| Title: |
Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis |
| Authors: |
Ahmad, A; Lim, LL; Morieri, ML; Tam, CHT; Cheng, F; Chikowore, T; Dudenhöffer-Pfeifer, M; Fitipaldi, H; Huang, C; Kanbour, S; Sarkar, S; Koivula, RW; Motala, AA; Tye, SC; Yu, G; Zhang, Y; Provenzano, M; Sherifali, D; de Souza, RJ; Tobias, DK; Franks, PW; Rich, SS; Wagner, R; Vilsbøll, T; Vesco, KK; Udler, MS; Tuomi, T; Sweeting, A; Sims, EK; Sherr, JL; Semple, RK; Reynolds, RM; Redondo, MJ; Redman, LM; Pratley, RE; Pop-Busui, R; Pollin, TI; Perng, W; Pearson, ER; Ozanne, SE; Owen, KR; Oram, R; Murphy, R; Mohan, V; Misra, S; Meigs, JB; Mathioudakis, N; Mathieu, C; Ma, RCW; Loos, RJF; Lim, SS; Laffel, LM; Kwak, SH; Josefson, JL; Hood, KK; Hivert, MF; Hirsch, IB; Hattersley, AT; Griffin, K; Greeley, SAW; Gottlieb, PA; Gloyn, AL; Florez, JC; Dennis, JM; Costacou, T; Boyle, K; Billings, LK; Brown, RJ; Philipson, LH; Nolan, JJ; Eckel, RH; Mixter, E; Mekonnen, EG; Gruber, C; Fawcett, AJ; Auh, S; Zhu, Y; Zhang, C; Saint-Martin, C; Pomares-Millan, H; Njølstad, PR; Nakabuye, M; Molnes, J; McGovern, A; Maloney, KA; Flanagan, SE; de Franco, E; Aukrust, I; Polak, M; Beltrand, J; Zhou, SJ; White, SL; Hannah, W; Wentworth, JM; Vatier, C; Van der Schueren, B; Urazbayeva, M; Ukke, GG; Taylor, R |
| Publisher Information: |
Springer Science and Business Media LLC 2024-12-01 |
| Document Type: |
Electronic Resource |
| Abstract: |
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 |
| Index Terms: |
Journal Article |
| URL: |
http://hdl.handle.net/11343/352732 |
| Availability: |
Open access content. Open access content; https://creativecommons.org/licenses/by/4.0; CC BY |
| Other Numbers: |
UMV oai:jupiter.its.unimelb.edu.au:11343/352732; Ahmad, A., Lim, L. L., Morieri, M. L., Tam, C. H. T., Cheng, F., Chikowore, T., Dudenhöffer-Pfeifer, M., Fitipaldi, H., Huang, C., Kanbour, S., Sarkar, S., Koivula, R. W., Motala, A. A., Tye, S. C., Yu, G., Zhang, Y., Provenzano, M., Sherifali, D., de Souza, R. J. ,... Taylor, R. (2024). Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis. Communications Medicine, 4 (1), pp.11-. https://doi.org/10.1038/s43856-023-00429-z.; 2730-664X; 10.1038/s43856-023-00429-z; 2730-664X; 1508024304 |
| Contributing Source: |
UNIV OF MELBOURNE; From OAIster®, provided by the OCLC Cooperative. |
| Accession Number: |
edsoai.on1508024304 |
| Database: |
OAIster |