Evidence map›Paper›PMID 31882689›Full record

Trial reportScientific reports2019

Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.

Li-Na Liao, Tsai-Chung Li, Chia-Ing Li, Chiu-Shong Liu, Wen-Yuan Lin, Chih-Hsueh Lin, Chuan-Wei Yang, Ching-Chu Chen, Chiz-Tzung Chang, Ya-Fei Yang and 4 more

Open access · goldAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 4 pooled it
2.1field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 24 citations in OpenAlex.

  1. Pooled it
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  9. Contemporary Perspectives on Chronic Renal Disorders.Chronic diseases and translational medicine · 2025
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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

14 authors at 2 institutions in 1 country.

Li-Na LiaoDepartment of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.
Tsai-Chung LiDepartment of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.ORCID http://orcid.org/0000-0002-3346-7462
Chia-Ing LiSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Chiu-Shong LiuSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Wen-Yuan LinSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.ORCID http://orcid.org/0000-0002-5220-5759
Chih-Hsueh LinSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Chuan-Wei YangDepartment of Medical Research, China Medical University Hospital, Taichung, Taiwan.
Ching-Chu ChenDivision of Endocrinology and Metabolism, Department of Medicine, China Medical University Hospital, Taichung, Taiwan.
Chiz-Tzung ChangSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Ya-Fei YangSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Yao-Lung LiuSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Huey-Liang KuoSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.
Fuu-Jen TsaiSchool of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan. d0704@mail.cmuh.org.tw.
Cheng-Chieh LinSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan. cclin@mail.cmuh.org.tw.
China Medical University · TWAsia University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated whether genetic information could offer improvement on risk prediction of diabetic nephropathy (DN) while adding susceptibility variants into a risk prediction model with conventional risk factors in Han Chinese type 2 diabetes patients. A total of 995 (including 246 DN cases) and 519 (including 179 DN cases) type 2 diabetes patients were included in derivation and validation sets, respectively. A genetic risk score (GRS) was constructed with DN susceptibility variants based on findings of our previous genome-wide association study. In derivation set, areas under the receiver operating characteristics (AUROC) curve (95% CI) for model with clinical risk factors only, model with GRS only, and model with clinical risk factors and GRS were 0.75 (0.72-0.78), 0.64 (0.60-0.68), and 0.78 (0.75-0.81), respectively. In external validation sample, AUROC for model combining conventional risk factors and GRS was 0.70 (0.65-0.74). Additionally, the net reclassification improvement was 9.98% (P = 0.001) when the GRS was added to the prediction model of a set of clinical risk factors. This prediction model enabled us to confirm the importance of GRS combined with clinical factors in predicting the risk of DN and enhanced identification of high-risk individuals for appropriate management of DN for intervention.

Indexed as

Asian PeopleDiabetes Mellitus, Type 2Diabetic NephropathiesGenetic Predisposition to DiseaseModels, GeneticAgedChinaFemaleHumansMaleMiddle AgedPredictive Value of TestsRisk Assessment

Identifiers

PMID31882689
PMCPMC6934611
OpenAlexW2998252356

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.