Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

• Published in: Communications medicine 2024-01, Vol.4 (1), p.11-28, Article 11
• Main Authors: Ahmad, Abrar, Lim, Lee-Ling, Morieri, Mario Luca, Tam, Claudia Ha-ting, Cheng, Feifei, Chikowore, Tinashe, Dudenhöffer-Pfeifer, Monika, Fitipaldi, Hugo, Huang, Chuiguo, Kanbour, Sarah, Sarkar, Sudipa, Koivula, Robert Wilhelm, Motala, Ayesha A., Tye, Sok Cin, Yu, Gechang, Zhang, Yingchai, Provenzano, Michele, Sherifali, Diana, de Souza, Russell J., Tobias, Deirdre Kay, Gomez, Maria F., Ma, Ronald C. W., Mathioudakis, Nestoras
• Format: Article
• Language: English
• Subjects: 692/163/2743/137/138; 692/53/2422; Algorithms; Biomarkers; Cardiac and Cardiovascular Systems; Cardiovascular disease; Clinical Medicine; Diabetes; Endocrinology and Diabetes; Endokrinologi och diabetes; Health risk assessment; Kardiologi; Klinisk medicin; Medical and Health Sciences; Medical prognosis; Medicin och hälsovetenskap; Medicine; Medicine & Public Health; Meta-analysis; Precision medicine; Risk factors; Sociodemographics; Systematic review
• ISSN: 2730-664X; 2730-664X
• DOI: 10.1038/s43856-023-00429-z

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D. Plain language summary People living with type 2 diabetes (T2D) are more likely to develop problems with their heart or blood circulation, known as cardiovascular disease (CVD), than people who do not have T2D. However, it can be difficult to predict which people with T2D are most likely to develop CVD. This is because current approaches, such as blood tests, do not identify all people with T2D who are at an increased risk of CVD. In this study we reviewed published papers that invest