Multiple sclerosis and related disorders · 2026
Is serum neurofilament light chain accurate enough to guide multiple sclerosis care? Diagnostic performance and optimal cutoff in a systematic review and meta-analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод в очереди
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Santana João Lucas Silva, Themoteo Rafael Martins, Allioni Gabriela Abrahão, Marzano Lucas Alexandre Santos, Bernal Henrique de Moraes, Veiga Milena Lins, Sales Alana Bacelar Limeira, Apóstolos-Pereira Samira Luisa, Adoni Tarso, Callegaro Dagoberto, Silva Guilherme Diogo
Аннотация
BACKGROUND: Serum neurofilament light chain (sNfL) has emerged as a minimally invasive biomarker reflecting neuroaxonal injury in multiple sclerosis (MS), with potential utility for detecting inflammatory disease activity. However, uncertainty persists regarding its diagnostic accuracy, reproducibility, and optimal clinical cutoff. This systematic review and meta-analysis evaluated the diagnostic performance of sNfL for MS disease activity, assessed the impact of methodological bias, and estimated an optimal cutoff for predicting clinical relapses.
METHODS: The review protocol was registered on PROSPERO (CRD420251027150). We conducted a PRISMA-compliant systematic review and meta-analysis of studies assessing sNfL in adults with MS. PubMed/MEDLINE, Embase, and Scopus were searched from inception to May 2026. Eligible studies evaluated sNfL measured by single-molecule array (Simoa™) and reported disease activity outcomes, including clinical relapse, MRI activity, or no evidence of disease activity (NEDA-3). Diagnostic accuracy was assessed through reconstruction of 2 × 2 contingency tables, hierarchical summary receiver operating characteristic (sROC) analyses, subgroup analyses, and multi-cutoff meta-analysis modeling.
RESULTS: Twenty-eight studies comprising 11,213 patients were included. Considerable heterogeneity was identified across studies regarding disease-activity definitions, analytical methods, and cutoff strategies. Fourteen studies (50%) were judged to have high risk of bias, mainly due to post hoc threshold selection. Across analyses, diagnostic performance remained modest, with pooled AUC values ranging from 0.61 to 0.71, consistently below the prespecified threshold of 0.80 considered indicative of good clinical accuracy. Similar results were observed across subgroup analyses according to outcome definition and threshold strategy. Multi-cutoff modeling identified an optimal cutoff of 10 pg/mL for predicting clinical relapse, but discriminative performance remained limited, with sensitivity of 0.69, specificity of 0.65, and AUC of 0.72.
CONCLUSION: The current literature on sNfL in MS is affected by substantial methodological heterogeneity and risk of bias. Nevertheless, even after subgroup and multi-cutoff analyses, sNfL did not achieve sufficient diagnostic accuracy for routine clinical use as a standalone biomarker of inflammatory disease activity.
METHODS: The review protocol was registered on PROSPERO (CRD420251027150). We conducted a PRISMA-compliant systematic review and meta-analysis of studies assessing sNfL in adults with MS. PubMed/MEDLINE, Embase, and Scopus were searched from inception to May 2026. Eligible studies evaluated sNfL measured by single-molecule array (Simoa™) and reported disease activity outcomes, including clinical relapse, MRI activity, or no evidence of disease activity (NEDA-3). Diagnostic accuracy was assessed through reconstruction of 2 × 2 contingency tables, hierarchical summary receiver operating characteristic (sROC) analyses, subgroup analyses, and multi-cutoff meta-analysis modeling.
RESULTS: Twenty-eight studies comprising 11,213 patients were included. Considerable heterogeneity was identified across studies regarding disease-activity definitions, analytical methods, and cutoff strategies. Fourteen studies (50%) were judged to have high risk of bias, mainly due to post hoc threshold selection. Across analyses, diagnostic performance remained modest, with pooled AUC values ranging from 0.61 to 0.71, consistently below the prespecified threshold of 0.80 considered indicative of good clinical accuracy. Similar results were observed across subgroup analyses according to outcome definition and threshold strategy. Multi-cutoff modeling identified an optimal cutoff of 10 pg/mL for predicting clinical relapse, but discriminative performance remained limited, with sensitivity of 0.69, specificity of 0.65, and AUC of 0.72.
CONCLUSION: The current literature on sNfL in MS is affected by substantial methodological heterogeneity and risk of bias. Nevertheless, even after subgroup and multi-cutoff analyses, sNfL did not achieve sufficient diagnostic accuracy for routine clinical use as a standalone biomarker of inflammatory disease activity.