Cast nephropathy (CN) is associated with a unfavorable outcome in monoclonal light chain (mLC)-disease, but also more possible LC-related renal diseases as well as not LC-related disease can occur. Thus, it is crucial to understand the underlying renal disease. On the other hand, LC can interfere with coagulation preventing kidney biopsy as the gold standard. We sought to develop a non-invasive algorithm to diagnose CN with a good sensitivity and specificity.
We analysed data from patients with mLC-disease who underwent kidney biopsy. The patients were classified in 4 groups according the renal histology: CN, AL-amyloidosis, light-chain-deposition-disease, and other renal disease. Afterwards different algorithms were calculated for their sensitivity and specificity.
CN showed a significant higher concentration of serum-free-LC and urine-LC (LCu), but there was a wide and overlapping range with the other groups. The best accuracy was achieved for a LCu/GFR-ratio>2 in patients with lambda-LC and either a LCu/GFR>1 and proteinuria5 in patients with proteinuria>8g/24h in patients with kappa-LC. In lambda-LC the sensitivity and specificity for CN was 94% and 90% respectively; in kappa-LC 87% and 81%, respectively.
In patients with coagulation disturbances due to LC a non-invasive algorithm can separate patients with CN from other renal disease in mLC disease.

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