Türe Neslişah, Emecen Ahmet Naci, Ünal Belgin
Ayvacik District Health Directorate, 17860, Ayvacik, Canakkale, Turkey.
Department of Public Health, Epidemiology Subsection, Faculty of Medicine, Dokuz Eylul University, 35340, Balcova, Izmir, Turkey.
J Prev (2022). 2024 Dec 15. doi: 10.1007/s10935-024-00819-6.
Globorisk is a country-specific risk prediction model that estimates 10-year cardiovascular disease (CVD) risk. This study aims to evaluate the agreement between different versions of Globorisk and their ability to predict CVD in a nationwide Turkish cohort. Baseline data from 5449 participants aged 40-74 were obtained from Türkiye Chronic Diseases and Risk Factors Survey 2011. Office- and laboratory-based Globorisk risk scores were calculated using age, gender, systolic blood pressure (SBP), current smoking status, body mass index (BMI), diabetes, and total cholesterol levels. Correlation and Bland-Altman analysis were employed to assess the agreement between 10-year risk scores. Multivariable logistic regression models were estimated with Globorisk variables to predict the presence of CVD over a 6-year follow-up period. Model calibration was performed. The study identified 515 incident CVD cases during the 6-year follow-up period. There was a strong positive correlation between 10-year Globorisk versions (r = 0.89). The limit of the agreement was narrower in males (- 6.11 to 6.89%) compared to females (- 7.01 to 7.73%). Age and systolic blood pressure were associated with 6-year CVD in both office- and laboratory-based models. The models showed similar discriminative performance (AUC: 0.68) and predictive accuracy (mean absolute error: 0.009) for 6-year CVD. Both Globorisk models were strongly correlated, had similar discrimination power and predictive accuracy. The office-based Globorisk can be used instead of the laboratory-based model, especially where resources are limited.
全球心血管疾病风险预测模型(Globorisk)是一种针对特定国家的风险预测模型,用于估计10年心血管疾病(CVD)风险。本研究旨在评估不同版本的Globorisk之间的一致性,以及它们在全国性土耳其队列中预测CVD的能力。2011年土耳其慢性病和危险因素调查提供了5449名年龄在40 - 74岁参与者的基线数据。基于办公室和实验室的Globorisk风险评分通过年龄、性别、收缩压(SBP)、当前吸烟状况、体重指数(BMI)、糖尿病和总胆固醇水平进行计算。采用相关性分析和布兰德-奥特曼分析来评估10年风险评分之间的一致性。使用Globorisk变量估计多变量逻辑回归模型,以预测6年随访期内心血管疾病的发生情况,并进行模型校准。该研究在6年随访期内确定了515例心血管疾病新发病例。10年Globorisk版本之间存在强正相关(r = 0.89)。与女性(-7.01%至7.73%)相比,男性的一致性界限更窄(-6.11%至6.89%)。在基于办公室和实验室的模型中,年龄和收缩压与6年心血管疾病相关。这些模型在预测6年心血管疾病方面显示出相似的判别性能(曲线下面积:0.68)和预测准确性(平均绝对误差:0.009)。两个Globorisk模型都高度相关,具有相似的判别能力和预测准确性。在资源有限的情况下,尤其可以使用基于办公室的Globorisk模型替代基于实验室的模型。