Role of Triglyceride-Glucose Index and Inflammatory Biomarkers as Prognostic Tools for Progression of Diabetic Nephropathy

September 5, 2026 updated by: Medhat Waheed Saber Khalifa, Assiut University

Role of Triglyceride-Glucose Index and Inflammatory Biomarkers as Prognostic Tools for Progression of Diabetic Nephropathy: A Cross-Sectional Study

This study aims to evaluate the prognostic value of the Triglyceride-Glucose (TyG) index alongside inflammatory biomarkers in predicting the progression of diabetic nephropathy, exploring their correlation with disease severity to identify accessible, cost-effective markers for early risk stratification and clinical monitoring in diabetic patients.

Study Overview

Status

Not yet recruiting

Conditions

Detailed Description

Diabetic nephropathy (DN) is a major microvascular complication of diabetes and a leading cause of chronic kidney disease and end-stage renal disease worldwide . Approximately 30%-40% of people with diabetes develop DN, although prevalence varies by population and region . Clinically, DN is characterized by persistent albuminuria and progressive decline in glomerular filtration rate, and it is strongly linked to cardiovascular events, premature mortality, and major socioeconomic burden . Global burden estimates for 2021 reported 107.6 million prevalent cases, 477.3 thousand deaths, and rising disability-adjusted life years, underscoring the growing public health impact of DN .

Risk stratification in DN is essential for identifying patients at high risk of progression, guiding surveillance intensity, and enabling timely use of renoprotective therapies . Current management relies mainly on albuminuria and estimated glomerular filtration rate, alongside optimization of glycemic control, blood pressure, renin-angiotensin system blockade, SGLT2 inhibitors, GLP-1 receptor agonists, and mineralocorticoid receptor antagonists . However, these conventional markers have important limitations because albuminuria may appear after substantial renal injury, and some patients experience renal decline without marked albuminuria .

Novel biomarkers increasingly focus on metabolic and inflammatory pathways underlying diabetic nephropathy progression . The triglyceride-glucose (TyG) index has emerged as a simple surrogate of insulin resistance and has shown independent association with DN, while inflammatory markers such as TNF-related pathways and interleukin-6 also appear relevant to progression . Among inflammatory indices, NLR has shown the most consistent association with diabetic nephropathy occurrence and progression, while PLR and SII have also been linked to albuminuria, proteinuria, and renal dysfunction in several studies . Still, the evidence remains limited by cross-sectional and single-center designs, heterogeneity, inconsistent cutoffs, and modest standalone accuracy, so larger multicenter longitudinal studies are needed to validate their incremental prognostic value .

Study Type

Observational

Enrollment (Estimated)

105

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patients (≥18 years) with type 1 or type 2 diabetes mellitus, with or without diabetic nephropathy.

Description

Inclusion Criteria:

  • Adult patients (≥18 years).
  • Patients diagnosed with Type 2 or Type 1 Diabetes Mellitus.
  • Patients accepted to provide informed consent and available for clinical examination, blood sampling, and completion of required laboratory investigations (Triglyceride level, fasting glucose, inflammatory markers).

Exclusion Criteria:

  • Patients with non-diabetic causes of chronic kidney disease (e.g., glomerulonephritis, polycystic kidney disease, obstructive uropathy).
  • Patients with acute kidney injury, active urinary tract infection, or other acute inflammatory/infectious conditions that could confound inflammatory biomarker levels.
  • Patients on dialysis or with a history of renal transplantation.
  • Patients with conditions known to independently alter triglyceride/glucose levels or hematological parameters (PLR, NLR, SII) were excluded, including uncontrolled thyroid disease, active malignancy, current corticosteroid or immunosuppressive therapy, pregnancy, or severe hepatic dysfunction affecting lipid/glucose metabolism; hematological disorders such as hematological malignancies, or thrombocytopenia/thrombocytosis of nondiabetic origin; active infection, sepsis, and recent blood transfusion or use of medications affecting blood cell counts (e.g., chemotherapy, anticoagulants affecting platelet function).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Group A: patients with diabetes mellitus without diabetic nephropathy
Group B: patients with early-stage DN (Stage 1, Stage 2, and Stage 3a)
Group C: patients with advanced-stage DN (Stage 3b, Stage 4, Stage 5 not on dialysis)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Association between the Triglyceride-Glucose (TyG) index and inflammatory biomarkers (NLR, PLR, SII) with the severity/stage of diabetic nephropathy
Time Frame: Baseline
To evaluate the association between the Triglyceride-Glucose (TyG) index and inflammatory biomarkers (NLR, PLR, SII) with the severity/stage of diabetic nephropathy (based on eGFR and UACR categories, per KDIGO classification), and to determine their diagnostic/prognostic accuracy (sensitivity, specificity, AUC via ROC analysis) in identifying patients at higher risk of DN progression.
Baseline

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Assiut University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2026

Primary Completion (Estimated)

October 1, 2027

Study Completion (Estimated)

November 1, 2027

Study Registration Dates

First Submitted

September 5, 2026

First Submitted That Met QC Criteria

September 5, 2026

First Posted (Actual)

September 10, 2026

Study Record Updates

Last Update Posted (Actual)

September 10, 2026

Last Update Submitted That Met QC Criteria

September 5, 2026

Last Verified

September 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • TyG, NLR, PLR, and SII in DN

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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