 mL) and first-morning midstream urine (5 mL) were collected under aseptic conditions. Serum was separated within 2 hours by centrifugation (3000 rpm, 10 minutes) and residual aliquots stored at –80°C for batch analysis. Routine parameters (creatinine, BUN, electrolytes, calcium, phosphate, intact PTH, UACR) were measured by standard automated colorimetric, ion-selective electrode, and electrochemiluminescence immunoassay methods. eGFR was calculated using the CKD-EPI 2021 creatinine–cystatin C combined equation. Serum Cystatin C was measured by particle-enhanced immunoturbidimetric assay; FGF-23 and soluble Klotho by ELISA; and hs-CRP by latex-enhanced immunoturbidimetric assay. Follow-up and outcomes: CKD patients were followed clinically and biochemically at 3, 6, and 12 months. The primary outcome, CKD progression, was defined as a sustained ≥40% decline in eGFR from baseline (confirmed ≥90 days apart) or initiation of renal replacement therapy. Secondary outcomes included MACE, worsening anaemia, and CKD-related hospitalization. Statistical analysis: Data were analysed using IBM SPSS v26.0 and MedCalc v20.1. Continuous variables were expressed as mean ± SD or median [IQR] as appropriate, and compared across stages using one-way ANOVA or Kruskal–Wallis tests with post-hoc correction. Correlations were assessed by Pearson's/Spearman's coefficients. Binary logistic regression identified independent predictors of progression; ROC analysis determined sensitivity, specificity, and AUC for individual and combined markers; and a multimarker panel was constructed using stepwise logistic regression. A p-value <0.05 was considered significant. Ethical considerations: The study was approved by the Institutional Ethics Committee, and written informed consent was obtained from all participants in English or Hindi, with assurance of confidentiality and voluntary withdrawal at any time.

Table 1. Baseline Demographic Characteristics

Age, diabetes, and hypertension prevalence rose progressively with advancing CKD stage, while sex distribution and BMI showed comparatively modest change, confirming that the cohort reflects a typical diabetic/hypertensive-predominant Indian CKD population and validating between-stage comparability apart from these expected covariates.

Table 2. Routine Biochemical Parameters

eGFR declined progressively from 98 mL/min/1.73m² in controls to 11 mL/min/1.73m² in CKD stage 5, validating stage classification. PTH and phosphate rose sharply from stage 3 onwards, while calcium and haemoglobin fell in parallel, reflecting the interlinked development of CKD-mineral and bone disorder and renal anaemia as GFR declines.

Table 3. Serum Novel Biomarkers

Serum Cystatin C, FGF-23, and hs-CRP increased progressively across CKD stages, while soluble Klotho showed a reciprocal, continuous decline. The steep rise in FGF-23 beginning at stage 3, well before overt hyperphosphatemia, supports its role as an early compensatory phosphaturic signal in CKD-MBD, while the parallel fall in Klotho is consistent with progressive loss of functional renal tubular mass.

Table 5. Correlation of Biomarkers with eGFR

Cystatin C showed the strongest inverse correlation with eGFR among all markers tested, reaffirming its close biological relationship to filtration function, while soluble Klotho showed the strongest positive correlation, consistent with its role as a marker of preserved tubular reserve.

Table 6. Logistic Regression for 12-Month CKD Progression

On multivariable analysis, serum Cystatin C carried the highest adjusted odds ratio for progression, followed by diabetes mellitus and urinary NGAL, while soluble Klotho was independently protective (OR <1), indicating that higher Klotho levels are associated with slower disease progression even after adjustment for conventional risk factors.

Table 7. ROC Analysis for Prediction of CKD Progression

Serum Cystatin C demonstrated the highest individual diagnostic accuracy for 12-month progression (AUC 0.94), followed closely by soluble Klotho (AUC 0.90) and urinary NGAL (AUC 0.91), all within the "excellent" discrimination range.

Table 8. Comparative Performance of Predictive Models

The multimarker panel (Cystatin C + NGAL + FGF-23 + soluble Klotho) achieved the highest overall accuracy (AUC 0.98), substantially outperforming both eGFR alone and the current standard eGFR+UACR combination, indicating meaningful incremental predictive value from novel biomarker integration.

Table 9. Twelve-Month Clinical Outcomes

Of 220 CKD patients followed for 12 months, 72 (32.7%) met the composite progression endpoint. Progressors experienced significantly higher rates of dialysis initiation, MACE, hospitalization, and mortality than non-progressors, confirming the clinical relevance of the biochemical progression endpoint used in this study.

