ArticleKidney international2025
The Mayo MGRS Prediction Tool calculates the risk of finding monoclonal gammopathy of renal significance in a kidney biopsy in patients with monoclonal gammopathy.
Article in Kidney international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Executive summary of the European consensus report on the diagnosis and treatment of monoclonal gammopathy of renal significance.Clinical kidney journal · 2026Review
- Monoclonal gammopathy of clinical significance: a multisystem review.Blood cancer journal · 2026Review
- Microneedle Strategies for Diabetic Wound Management: A Comprehensive Review of Materials, Mechanisms, and Therapeutic Outcomes.Materials today. Advances · 2026Article
- Patient With MGRS/PGNMID Without Detection of a Peripheral Clone: Case Report and Literature Review.Case reports in hematology · 2026Article
- Current management of non-amyloidosis monoclonal gammopathy of renal significance: Clinical features, treatment selections, responses and renal outcomes.British journal of haematology · 2026Article
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Funding
Abstract
introductionMonoclonal gammopathy of renal significance (MGRS) is increasingly recognized as an important cause of kidney failure. A kidney biopsy remains an important diagnostic measure. However, a kidney biopsy is not without risks. Here, we devised the Mayo MGRS Prediction Tool to assess the probability of finding MGRS in patients with chronic kidney disease with monoclonal gammopathy (MG).
methodsWe included patients from 2013 to October 2023 who underwent a kidney biopsy at the Mayo Clinic excluding those whose hematological condition required specific treatment due to tumor burden such as multiple myeloma.
resultsOf 280 patients, 92 (32.9%) had MGRS lesions with amyloid light chain or primary amyloidosis being the most common lesion in 38 patients (41.3%). We performed multivariable logistic regression with forward variable selection to fit the model. The final model included eight predictors: diabetes, affected/unaffected free light chain ratio, urinary protein (g/24 hours), positive urine protein electrophoresis or immunofixation electrophoresis, serum creatinine, C3 level (mg/dL), hematuria, and systolic blood pressure. The calculated and optimism-corrected area under the curve was 0.896 and 0.836, respectively. The decision curve analysis showed that the model provided net benefit across all thresholds. A threshold probability of 0.10 was 98.9% sensitive and 50.5% specific, and a threshold probability of 0.25 was 88.0% sensitive and 70.2% specific. The model was validated using an external cohort of 109 patients from the University of Minnesota with good performance.
conclusionsOur Mayo MGRS Prediction Tool is useful in assisting clinicians in predicting the probability of finding an MGRS lesion in a kidney biopsy.
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