Evidence map›Paper›PMID 42470323›Full record

ArticleJournal of diabetes research2026

Selection and Validation of Novel Biomarkers for ntOPN-Based Models for Diabetic Kidney Disease in Patients With Diabetes Mellitus.

Lu-Xi Zou, Zhi-Li Hou, Chen-Huan Qian, Xue Wang, Ling Sun

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

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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

5 authors.

Lu-Xi ZouSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China, xzmc.edu.cn.ORCID https://orcid.org/0000-0001-9974-2642
Zhi-Li HouDepartment of Nephrology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, China, xzmc.edu.cn.ORCID https://orcid.org/0009-0008-0410-3732
Chen-Huan QianDepartment of Nephrology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, China, xzmc.edu.cn.ORCID https://orcid.org/0009-0004-7795-2365
Xue WangDepartment of Nephrology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, China, xzmc.edu.cn.ORCID https://orcid.org/0009-0005-3633-5309
Ling SunDepartment of Nephrology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, China, xzmc.edu.cn.ORCID https://orcid.org/0000-0002-5276-1309

Funding

333 High-level Personnel Cultivation Project in Jiangsu Province [2022]3-12-151Jiangsu Commission of Health Y12023008Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province 2024SJZD062Research Project of Jiangsu Provincial Commission of Health ZD2022044Science and Technology Foundation of the Xuzhou Health Committee XWKYHT20240026Science and Technology Foundation of Xuzhou City KC25078
6 · The paper itself

Abstract

introductionWe previously found that urinary n-terminal osteopontin (ntOPN) performed well for predicting diabetic kidney disease (DKD). This study is aimed at screening potential biomarkers for improving ntOPN-based models in DKD detection and prediction.

methodsWe performed a cross-sectional and then prospective cohort study. The novel biomarkers for DKD development were selected by the SOMAscan platform. The selected biomarkers were further validated by the SHapley Additive exPlanations (SHAP) algorithm, Pearson correlation, and logistic regression. The ntOPN-based models for DKD prediction were established, evaluated, and utilized by machine learning.

resultsThe baseline growth differentiation factor 15 (GDF15) was selected by SOMAscan assays, and urinary GDF15 was validated as an independent predictor for DKD occurrence (adjusted OR 1.43, 95% CI 1.20-1.75) and progression (adjusted OR 1.39, 95% CI 1.15-1.75) by multivariate logistic regression. The receiver operating characteristic (ROC) analysis showed that the multibiomarker panel consisting of urinary ntOPN-to-creatinine ratio (UntOCR) and urinary GDF15-to-creatinine ratio (UGCR) had stronger abilities in forecasting the 2-year risk of DKD occurrence (AUC 0.838 vs. 0.818) and DKD progression (AUC 0.867 vs. 0.834) than the combination of estimated glomerular filtration rate (eGFR

conclusionsCompared with eGFR

Indexed as

Diabetic NephropathiesGrowth Differentiation Factor 15OsteopontinAgedBiomarkersCreatinineCross-Sectional StudiesDisease ProgressionFemaleHumansMaleMiddle AgedProspective StudiesROC CurveBiomarkersCreatinineGDF15 protein, humanGrowth Differentiation Factor 15OsteopontinSPP1 protein, humandiabetic kidney diseasegrowth differentiation factor 15 (GDF15)nomogramn-terminal osteopontin (ntOPN)prediction model

Identifiers

PMID42470323
PMCPMC13380030

What Socratic holds

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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 Socratic graph.