A non-invasive differential diagnostic model for light chain cast nephropathy in newly diagnosed multiple myeloma patients with renal involvement: a multicenter study

Abstract

Objective Light chain cast nephropathy is the most common form of renal lesion in multiple myeloma. Kidney impairment caused by light chain cast nephropathy can be reversed and survival can be improved if early diagnosis is available. It is thus of imperative importance to develop a non-invasive method to diagnose light chain cast nephropathy once the kidney biopsy is not always applicable. Methods We consecutively screened newly diagnosed multiple myeloma patients with kidney biopsies from 4 centers in China. Kidney pathologies were reviewed and clinical presentations were recorded. Then a diagnostic model was established by logistic regression and the predictive values were assessed. Results Between 1 June 1999 and 30 June 2019, a kidney biopsy was performed in 94 patients with newly diagnosed multiple myeloma, and light chain cast nephropathy was the most common pattern, seen in 52% of biopsied patients. The diagnostic model was established by multivariate logistic regression analysis as P(z) = 1/(1 + e(-z)) and z = - 0.093 Hemoglobin (g/L) + 0.421 Serum albumin (g/L) + 3.463 Acute kidney injury (0/1) - 9.207 High-density lipoprotein (mmol/L). If P(z) >= 0.55, the diagnosis pointed to light chain cast nephropathy; if P(z) < 0.55, the diagnosis favored non-light chain cast nephropathy. The area under the receiver operating characteristic curves was 0.981 (95% CI 0.959, 1.000). The model had a sensitivity of 93.9%, a specificity of 95.6%, a positive predictive value of 96.0%, a negative predictive value of 94.0%, and a total consistency of 95.0%. Conclusion We built a novel, non-invasive diagnostic model through a multicenter study, which may be helpful in the diagnosis of light chain cast nephropathy in newly diagnosed multiple myeloma patients. Graphic abstract