ArticleDiabetologia2018
Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.
Article in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 36 papers, 6 of them syntheses that pooled it.
What it found
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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.
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.
Observational Study on Cardiac Morphology and Function in Patients With Peripheral Artery Disease in Vastmanland County, Sweden(PADVa).
Observational Study on Peripheral Vascular Disease, Glucometabolic Status, and Type D Personality in Patients With Acute Myocardial Infarction.
Who cites it
36 citing papers in PubMed, 6 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- Overcoming Missing Data: Accurately Predicting Cardiovascular Risk in Type 2 Diabetes, A Systematic Review.Journal of diabetes · 2025Pooled it
- Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.BMC medicine · 2024Pooled it
- Evaluation of Machine Learning Methods Developed for Prediction of Diabetes Complications: A Systematic Review.Journal of diabetes science and technology · 2023Pooled it
- Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review.Cardiovascular diabetology · 2023Pooled it
- Plasma Protein Profile of Incident Myocardial Infarction, Ischemic Stroke, and Heart Failure in 2 Cohorts.Journal of the American Heart Association · 2021Pooled it
- Pooled it
- A validated, modifiable proteomic score from the EXSCEL trial predicts cardiovascular events in diabetes.JCI insight · 2026Trial
- Paediatric proteomic signatures of cardiometabolic disease-associated traits predict adult disease outcomes.Nature metabolism · 2026Article
- Beyond eGFR and Albuminuria: Biological Pathways and Multiomics in Cardiovascular-Kidney-Metabolic Disease.Kidney international reports · 2026Review
- Improved sex-specific cardiovascular risk prediction with multi-omics data in people with type 2 diabetes.Cardiovascular diabetology · 2025Article
- Plasma proteomic signatures for type 2 diabetes and related traits in the UK Biobank cohort.Diabetes research and clinical practice · 2025Article
- Omics Approach for Personalised Prevention of Type 2 Diabetes Mellitus for African and European Populations (OPTIMA): a protocol paper.BMJ open · 2025Article
- Risk prediction of ischemic heart disease using plasma proteomics, conventional risk factors and polygenic scores in Chinese and European adults.European journal of epidemiology · 2024Article
- A plasma proteomic signature for atherosclerotic cardiovascular disease risk prediction in the UK Biobank cohort.medRxiv : the preprint server for health sciences · 2024Article
- An elevated urinary albumin-to-creatinine ratio increases the risk of incident cardia-cerebrovascular disease in individuals with type 2 diabetes.Diabetology & metabolic syndrome · 2024Article
- Proteomics and lipidomics in atherosclerotic cardiovascular disease risk prediction.European heart journal · 2023Article
- Are the results from a multiplex proteomic assay and a conventional immunoassay for NT-proBNP and GDF-15 comparable?Clinical proteomics · 2023Article
- Increased serum S100A12 levels are associated with higher risk of acute heart failure in patients with type 2 diabetes.ESC heart failure · 2022Article
- Precision prognostics for the development of complications in diabetes.Diabetologia · 2022Review
- Novel Biomarkers Detected by Proteomics Predict Death and Cardiovascular Events in Hemodialysis Patients.Biomedicines · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 6 institutions in 3 countries.
Funding
Abstract
aims/hypothesisMultiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes.
methodsWe combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample.
resultsOf 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (±SD) of 6.4 ± 2.3 years. We replicated associations (<5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit α (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. CONCLUSIONS/
interpretationWe identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.
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What OpenQuestion holds
Registered trials
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.