학술논문
Improving the efficiency of free kappa light chains as diagnostic biomarker of Multiple Sclerosis by using a novel algorithm.
Document Type
Academic Journal
Author
Tortosa-Carreres J; Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Medicine Department, University of Valencia, Valencia 46010, Spain. Electronic address: jorditc95@outlook.com.; Quiroga-Varela A; Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain.; Castillo-Villalba J; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España; Medicine Department, University of Valencia, Valencia 46010, Spain.; Piqueras-Rodríguez M; Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Medicine Department, University of Valencia, Valencia 46010, Spain.; Ramió-Torrenta L; Girona Neuroimmumology and Multiple Sclerosis Unit, Neurology Department, Dr. Josep Trueta University Hospital and Santa Caterina Hospital, Girona, Spain; Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain; Medical Sciences Department, University of Girona, Girona, Spain.; Cubas-Núñez L; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España.; Gasqué-Rubio R; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España; Medicine Department, University of Valencia, Valencia 46010, Spain.; Quintanilla-Bordas C; Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España.; Huertas-Pons JM; Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain.; Miguela A; Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain.; Casanova B; Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España.; Laiz-Marro B; Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain.; Pérez-Miralles FC; Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España.
Source
Publisher: Elsevier B. V Country of Publication: Netherlands NLM ID: 101580247 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2211-0356 (Electronic) Linking ISSN: 22110348 NLM ISO Abbreviation: Mult Scler Relat Disord Subsets: MEDLINE
Subject
Language
English
Abstract
Background: Intrathecal immunoglobulin synthesis (ITS) plays a crucial role in the diagnosis of multiple sclerosis (MS). Traditionally, the gold standard method for detecting ITS has been through the analysis of oligoclonal bands (OCB). However, the paradigm has shifted with the introduction of the free kappa light chains (FKLC) method. In fact, a recent consensus recommends evaluating FKLC index (FKLCi) as the primary approach and reserving oligoclonal bands with borderline results. The objective of our study is to investigate the diagnostic efficiency of combining FKLC with other methods to predict ITS while minimizing the reliance on OCB.
Methods: A total of 192 patients were included in the study, consisting of 145 individuals diagnosed with multiple sclerosis (pwMS) and 46 with other neurological diseases (controls). Among the MS cases, 100 patients were assigned to the Training Cohort (TC), while an external Validation Cohort (VC) comprised of 45 MS patients was established. Diagnostic efficiency was assessed for FKLCi, OCB, Link index, and the Reiber formula for IgG and FKLC. Optimal cutoff values for Link index and FKLCi were also determined. The last procedure was developed for diverse algorithms using the parameters mentioned above, which included the optimal cutoffs previously obtained. The calculations were conducted independently for both the TC and the VC, as well as for a composite cohort formed by combining data from all patients (OC) RESULTS: One algorithm, named KRO, was developed based on the determination of FKLCi and Reiber Formula as the primary diagnostic parameters. For cases where the FKLCi result was mildly increased, OCB was utilized as a supplementary test. The KRO algorithm demonstrated superior diagnostic accuracy in the OC (89%), resulting in a reduction of OCB consumption by 91%.
Discussion: The KRO algorithm demonstrated superior sensitivity and accuracy although lower specificity and NPV compared to the use of FKLCi and OCB alone. The present research aligns with the new consensus recommendations regarding the diagnostic approach. Our findings indicate that employing a combined marker approach via KRO could prove to be a proficient screening tool for multiple sclerosis. This approach also holds the potential to address inherent limitations associated with each individual marker. However, to further validate and solidify the efficacy of our algorithm, additional studies involving larger cohorts are warranted.
Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest related to this research. There are no financial, personal, or professional relationships that could potentially bias or influence the interpretation of the results presented in this study.
(Copyright © 2023. Published by Elsevier B.V.)
Methods: A total of 192 patients were included in the study, consisting of 145 individuals diagnosed with multiple sclerosis (pwMS) and 46 with other neurological diseases (controls). Among the MS cases, 100 patients were assigned to the Training Cohort (TC), while an external Validation Cohort (VC) comprised of 45 MS patients was established. Diagnostic efficiency was assessed for FKLCi, OCB, Link index, and the Reiber formula for IgG and FKLC. Optimal cutoff values for Link index and FKLCi were also determined. The last procedure was developed for diverse algorithms using the parameters mentioned above, which included the optimal cutoffs previously obtained. The calculations were conducted independently for both the TC and the VC, as well as for a composite cohort formed by combining data from all patients (OC) RESULTS: One algorithm, named KRO, was developed based on the determination of FKLCi and Reiber Formula as the primary diagnostic parameters. For cases where the FKLCi result was mildly increased, OCB was utilized as a supplementary test. The KRO algorithm demonstrated superior diagnostic accuracy in the OC (89%), resulting in a reduction of OCB consumption by 91%.
Discussion: The KRO algorithm demonstrated superior sensitivity and accuracy although lower specificity and NPV compared to the use of FKLCi and OCB alone. The present research aligns with the new consensus recommendations regarding the diagnostic approach. Our findings indicate that employing a combined marker approach via KRO could prove to be a proficient screening tool for multiple sclerosis. This approach also holds the potential to address inherent limitations associated with each individual marker. However, to further validate and solidify the efficacy of our algorithm, additional studies involving larger cohorts are warranted.
Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest related to this research. There are no financial, personal, or professional relationships that could potentially bias or influence the interpretation of the results presented in this study.
(Copyright © 2023. Published by Elsevier B.V.)