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Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.
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.
Afiliación
  • Ahmad A; Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
  • Lim LL; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
  • Morieri ML; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Tam CH; Asia Diabetes Foundation, Hong Kong SAR, China.
  • Cheng F; Metabolic Disease Unit, University Hospital of Padova, Padova, Italy.
  • Chikowore T; Department of Medicine, University of Padova, Padova, Italy.
  • Dudenhöffer-Pfeifer M; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Fitipaldi H; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Huang C; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Kanbour S; Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
  • Sarkar S; MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • Koivula RW; Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • Motala AA; Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
  • Tye SC; Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
  • Yu G; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Zhang Y; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Provenzano M; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Sherifali D; AMAN Hospital, Doha, Qatar.
  • de Souza RJ; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Tobias DK; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom.
  • Gomez MF; Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands.
  • Ma RCW; Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA.
  • Mathioudakis N; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
Commun Med (Lond) ; 4(1): 11, 2024 Jan 22.
Article en En | MEDLINE | ID: mdl-38253823
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 of CVD in T2D.
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 investigated the differences between people with T2D who experienced CVD compared to those who did not. We found some indicators that could potentially be used to determine which people with T2D are most likely to develop CVD. More studies are needed to determine how useful these are. However, they could potentially be used to enable clinicians to provide targeted advice and treatment to those people with T2D at most risk of developing CVD.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: Commun Med (Lond) Año: 2024 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: Commun Med (Lond) Año: 2024 Tipo del documento: Article País de afiliación: Suecia