Evidence map›Paper›PMID 39075557›Full record

ReviewBiomarker research2024

Blood and urine biomarkers of disease progression in IgA nephropathy.

Zhi-Yu Duan, Chun Zhang, Xiang-Mei Chen, Guang-Yan Cai

Abstract readReview
In one paragraph

Review in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

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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

4 authors.

Zhi-Yu DuanDepartment of Nephrology, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, First Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Chun ZhangDepartment of Nephrology, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, First Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Xiang-Mei ChenDepartment of Nephrology, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, First Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Guang-Yan CaiDepartment of Nephrology, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, First Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China. caiguangyan@sina.com.

Funding

Grant for GYC 22KJLJ001National Key Research and Development Program of China Stem Cell and Translational Research 2022YFC3602005National Natural Science Foundation of China 82170686Science and Technology Project of Beijing, China D181100000118004
6 · The paper itself

Abstract

The prognosis of patients with IgA nephropathy (IgAN) is variable but overall not good. Almost all patients with IgAN are at risk of developing end-stage renal disease within their expected lifetime. The models presently available for prediction of the risk of progression of IgAN, including the International IgA Nephropathy Prediction Tool, consist of traditional clinical, pathological, and therapeutic indicators. Finding biomarkers to improve the existing risk prediction models or replace pathological indicators is important for clinical practice. Many studies have attempted to identify biomarkers for prediction of progression of IgAN, such as galactose-deficient IgA1, complement, a spectrum of protein biomarkers, non-coding RNA, and shedding cells. This article reviews the biomarkers of progression of IgAN identified in recent years, with a focus on those with clinical value, in particular the combination of multiple biomarkers into a biomarker spectrum. Future research should focus on establishing a model based primarily on biomarkers that can predict progression of IgAN and testing it in various patient cohorts.

Indexed as

BiomarkersEnd-stage renal diseaseIgA nephropathyPredictionProgression

Identifiers

PMID39075557
PMCPMC11287988

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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.