This prospective cohort study demonstrates that serum Cystatin C, FGF-23, and soluble Klotho track closely with CKD severity and independently predict 12-month disease progression in an Indian tertiary care population, with a combined multimarker panel substantially outperforming conventional markers such as eGFR and UACR. The superior correlation of Cystatin C with eGFR compared with creatinine-based indices is consistent with its established biological advantages: being a low-molecular-weight protein produced at a constant rate by nucleated cells and cleared almost exclusively by glomerular filtration, Cystatin C is less influenced by muscle mass, diet, and tubular secretion than creatinine. This property underlies its incorporation into the 2021 CKD-EPI creatinine–cystatin C equation, which was developed specifically to improve the accuracy and equity of GFR estimation [3]. Our finding of an AUC of 0.94 for Cystatin C in predicting progression aligns with growing evidence that Cystatin C-based indices provide earlier and more precise identification of declining renal function than creatinine alone. The progressive elevation of FGF-23 from CKD stage 3 onward, preceding overt hyperphosphatemia, corroborates prior large cohort data showing that FGF-23 rises early in CKD as a compensatory phosphaturic hormone and is independently associated with mortality and progression to end-stage renal disease, even after adjustment for phosphate, PTH, and vitamin D status [4]. This supports the concept that FGF-23 elevation is not merely a marker of advanced mineral bone disease but an early, mechanistically relevant signal of disturbed phosphate homeostasis. The reciprocal decline in soluble Klotho paralleled the rise in FGF-23, consistent with the physiological role of Klotho as an obligate co-receptor for FGF-23 signalling in the kidney and parathyroid gland. Renal tubular Klotho expression falls early in CKD, preceding measurable declines in eGFR in several experimental and clinical studies, and Klotho deficiency has been proposed as a unifying mechanism linking accelerated vascular calcification, left ventricular hypertrophy, and CKD-MBD to loss of functional nephron mass [5,6]. The independent protective association we observed (OR 0.993 per unit increase) supports Klotho's candidacy as both a biomarker and a potential therapeutic target, an area of active ongoing investigation. Importantly, the multimarker panel combining Cystatin C, NGAL, FGF-23, and Klotho achieved markedly superior discrimination (AUC 0.98) compared with eGFR+UACR (AUC 0.84), the current clinical standard endorsed by KDIGO for risk stratification [2]. This finding is conceptually consistent with, though more pronounced than, improvements reported for validated clinical risk equations incorporating routine parameters alone [7,8], suggesting that biological heterogeneity not captured by filtration and albuminuria measures — particularly mineral metabolism and tubular injury pathways — contributes meaningfully to progression risk. Limitations: This single-centre study, while adequately powered for the primary comparisons, may have limited generalizability to other ethnic and healthcare settings; the 12-month follow-up, though clinically meaningful, may underestimate long-term predictive performance; and external validation of the multimarker panel in an independent cohort is required before clinical implementation.

Serum Cystatin C, FGF-23, and soluble Klotho are strongly and independently associated with CKD stage and 12-month progression in this Indian tertiary care cohort. A multimarker panel integrating these biomarkers with urinary NGAL substantially outperforms conventional eGFR- and albuminuria-based risk assessment, supporting its potential utility for early risk stratification, closer monitoring, and timely nephroprotective intervention in patients at highest risk of progression. Prospective multicentre validation is warranted before routine clinical adoption.

1. GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020;395(10225):709-733.
2. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3(1):1-150.
3. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, et al. New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med. 2021;385(19):1737-1749.
4. Isakova T, Xie H, Yang W, Xie D, Anderson AH, Scialla J, et al; Chronic Renal Insufficiency Cohort (CRIC) Study Group. Fibroblast growth factor 23 and risks of mortality and end-stage renal disease in patients with chronic kidney disease. JAMA. 2011;305(23):2432-2439.
5. Kuro-o M, Matsumura Y, Aizawa H, Kawaguchi Y, Suga T, Utsugi T, et al. Mutation of the mouse klotho gene leads to a syndrome resembling ageing. Nature. 1997;390(6655):45-51.
6. Kuro-o M. The Klotho proteins in health and disease. Nat Rev Nephrol. 2019;15(1):27-44.
7. Tangri N, Stevens LA, Griffith J, Tighiouart H, Djurdjev O, Naimark D, et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA. 2011;305(15):1553-1559.
8. Tangri N, Grams ME, Levey AS, Coresh J, Appel LJ, Astor BC, et al. Multinational assessment of accuracy of equations for predicting risk of kidney failure: a meta-analysis. JAMA. 2016;315(2):164-174.
9. Han WK, Bailly V, Abichandani R, Thadhani R, Bonventre JV. Kidney injury molecule-1 (KIM-1): a novel biomarker for human renal proximal tubular injury. Kidney Int. 2002;62(1):237-244.
10. Devarajan P. NGAL: a troponin-like biomarker for human acute kidney injury. Nephrology (Carlton). 2010;15(4):419-428.