Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.
Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.
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DOI：
10.1038/s43856-023-00429-z
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发表时间：
2024-01-22
期刊：
影响因子：
--
通讯作者：
Mathioudakis, Nestoras
中科院分区：
文献类型：
--
作者：
Ahmad, Abrar;Lim, Lee-Ling;Morieri, Mario Luca;Tam, Claudia Ha-Ting;Cheng, Feifei;Chikowore, Tinashe;Dudenhoffer-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
精准医疗有可能改善2型糖尿病（T2D）患者的心血管疾病（CVD）风险预测。我们对纵向研究进行了系统回顾和荟萃分析，以确定可能改善T2D CVD风险预测的潜在新预后因素。在确定的9380项研究中，416项研究符合纳入标准。报告了321项生物标志物研究、48项遗传标志物研究和47项风险评分/模型研究的结果。在所有评估的生物标志物中，只有13个显示出预测性能的改善。汇总荟萃分析、非汇总分析以及预测性能改善和偏倚风险评估的结果显示，N末端前B型利钠肽的预测效用最高（NT-proBNP）（高证据），肌钙蛋白-T（TnT）（中度证据），葡萄糖（TyG）指数（中度证据），冠心病遗传风险评分（GRS-CHD）（中度证据）;冠状动脉计算机断层扫描血管造影的中等预测效用（低证据），单光子发射计算机断层扫描（低证据），脉搏波速度（中等证据）; C反应蛋白的预测效用低（中度证据）、冠状动脉钙评分（低证据）、半乳糖凝集素-3（低证据）、肌钙蛋白-I（低证据）、颈动脉斑块（低证据）和生长分化因子-15（低证据）。风险评分显示出适度的歧视，在与原始发展队列不同的人群中表现较低。尽管对这一主题的兴趣很高，但很少有研究进行严格的分析，以证明在T2D的既定CVD风险因素之外的增量预测效用。确定的最有希望的标志物是NT-proBNP、TnT、TyG和GRS-CHD，NT-proBNP的证据强度最高。需要进一步研究以确定其在T2D中CVD风险分层和管理中的临床效用。患有2型糖尿病（T2D）的人比没有T2D的人更容易出现心脏或血液循环问题，称为心血管疾病（CVD）。然而，很难预测哪些T2D患者最有可能患上CVD。这是因为目前的方法，如血液检查，不能识别出所有患有心血管疾病风险增加的T2D患者。在这项研究中，我们回顾了已发表的论文，这些论文调查了经历CVD的T2D患者与未经历CVD的患者之间的差异。我们发现了一些可能用于确定哪些T2D患者最有可能发展为CVD的指标。还需要更多的研究来确定这些方法有多有用。然而，它们可能被用于使临床医生能够为那些最有可能发生CVD的T2D患者提供有针对性的建议和治疗。Ahmad、Lim、Morieri、Tam等人对用于预测2型糖尿病心血管结局的生物标志物、遗传标志物和风险评分进行了系统综述和荟萃分析。确定了一些预后标志物，它们提供了超出已确定的心血管危险因素的增量预测效用。
Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). 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. 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. 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. Ahmad, Lim, Morieri, Tam et al perform a systematic review and meta-analysis of biomarkers, genetic markers, and risk scores for prediction of cardiovascular outcomes in Type 2 diabetes. A few prognostic markers are identified that provide incremental predictive utility beyond established cardiovascular risk factors.
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影响因子：
16.2
作者：
Bruno G;Landi A;Barutta F;Ghezzo G;Baldin C;Spadafora L;Schimmenti A;Prinzis T;Cavallo Perin P;Gruden G
通讯作者：
Gruden G
DOI：
10.1093/ndt/gfy154
发表时间：
2019-08-01
期刊：
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
影响因子：
--
作者：
Lim LL;Fu AWC;Lau ESH;Ozaki R;Cheung KKT;Ma RCW;Luk AOY;Chan JCN;Kong APS
通讯作者：
Kong APS
影响因子：
16.2
作者：
Araki S;Haneda M;Koya D;Sugaya T;Isshiki K;Kume S;Kashiwagi A;Uzu T;Maegawa H
通讯作者：
Maegawa H
影响因子：
16.2
作者：
Yoshida M;Mita T;Yamamoto R;Shimizu T;Ikeda F;Ohmura C;Kanazawa A;Hirose T;Kawamori R;Watada H
通讯作者：
Watada H
影响因子：
1.5
作者：
Umamahesh K;Vigneswari A;Surya Thejaswi G;Satyavani K;Viswanathan V
通讯作者：
Viswanathan V