Evidence map›Paper›PMID 38135837›Full record

ArticleImmunologic research2024

Serum soluble LYVE1 is a promising non-invasive biomarker of renal fibrosis: a population-based retrospective cross-sectional study.

Jing Liu, Yuqing Liu, Wenqian Zhou, Yiguo Liu, Saiya Zhu, Ying Yu, Jieli Huang, Chen Yu

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In one paragraph

Article in Immunologic research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 15% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jing Liu *Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Yuqing Liu *Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Wenqian ZhouDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Yiguo LiuDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Saiya ZhuDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Ying YuDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Jieli HuangDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China.
Chen YuDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Putuo District, Shanghai, 200092, China. yuchen@tongji.edu.cn.
Tongji Hospital · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diagnosis of renal fibrosis can only be verified by kidney biopsy, but biomarkers for non-invasive evaluation remain unsatisfactory. Patients with fibrosis often have abnormalities of the lymphatic vascular system and associated immune function. We describe here a lymphatic marker as a candidate biomarker for fibrosis. After assessing and grading the fibrosis scores, testing serum soluble lymphatic vessel endothelial hyaluronan receptor1 (sLYVE1) level, and collecting clinical information, the association between sLYVE1 and renal fibrosis was analyzed. Logistic regression analysis was used to screen variables. Diagnosis models with or without sLYVE1 were built, and nomograms were plotted. Calibration curve, C-index, and DCA were performed to assess the models. A total of 298 patients were enrolled in the study, of which 199 were included in the training cohort and 99 patients in the validation cohort. Serum sLYVE1 levels markedly elevated with increasing fibrosis grade (p<0.05). ROC analysis of sLYVE1 showed an AUC of 0.791 and 0.846 with optimal cut-off value of 405.25 ng/mL and 498.55 ng/mL for the prediction of moderate-to-severe renal fibrosis (MSF) and severe renal fibrosis (SF), respectively. The diagnostic nomogram model without sLYVE1 (model 1) included traditional clinical determinants (C-index: 0.658 for MSF; 0.603 for SF). A combination of model 1 and sLYVE1 (model 2) improved predictive performance (C-index: 0.847 for MSF; 0.856 for SF). Calibration curve and DCA demonstrated a better consistency accuracy and clinical benefit of model 2 than model 1. Serum sLYVE1 may be identified as a potential biomarker of renal fibrosis. Models incorporating sLYVE1 may be beneficial for a more accurate non-invasive diagnosis of renal fibrosis.

Indexed as

BiomarkersFibrosisKidneyVesicular Transport ProteinsAdultAgedCross-Sectional StudiesFemaleHumansKidney DiseasesMaleMiddle AgedNomogramsRetrospective StudiesROC CurveBiomarkersLYVE1 protein, humanVesicular Transport ProteinsClinical trialImmuneLymphangiogenesisLymphatic systemLYVE1Renal fibrosis

Identifiers

PMID38135837
PMCPMC11217098
OpenAlexW4390144515

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.