Ruwanpathirana Thilanga, Owen Alice, Reid Christopher M
CCRE Therapeutics, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Vic., Australia.
Cardiovasc Ther. 2015 Apr;33(2):62-70. doi: 10.1111/1755-5922.12110.
The objectives were to review the currently available and widely used cardiovascular risk assessment models and to examine the evidence available on new biomarkers and the nonclinical measures in improving the risk prediction in the population level. Identification of individuals at risk of cardiovascular disease (CVD), to better target prevention and treatment, has become a top research priority. Cardiovascular risk prediction has progressed with the development and refinement of risk prediction models based upon established clinical factors, and the discovery of novel biomarkers, lifestyle, and social factors may offer additional information on the risk of disease. However, a significant proportion of individuals who have a myocardial infarction still are categorized as low risk by many of the available methods. Although novel biomarkers can improve risk prediction, including B-type natriuretic peptides which have shown the best predictive capacity per unit cost, there is concern that the use of risk prediction strategies which rely upon new/or expensive biomarkers could further broaden social inequalities in CVD. In contrast, nonclinical factors such as work stress, social isolation, and early childhood experience also appear to be associated with cardiovascular risk and have the potential to be utilized for the baseline risk stratification at the population level. A stepwise approach of nonclinical methods followed by risk scores consisting of clinical risk factors may offer a better option for initial and subsequent screening, preserving more specialized approaches including novel biomarkers for enhanced risk stratification at population level in a cost-effective manner.
目标是回顾当前可用且广泛使用的心血管风险评估模型，并审视关于新生物标志物和非临床测量方法在改善人群水平风险预测方面的现有证据。识别有心血管疾病（CVD）风险的个体，以便更好地确定预防和治疗目标，已成为首要研究重点。随着基于既定临床因素的风险预测模型的发展和完善，心血管风险预测取得了进展，而新生物标志物、生活方式和社会因素的发现可能会提供有关疾病风险的更多信息。然而，许多现有方法仍将很大一部分心肌梗死患者归类为低风险。尽管新生物标志物可以改善风险预测，包括B型利钠肽，其已显示出每单位成本最佳的预测能力，但人们担心依赖新的/或昂贵生物标志物的风险预测策略的使用可能会进一步扩大CVD方面的社会不平等。相比之下，工作压力、社会孤立和童年早期经历等非临床因素似乎也与心血管风险相关，并且有可能用于人群水平的基线风险分层。采用非临床方法，随后结合由临床风险因素组成的风险评分的逐步方法，可能为初始和后续筛查提供更好的选择，以具有成本效益的方式保留包括新生物标志物在内的更专业方法，用于在人群水平进行强化风险分层。
