Evidence map›Paper›PMID 30214214›Full record

ReviewNeuropsychiatric disease and treatment2018

Neurofilament light chain as a biological marker for multiple sclerosis: a meta-analysis study.

Laisheng Cai, Jingwei Huang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Neuropsychiatric disease and treatment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Laisheng CaiDepartment of Neurology, The First Affiliated Hospital of Nanchang University, Jiangxi, People's Republic of China, huangjw67@sohu.com.
Jingwei HuangDepartment of Neurology, The First Affiliated Hospital of Nanchang University, Jiangxi, People's Republic of China, huangjw67@sohu.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThere is a need for biomarkers in multiple sclerosis (MS) to make an early diagnosis and monitor its progression. This study was designed to evaluate the value of neurofilament light (NFL) chain levels as cerebrospinal fluid (CSF) or blood biomarker in patients with MS by using a quantitative meta-analysis.

methodsThe PubMed, Embase, and Web of Science databases were systematically searched for relevant studies. Articles in English that evaluated the utility of NFL in CSF and blood in the diagnosis of MS were included. Data were extracted by two independent researchers. Mean (± SD) NFL concentration for MS patients and control subjects were extracted. Review Manager version 5.3 software with a continuous-variable random-effects model was used to summarize the diagnostic indexes from eligible studies. The Newcastle-Ottawa Scale was used for assessing the quality and risk of bias of included studies. In addition, subgroup analysis and meta-regression were performed to assess potential heterogeneity sources.

resultsThe meta-analysis included 13 articles containing results from 15 studies. A total of 10 studies measured NFL levels in CSF and five studies measured NFL levels in blood. Data were available on 795 participants in CSF and 1,856 participants in blood. Moreover, CSF NFL in MS patients was higher than that in healthy control groups (pooled standard mean difference [Std.MD]=0.88, 95% CI [0.50, 1.26],

conclusionNFL chain has significantly increased in MS patients, which substantially strengthens the clinical evidence of the NFL in MS. The NFL may be used as a prognostic biomarker to monitor disease progression, disease activity, and treatment efficacy in the future.

Indexed as

meta-analysismultiple sclerosisneurofilament light chain

Identifiers

PMID30214214
PMCPMC6126505

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.