title: Agreement Between Cardiovascular Disease Risk Scores in Resource-Limited Settings: Evidence from 5 Peruvian Sites.
abstract: It is unclear how well currently available risk scores predict cardiovascular disease (CVD) risk in low-income and middle-income countries. We aim to compare the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations (ACC/AHA model) with 6 other CVD risk tools to assess the concordance of predicted CVD risk in a random sample from 5 geographically diverse Peruvian populations. We used data from 2 Peruvian, age and sex-matched, population-based studies across 5 geographical sites. The ACC/AHA model were compared with 6 other CVD risk prediction tools: laboratory Framingham risk score for CVD, non-laboratory Framingham risk score for CVD, Reynolds risk score, systematic coronary risk evaluation, World Health Organization risk charts, and the Lancet chronic diseases risk charts. Main outcome was in agreement with predicted CVD risk using Lin's concordance correlation coefficient. Two thousand one hundred and eighty-three subjects, mean age 54.3 (SD ± 5.6) years, were included in the analysis. Overall, we found poor agreement between different scores when compared with ACC/AHA model. When each of the risk scores was used with cut-offs specified in guidelines, ACC/AHA model depicted the highest proportion of people at high CVD risk predicted at 10 years, with a prevalence of 29.0% (95% confidence interval, 26.9-31.0%), whereas prevalence with World Health Organization risk charts was 0.6% (95% confidence interval, 0.2-8.6%). In conclusion, poor concordance between current CVD risk scores demonstrates the uncertainty of choosing any of them for public health and clinical interventions in Latin American populations. There is a need to improve the evidence base of risk scores for CVD in low-income and middle-income countries.
authors.affiliation: From the *CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; †Santa Cruz de Ratacocha Primary Healthcare Centre, Social Service in Rural Setting, Ministry of Health, Huanuco, Peru; ‡Division of Cardiology, Department of Medicine, §Duke Clinical Research Institute, ¶Duke Global Health Institute, Duke University, Durham, NC; ‖School of Medicine, University College London, London, UK; **Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; ††Asociación Benéfica PRISMA, Lima, Peru; ‡‡Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD; §§Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru; and ¶¶Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
authors.forename: Juan Carlos
authors.initials: JC
authors.lastname: Bazo-Alvarez
authors.forename: Renato
authors.initials: R
authors.lastname: Quispe
authors.forename: Frank
authors.initials: F
authors.lastname: Peralta
authors.forename: Julio A
authors.initials: JA
authors.lastname: Poterico
authors.forename: Giancarlo A
authors.initials: GA
authors.lastname: Valle
authors.forename: Melissa
authors.initials: M
authors.lastname: Burroughs
authors.forename: Timesh
authors.initials: T
authors.lastname: Pillay
authors.forename: Robert H
authors.initials: RH
authors.lastname: Gilman
authors.forename: William
authors.initials: W
authors.lastname: Checkley
authors.forename: Germán
authors.initials: G
authors.lastname: Malaga
authors.forename: Liam
authors.initials: L
authors.lastname: Smeeth
authors.forename: Antonio
authors.initials: A
authors.lastname: Bernabé-Ortiz
authors.forename: J Jaime
authors.initials: JJ
authors.lastname: Miranda
mesh_terms: D000368:Aged; D000572:American Heart Association; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D005260:Female; D006295:Health Resources / Q000600:supply & distribution; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010568:Peru / Q000453:epidemiology; D015995:Prevalence; D018570:Risk Assessment; D012424:Rural Population; D014481:United States; D014505:Urban Population