Multi‐marker algorithms based on CXCL13, IL‐10, sIL‐2 receptor, and β2‐microglobulin in cerebrospinal fluid to diagnose CNS lymphoma
Year: 2020
Type: article
Study design: Observational Study
Abstract: Tumor biopsy is essential for the definitive diagnosis of central nervous system (CNS) lymphoma. However, the biopsy procedure carries the risk of complications such as bleeding, convulsions, and infection. Cerebrospinal fluid (CSF) β2-microglobulin (β2-MG), soluble IL-2 receptor (sIL-2R), and interleukin-10 (IL-10) are known to be useful diagnostic biomarkers for CNS lymphoma. The C-X-C motif chemokine ligand 13 (CXCL13) was recently reported to be another useful biomarker for CNS lymphoma. The purpose of this study is to establish a diagnostic algorithm that can avoid biopsy by combining these diagnostic biomarkers. In the first, we conducted a case-control study (n = 248) demonstrating that the CSF CXCL13 concentration was significantly increased in CNS lymphoma patients compared with various other brain diseases (AUC = 0.981). We established a multi-marker diagnostic model using CSF CXCL13, IL-10, β2-MG, and sIL-2R from the results of the case-control study and then applied the model to a prospective study (n = 104) to evaluate its utility. The multi-marker diagnostic algorithms had excellent diagnostic performance: the sensitivity, specificity, positive predictive value, and negative predictive value were 97%, 97%, 94%, and 99%, respectively. In addition, CSF CXCL13 was a prognostic biomarker for CNS lymphoma patients. Our study suggests that multi-marker algorithms are important diagnostic tools for patients with CNS lymphoma.
Source: Cancer Medicine
DOI: 10.1002/cam4.3048
Authors: Masahiro Maeyama, Takashi Sasayama, Kazuhiro Tanaka, Satoshi Nakamizo, Hirotomo Tanaka, Masamitsu Nishihara, Yuichi Fujita, Kenji Sekiguchi, Masaaki Kohta, Katsu Mizukawa, Takanori Hirose, Tomoo Itoh, Eiji Kohmura
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,750
Awards: G1666209173, Basic research of ketogenic diet therapy with inhibitor of aminno acid metabolism for glioblastoma, Approaches to establish the algorithm for the pathologic diagnosis of lipogenic mesenchymal tumors, Analysis of dissemination factor of glioma cells, New integrated therapy for glioblastoma considering intratumoral metabolic remodeling with a ketogenic diet, G728724459, Basic research on new glioblastoma treatment by tumor-related macrophage immune checkpoint inhibition
OpenAlex ID: W3016932049
