TY - JOUR
T1 - Precision prognostics for cardiovascular disease in Type 2 diabetes
T2 - a systematic review and meta-analysis
AU - Ahmad, Abrar
AU - Lim, Lee Ling
AU - Morieri, Mario Luca
AU - Tam, Claudia Ha ting
AU - Cheng, Feifei
AU - Chikowore, Tinashe
AU - Dudenhöffer-Pfeifer, Monika
AU - Fitipaldi, Hugo
AU - Huang, Chuiguo
AU - Kanbour, Sarah
AU - Sarkar, Sudipa
AU - Koivula, Robert Wilhelm
AU - Motala, Ayesha A.
AU - Tye, Sok Cin
AU - Yu, Gechang
AU - Zhang, Yingchai
AU - Provenzano, Michele
AU - Sherifali, Diana
AU - de Souza, Russell J.
AU - Tobias, Deirdre Kay
AU - Franks, Paul W.
AU - Rich, Stephen S.
AU - Wagner, Robert
AU - Vilsbøll, Tina
AU - Vesco, Kimberly K.
AU - Udler, Miriam S.
AU - Tuomi, Tiinamaija
AU - Sweeting, Arianne
AU - Sims, Emily K.
AU - Sherr, Jennifer L.
AU - Semple, Robert K.
AU - Reynolds, Rebecca M.
AU - Redondo, Maria J.
AU - Redman, Leanne M.
AU - Pratley, Richard E.
AU - Pop-Busui, Rodica
AU - Pollin, Toni I.
AU - Perng, Wei
AU - Pearson, Ewan R.
AU - Ozanne, Susan E.
AU - Owen, Katharine R.
AU - Oram, Richard
AU - Murphy, Rinki
AU - Mohan, Viswanathan
AU - Misra, Shivani
AU - Meigs, James B.
AU - Mathioudakis, Nestoras
AU - Mathieu, Chantal
AU - Støy, Julie
AU - Gomez, Maria F.
AU - ADA/EASD PMDI
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85198222649&partnerID=8YFLogxK
U2 - 10.1038/s43856-023-00429-z
DO - 10.1038/s43856-023-00429-z
M3 - Review
C2 - 38253823
AN - SCOPUS:85198222649
SN - 2730-664X
VL - 4
JO - Communications Medicine
JF - Communications Medicine
IS - 1
M1 - 11
ER -