Evidence mapPaperPMID 41489455Full record

ArticleJournal of molecular cell biology2026

A protein-based prediction model for fragility fracture risk in individuals with diabetes.

Suna Wang, Li Shen, Weituo Zhang, Jingyi Guo, Wei Chen, Xiangtian Yu, Cheng Hu

Abstract read
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Article in Journal of molecular cell biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Suna WangClinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
Li ShenClinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
Weituo ZhangClinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Jingyi GuoClinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
Wei ChenClinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
Xiangtian YuClinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.
Cheng HuShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China.

Funding

Fundamental Research Funds for the Central Universities YG2023QNB20National Key Research and Development Program of China 2022YFA1004800National Key Research and Development Program of China 2022YFF1202100National Science and Technology Major Project 2024ZD0532200
6 · The paper itself

Abstract

Individuals with diabetes are at high risk of fragility fractures. We aimed to develop and validate a protein-based model to predict fragility fractures in individuals with diabetes and to explore whether a protein risk score (ProRS) would improve the risk prediction. A total of 3535 individuals with diabetes from the UK Biobank Pharma Proteomics Project were included in the study. During a median follow-up period of 13.3 years, 5.2% (185) of the individuals with diabetes experienced a fragility fracture. Of 2902 unique proteins, 139 exhibited significant associations with fragility fracture risk. A protein-based model that included 10 proteins was then developed using the machine learning model. Compared with the low ProRS tertile, medium and high tertiles were strongly associated with increased fragility fracture risk. The ProRS achieved a C-index of 0.739 and a 10-year area under the curve (AUC) of 0.733 for the fragility fracture prediction. Adding ProRS to the traditional prediction model (the fracture risk assessment tool [FRAX]) improved the prediction performance with a C-index increase of 0.080 (0.673 [FRAX] vs. 0.754 [FRAX+ProRS]) and a 10-year AUC increase of 0.064 (0.693 vs. 0.757), thereby promoting early monitoring and prevention in individuals with diabetes.

Indexed as

Diabetes MellitusFractures, BoneOsteoporotic FracturesProteinsAgedFemaleHumansMalePrediction AlgorithmsPredictive Learning ModelsProteomicsRisk AssessmentRisk FactorsProteinsdiabetesfragility fracturesprediction modelproteomics

Identifiers

PMID41489455
PMCPMC13395793

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.