Jacobs Lotte, Efremov Ljupcho, Ferreira João Pedro, Thijs Lutgarde, Yang Wen-Yi, Zhang Zhen-Yu, Latini Roberto, Masson Serge, Agabiti Nera, Sever Peter, Delles Christian, Sattar Naveed, Butler Javed, Cleland John G F, Kuznetsova Tatiana, Staessen Jan A, Zannad Faiez
Research Unit of Hypertension and Cardiovascular Epidemiology, Studies Coordinating Centre, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Belgium.
INSERM, Centre d'Investigations Cliniques Plurithe'matique 1433, INSERM U1116, CHRU de Nancy, F-CRIN INI-CRCT, Universite' de Lorraine, Nancy, France.
J Am Heart Assoc. 2017 May 2;6(5):e005231. doi: 10.1161/JAHA.116.005231.
To address the need for personalized prevention, we conducted a subject-level meta-analysis within the framework of the Heart "OMics" in AGEing (HOMAGE) study to develop a risk prediction model for heart failure (HF) based on routinely available clinical measurements.
Three studies with elderly persons (Health Aging and Body Composition [Health ABC], [PREDICTOR], and Prospective Study of Pravastatin in the Elderly at Risk [PROSPER]) were included to develop the HF risk function, while a fourth study (Anglo-Scandinavian Cardiac Outcomes Trial [ASCOT]) was used as a validation cohort. Time-to-event analysis was conducted using the Cox proportional hazard model. Incident HF was defined as HF hospitalization. The Cox regression model was evaluated for its discriminatory performance (area under the receiver operating characteristic curve) and calibration (Grønnesby-Borgan χ statistic). During a follow-up of 3.5 years, 470 of 10 236 elderly persons (mean age, 74.5 years; 51.3% women) developed HF. Higher age, BMI, systolic blood pressure, heart rate, serum creatinine, smoking, diabetes mellitus, history of coronary artery disease, and use of antihypertensive medication were associated with increased HF risk. The area under the receiver operating characteristic curve of the model was 0.71, with a good calibration (χ 7.9, =0.54). A web-based calculator was developed to allow easy calculations of the HF risk.
Simple measurements allow reliable estimation of the short-term HF risk in populations and patients. The risk model may aid in risk stratification and future HF prevention strategies.
为满足个性化预防的需求，我们在“衰老过程中心脏‘组学’”（HOMAGE）研究框架内进行了一项个体水平的荟萃分析，以基于常规可用的临床测量指标开发心力衰竭（HF）风险预测模型。
纳入三项针对老年人的研究（健康、衰老与身体成分研究[Health ABC]、[PREDICTOR]以及老年人普伐他汀前瞻性风险研究[PROSPER]）以建立HF风险函数，同时将第四项研究（盎格鲁 - 斯堪的纳维亚心脏结局试验[ASCOT]）用作验证队列。使用Cox比例风险模型进行事件发生时间分析。将HF住院定义为新发HF。对Cox回归模型的判别性能（受试者工作特征曲线下面积）和校准（Grønnesby - Borgan χ统计量）进行评估。在3.5年的随访期间，10236名老年人（平均年龄74.5岁；51.3%为女性）中有470人发生HF。年龄较大、体重指数、收缩压、心率、血清肌酐、吸烟、糖尿病、冠状动脉疾病史以及使用抗高血压药物与HF风险增加相关。该模型的受试者工作特征曲线下面积为0.71，校准良好（χ =7.9，P =0.54）。开发了一个基于网络的计算器，以便于计算HF风险。
简单的测量指标能够可靠地估计人群和患者的短期HF风险。该风险模型可能有助于风险分层和未来的HF预防策略。
