ArticleClinical and experimental medicine2025
Comparison of clinical features between patients with and without renal involvement in IgG4-related disease.
Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Identification of Discriminatory Factors and Construction of a Nomogram for Differentiating IgG4-RD and DLBCL.Immunity, inflammation and disease · 2026Article
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8 authors.
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Abstract
objectiveThe kidney is one of the organs most frequently affected in immunoglobulin G4-related disease (IgG4-RD). Early identification of IgG4-RD with renal injury by clinical features is a current challenge. There is a paucity of data regarding the clinical features of renal involvement in IgG4-RD. MATERIALS: Patients with the diagnosis of IgG4-RD with and without renal injury were included in the retrospective cohort study. Cox regression analyses were used to investigate the risk factors for disease relapse and to construct the nomogram model.
resultsFrom December 2014 to February 2022, 54 patients with IgG4-RD were retrospectively enrolled. Renal involvement in IgG4-RD was observed in 55.6% of the patients. The differences of age and lacrimal gland accumulation were statistically significant (P < 0.001, and P = 0.034, respectively). Age was significantly higher in the kidney injury group. Regarding laboratory findings, basophil counts, hemoglobin levels, and serum cholinesterase level were significantly lower in patients with renal involvement (P = 0.033, P = 0.006 and P = 0.019). Erythrocyte sedimentation rate level was significantly higher in patients with renal involvement (P = 0.017). Seven (23.4%) patients in the kidney injury group relapsed during follow-up with mean recurrence time 9.86 ± 7.08 months. Early diagnosis plays a key role in patient outcomes. Female, elevated erythrocyte sedimentation rate level, and elevated complement component 4 are the risk factors for the disease relapse of IgG4-RD patients. Moreover, an effective nomogram model has been developed to predict disease relapse in patients with IgG4-RD.
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