ArticleInternational journal of general medicine2026
Prognostic Value of the HALP Score Compared with Other Inflammatory and Nutritional Indices in IgA Nephropathy.
Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: IgA nephropathy (IgAN) is the most common primary glomerulonephritis and is characterized by highly variable renal outcomes. Conventional prognostic factors, including proteinuria, hypertension, estimated glomerular filtration rate (eGFR), and the MEST-C classification, provide limited predictive accuracy. This study aimed to evaluate the prognostic value of inflammatory and nutritional indices, particularly the Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score, in patients with IgAN. Patients and methods: This retrospective cohort included 204 patients with biopsy-proven IgAN. Baseline demographic, clinical, laboratory, and histopathological data were collected. Inflammatory and nutritional indices (HALP, Systemic Immune-Inflammation Index [SII], Neutrophil-to-Lymphocyte Ratio [NLR], Platelet-to-Lymphocyte Ratio [PLR], Glasgow Prognostic Score [GPS/mGPS], and Controlling Nutritional Status [CONUT]) were calculated from routine laboratory parameters. Associations with renal outcomes, particularly progression to end-stage kidney disease (ESKD), were analyzed using Cox regression, Kaplan-Meier survival, and receiver operating characteristic (ROC) analyses. Results: During a median follow-up of 39.5 months, 17.1% of patients progressed to ESKD. Higher HALP scores were significantly associated with better renal survival, whereas other indices showed no consistent prognostic value. In multivariate analysis, HALP remained an independent predictor of renal outcome (hazard ratio = 0.13; Conclusion: The HALP score is a strong and independent prognostic biomarker in IgAN, outperforming other inflammatory and nutritional indices. Incorporating HALP into current risk-stratification models may enhance prognostic assessment and guide clinical management.
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