A dynamic interpretation of κFLC index for the diagnosis of multiple sclerosis: a change of perspective.
J Neurol
; 270(12): 6010-6020, 2023 Dec.
Article
em En
| MEDLINE
| ID: mdl-37639016
BACKGROUND: Previous studies attempted to define the best threshold for κ free light chains (κFLC) index, confirming higher sensitivity (Se) but less specificity (Sp) compared with IgG oligoclonal bands (OCB) for the diagnosis of MS. OBJECTIVE: To evaluate the diagnostic accuracy of different κFLC index intervals in a miscellaneous cohort of neurological patients, proposing a procedural flowchart for MS diagnosis. METHODS: We analyzed data from 607 patients diagnosed with MS (179), CIS (116), other inflammatory (94) or non-inflammatory neurological diseases (218). Measures of diagnostic accuracy were reported for different potential thresholds of κFLC index, and for IgG OCB and IgG index. Binary logistic regression was to used to calculate the odds of being diagnosed with MS based on each increase of κFLC index. RESULTS: CSF IgG OCB showed 72.2% Se (CI 95% 68.4-75.7) and 95.2% Sp (CI 95% 93.1-96.7) in discriminating between MS/CIS and controls, with an AUC of 0.84 (CI 95% 0.80-0.87). The highest diagnostic accuracy was reported for κFLC index cut-off of 5.0 (Se = 85.4%, Sp = 90.4%, AUC = 0.88), while a threshold of 11.0 exhibited higher Sp (95.5%, 95% CI 93.1-97.1) than IgG OCB. AUCs for all thresholds between 4.25 and 6.6 were not significantly different from each other, but were significantly higher than the AUC of IgG OCB (p < 0.05). The odds of being diagnosed with MS/CIS increased by 17.1% for each unit increase of κFLC index (OR = 1.17; 95% CI 1.12-1.23; p < 0.001). CONCLUSION: κFLC index performed better than CSF IgG OCB in supporting the diagnosis of MS/CIS, with the advantage of being a cost-effective and quantitative analysis.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Esclerose Múltipla
/
Doenças do Sistema Nervoso
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article