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Article Abstract

Introduction: Monoclonal 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).

Methods: We 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.

Results: Of 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.

Conclusions: Our 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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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12225640PMC
http://dx.doi.org/10.1016/j.kint.2025.04.018DOI Listing

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