Evidence mapPaperPMID 42496918Full record

ArticleLa Radiologia medica2026

Comparison of non-insulin glucose-lowering therapies on coronary atherosclerotic plaque progression in diabetes.

Ran Liu, Junyan Zhang, Zhongxiu Chen, Wenyu Huang, Wanjiang Li, Lin Shen, Yujia Cai, Yuting Lei, Minggang Zhou, Chen Li and 4 more

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Article in La Radiologia medica, 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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1 · What the graph read from it

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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

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No citing paper in PubMed yet.

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

14 authors.

Ran Liu *The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, Sichuan, China.
Junyan Zhang *Department of Cardiology, West China Hospital of Sichuan University, Chengdu, China.
Zhongxiu Chen *Department of Cardiology, West China Hospital of Sichuan University, Chengdu, China.
Wenyu HuangDepartment of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Wanjiang LiDepartment of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Lin ShenState Key Laboratory of Biotherapy, Department of Biology and Medicine, West China Hospital of Sichuan University, Chengdu, China.
Yujia CaiChinese Evidence-Based Medicine Center and MAGIC-China Center, West China Hospital Sichuan University, Chengdu, Sichuan, China.
Yuting LeiIntegrated Care Management Center, West China Hospital Sichuan University, Chengdu, China.
Minggang ZhouDepartment of Cardiology, West China Hospital of Sichuan University, Chengdu, China.
Chen LiDepartment of Cardiology, West China Hospital of Sichuan University, Chengdu, China.
Li RaoDepartment of Cardiology, West China Hospital of Sichuan University, Chengdu, China.
Hongmei YanThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, Sichuan, China.
Kaiyue DiaoDepartment of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Yong HeDepartment of Cardiology, West China Hospital of Sichuan University, Chengdu, China. heyongmd@wchscu.cn.ORCID http://orcid.org/0009-0003-6479-3636

Funding

Sichuan Province Science and Technology Support Program 2024YFFK0286the National Natural Science Foundation of China 82200553
6 · The paper itself

Abstract

purposeThe comparative effects of non-insulin glucose-lowering therapies on coronary plaque progression in type 2 diabetes (T2DM) remain unclear. This study aimed to evaluate the impact of five major classes of non-insulin therapies on the progression of coronary atherosclerosis using serial coronary computed tomography angiography (CCTA). MATERIAL AND

methodsThis was a retrospective, registry-based cohort study analyzing 880 serial CCTA scans from patients with T2DM enrolled in the TOCCATA (Tomography of Coronary Artery Plaque and Treatment) registry. Patients were stratified based on their prescribed therapy: metformin (n = 357), dipeptidyl peptidase-4 (DPP-4) inhibitors (n = 97), glucagon-like peptide-1 receptor agonists (GLP-1 RAs, n = 88), sodium-glucose cotransporter-2 inhibitors (SGLT2i, n = 258), and thiazolidinediones (TZDs, n = 80). The primary endpoints were vessel-level stenosis progression and changes in patient-level plaque scores, including the Maximum coronary stenosis score (MAXS), segment involvement score (SIS), and segment stenosis score (SSS). Multivariable Cox regression models, adjusted for relevant covariates, were used for the analysis.

resultsGLP-1 RAs were associated with the most significant reduction in vessel-level stenosis progression (adjusted Hazard Ratio [HR] 0.68, 95% Confidence Interval [CI]: 0.49-0.95, p = 0.024). This therapy class also consistently inhibited patient-level plaque progression across all scores (MAXS: HR 0.34, p = 0.002; SIS: HR 0.34, p < 0.001; SSS: HR 0.41, p < 0.001).In contrast, SGLT2i showed no significant effect on stenosis progression (HR 0.99, 95% CI: 0.82-1.19, p = 0.90) or SSS progression (HR 1.23, 95% CI: 1.00-1.52, p = 0.055). DPP-4 inhibitors showed a trend toward increased stenosis progression (HR 1.31, 95% CI: 1.01-1.69, p = 0.039). Metformin and TZDs had neutral effects on plaque progression.

conclusionIn this real-world cohort of patients with type 2 diabetes, GLP-1 receptor agonists were associated with significantly slower coronary plaque progression compared to other glucose-lowering therapies. Other therapies, including SGLT2i, demonstrated no similar protective effects. These findings suggest that GLP-1 receptor agonists may offer particular benefits for patients with advanced atherosclerosis and underscore the potential value of CCTA in informing personalized therapeutic decisions in type 2 diabetes management.

Indexed as

Coronary atherosclerotic plaque progressionCoronary Computed Tomography Angiography (CCTA)GLP-1 receptor agonists (GLP-1 RAs)Glucose-lowering therapiesType 2 Diabetes Mellitus (T2DM)

Identifiers

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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 Socratic graph.