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Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes : A Systematic Review and Meta-analysis

Ahmad, Abrar LU ; Lim, Lee-Ling ; Morieri, Mario Luca ; Tam, Claudia Ha-Ting ; Cheng, Feifei ; Chikowore, Tinashe ; Dudenhöffer-Pfeifer, Monika LU ; Fitipaldi, Hugo LU ; Huang, Chuiguo and Kanbour, Sarah , et al. (2023) p.1-73
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 could 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.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... (More)

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 could 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.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 on internal validation, with lower performance on external validation.

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: Patients with T2D are at high risk for CVD but predicting who will experience a cardiac event is challenging. Current risk tools and prognostic factors, such as laboratory tests, may not accurately predict risk in different patient populations. There is a need for personalized risk prediction tools to identify patients more accurately so that CVD prevention can be targeted to those who need it most. This study examined novel biomarkers, genetic markers, and risk scores on the prediction of CVD in individuals with T2D. We found that four laboratory markers and a genetic risk score for CHD had high predictive utility beyond traditional CVD risk factors and that risk scores had modest predictive utility when tested in diverse populations, but more studies are needed to determine their usefulness in clinical practice. The highest strength of evidence was observed for NT-proBNP, a laboratory test currently used to monitor patients with heart failure but not currently used in clinical practice for the purpose of CVD prediction in T2D.

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type
Working paper/Preprint
publication status
published
subject
pages
1 - 73
publisher
medRxiv
external identifiers
  • pmid:37162891
DOI
10.1101/2023.04.26.23289177
language
English
LU publication?
yes
id
985b8c19-52b9-40c8-b59d-753aec535012
date added to LUP
2023-06-13 13:18:03
date last changed
2023-09-01 14:47:45
@misc{985b8c19-52b9-40c8-b59d-753aec535012,
  abstract     = {{<p>BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D).</p><p>METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that could 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.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 on internal validation, with lower performance on external validation.</p><p>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.</p><p>PLAIN LANGUAGE SUMMARY: Patients with T2D are at high risk for CVD but predicting who will experience a cardiac event is challenging. Current risk tools and prognostic factors, such as laboratory tests, may not accurately predict risk in different patient populations. There is a need for personalized risk prediction tools to identify patients more accurately so that CVD prevention can be targeted to those who need it most. This study examined novel biomarkers, genetic markers, and risk scores on the prediction of CVD in individuals with T2D. We found that four laboratory markers and a genetic risk score for CHD had high predictive utility beyond traditional CVD risk factors and that risk scores had modest predictive utility when tested in diverse populations, but more studies are needed to determine their usefulness in clinical practice. The highest strength of evidence was observed for NT-proBNP, a laboratory test currently used to monitor patients with heart failure but not currently used in clinical practice for the purpose of CVD prediction in T2D.</p>}},
  author       = {{Ahmad, Abrar and Lim, Lee-Ling and Morieri, Mario Luca and Tam, Claudia Ha-Ting and Cheng, Feifei and Chikowore, Tinashe and Dudenhöffer-Pfeifer, Monika and Fitipaldi, Hugo and Huang, Chuiguo and Kanbour, Sarah and Sarkar, Sudipa and Koivula, Robert Wilhelm and Motala, Ayesha A and Tye, Sok Cin and Yu, Gechang and Zhang, Yingchai and Provenzano, Michele and Sherifali, Diana and de Souza, Russel and Tobias, Deirdre Kay and Gomez, Maria F and Ma, Ronald C W and Mathioudakis, Nestoras}},
  language     = {{eng}},
  note         = {{Preprint}},
  pages        = {{1--73}},
  publisher    = {{medRxiv}},
  title        = {{Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes : A Systematic Review and Meta-analysis}},
  url          = {{http://dx.doi.org/10.1101/2023.04.26.23289177}},
  doi          = {{10.1101/2023.04.26.23289177}},
  year         = {{2023}},
}