A non-invasive differential diagnostic model for light chain cast nephropathy in newly diagnosed multiple myeloma patients with renal involvement: a multicenter study
Autor: | Meng-Hua Chen, Suxia Wang, Ai-Bo Qin, Zu-Ying Xiong, Fu-De Zhou, Ming-Hui Zhao, Zi-Shan Lin, Xiao-Juan Yu, Bao Dong |
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Rok vydání: | 2021 |
Předmět: |
Nephrology
medicine.medical_specialty Kidney Receiver operating characteristic medicine.diagnostic_test business.industry 030232 urology & nephrology Acute kidney injury 030204 cardiovascular system & hematology medicine.disease Immunoglobulin light chain Gastroenterology Nephropathy 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Internal medicine Biopsy medicine business Multiple myeloma |
Zdroj: | Journal of Nephrology. |
ISSN: | 1724-6059 1121-8428 |
Popis: | 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. 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. 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) |
Databáze: | OpenAIRE |
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