A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): a pooled analysis of prospective cohorts and health examination surveys

Hajifathalian, Kaveh and Ueda, Peter and Lu, Yuan and Woodward, Mark and Ahmadvand, Alireza and Aguilar-Salinas, Carlos A. and Azizi, Fereidoun and Cifkova, Renata and Di Cesare, Mariachiara and Eriksen, Louise and Farzadfar, Farshad and Ikeda, Nayu and Khalili, Davood and Khang, Young-Ho and Lanska, Vera and León-Muñoz, Luz and Magliano, Dianna and Msyamboza, Kelias P. and Oh, Kyungwon and Rodríguez-Artalejo, Fernando and Rojas-Martinez, Rosalba and Shaw, Jonathan E. and Stevens, Gretchen A. and Tolstrup, Janne and Zhou, Bin and Salomon, Joshua A. and Ezzati, Majid and Danaei, Goodarz (2015) A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): a pooled analysis of prospective cohorts and health examination surveys. Lancet Diabetes and Endocrinology, 3 (5). pp. 339-355. ISSN 2213-8587

[img] PDF - Final accepted version (with author's formatting)
Restricted to Repository staff and depositor only

Download (1MB)

Abstract

Background Treatment of cardiovascular risk factors based on disease risk depends on valid risk prediction equations.
We aimed to develop, and apply in example countries, a risk prediction equation for cardiovascular disease (consisting here of coronary heart disease and stroke) that can be recalibrated and updated for application in different countries with routinely available information.
Methods We used data from eight prospective cohort studies to estimate coefficients of the risk equation with proportional hazard regressions. The risk prediction equation included smoking, blood pressure, diabetes, and total cholesterol, and allowed the effects of sex and age on cardiovascular disease to vary between cohorts or countries. We developed risk equations for fatal cardiovascular disease and for fatal plus non-fatal cardiovascular disease. We validated the risk equations internally and also using data from three cohorts that were not used to create the equations.
We then used the risk prediction equation and data from recent (2006 or later) national health surveys to estimate the proportion of the population at different levels of cardiovascular disease risk in 11 countries from different world regions (China, Czech Republic, Denmark, England, Iran, Japan, Malawi, Mexico, South Korea, Spain, and USA).
Findings The risk score discriminated well in internal and external validations, with C statistics generally 70% or more. At any age and risk factor level, the estimated 10 year fatal cardiovascular disease risk varied substantially between countries. The prevalence of people at high risk of fatal cardiovascular disease was lowest in South Korea, Spain, and Denmark, where only 5–10% of men and women had more than a 10% risk, and 62–77% of men and
79–82% of women had less than a 3% risk. Conversely, the proportion of people at high risk of fatal cardiovascular disease was largest in China and Mexico. In China, 33% of men and 28% of women had a 10 year risk of fatal cardiovascular disease of 10% or more, whereas in Mexico, the prevalence of this high risk was 16% for men and 11% for women. The prevalence of less than a 3% risk was 37% for men and 42% for women in China, and 55% for men and 69% for women in Mexico.
Interpretation We developed a cardiovascular disease risk equation that can be recalibrated for application in different countries with routinely available information. The estimated percentage of people at high risk of fatal cardiovascular disease was higher in low-income and middle-income countries than in high-income countries.

Item Type: Article
Additional Information: Published Online: 25 March 2015
Research Areas: A. > School of Science and Technology > Natural Sciences
Item ID: 17605
Notes on copyright: Access to full text restricted pending copyright check
Depositing User: Mariachiara Di Cesare
Date Deposited: 23 Sep 2015 11:31
Last Modified: 13 Nov 2018 21:41
URI: http://eprints.mdx.ac.uk/id/eprint/17605

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year