Background: Neurosarcoidosis is an inflammatory granulomatous disease. Up to 25% of occult sarcoidosis affecting the nervous system are only detected by autopsy. In addition, in recent years the suspicion arose that the soluble Interleukin-2 Receptor (sIL-2R) might be useful in differentiating between neurosarcoidosis and neurosarcoidosis-like diseases such as neurotuberculosis, multiple sclerosis, or cerebral lymphoma.
Objectives: Therefore, we aimed to systematically review randomized controlled trials (RCT), observational studies, and case-control studies evaluating sIL-2R levels in neurosarcoidosis patients.
Design: For this systematic review, a comprehensive literature search of electronic databases including EMBASE, The Web Of Science, The Cochrane Library, MEDLINE, and Google Scholar was conducted. The search was limited to the English language and publication date up to January 08 2024.
Data Sources And Methods: As part of the search strategy conducted, 6 articles met the inclusion criteria. Two independent reviewers extracted the relevant data from each article. In addition, 2 independent reviewers assessed the quality of each study using the Newcastle-Ottawa Scale (NOS).
Results: We included 6 studies comprising 98 patients suffering from neurosarcoidosis, 525 non-sarcoidosis patients, and 118 healthy controls. Included studies were published between 2010 and 2023. Cerebrospinal fluid (CSF) sIL-2R levels differed significantly between neurosarcoidosis patients and multiple sclerosis, vasculitis, and healthy controls whereas serum sIL-2R levels did not reveal sufficient discriminative power. sIL-2R index was able to discriminate neurosarcoidosis from neurotuberculosis, bacterial/viral meningitis, and healthy controls.
Conclusions: In this systematic review, we found indications that sIL-2R may be a useful biomarker for the diagnosis of neurosarcoidosis. To determine an additional diagnostic value of sIL-2R, large prospective studies are needed that not only examine absolute sIL-2R levels in serum or CSF but also the dynamic changes as well as the implications of renal function on sIL-2R levels.
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http://dx.doi.org/10.1177/11795735241274186 | DOI Listing |
BMC Med Inform Decis Mak
November 2024
Clinical Medical Center of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Background: Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients.
Methods: Laboratory indices of the NSCLC patients at their initial visit were collected for quality control and exploratory analysis.
J Orthop
April 2025
Department of Orthopaedic Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi-Ku, Tokyo 173-8606, Japan.
Zhongguo Dang Dai Er Ke Za Zhi
October 2024
Institute of Pediatrics, Seventh Medical Centre, General Hospital of the Chinese People's Liberation Army, Beijing 100010, China.
Ann Hematol
December 2024
Department of Hematology and Oncology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
Despite an emphasis on the prognostic impact of serum soluble interleukin-2 receptor (sIL-2R) at diagnosis in patients with diffuse large B-cell lymphoma (DLBCL), whether the prognostic impact of elevated sIL-2R is linear remains unclear. To verify the presence of a non-linear association between sIL-2R level at diagnosis and overall survival (OS) in patients with newly diagnosed DLBCL, we conducted a multi-center, observational retrospective study. Among 488 analyzable patients, Cox proportional hazards modeling identified serum sIL-2R level at diagnosis as an independent predictor of OS.
View Article and Find Full Text PDFAnn Clin Biochem
November 2024
Advanced Diagnostic System Development, Fujita Health University Graduate School of Health Sciences, Toyoake, Japan.
Objectives: Reports have shown that the kynurenine pathway, one of the pathways by which tryptophan is metabolized, is activated in patients with diffuse large B-cell lymphoma (DLBCL). Activation of the kynurenine pathway triggers the production of various metabolites, such as kynurenine (Kyn), 3-hydroxykynurenine (3-HK), 3-hydroxyanthranilic acid (3-HAA), kynurenic acid (KA), and anthranilic acid (AA), which contribute to immune tolerance. The current study aimed to investigate the changes in metabolites of kynurenine pathway in DLBCL patients and evaluate their performance predicting DLBCL.
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