Comparison of Nonblood-Based and Blood-Based Total CV Risk Scores in Global Populations.
BACKGROUND
Cost-effective primary prevention of cardiovascular disease (CVD) in low- and middle-income countries requires accurate risk assessment. Laboratory-based risk tools currently used in high-income countries are relatively expensive and impractical in many settings due to lack of facilities.


OBJECTIVE
This study sought to assess the correlation between a non-laboratory-based risk tool and 4 commonly used, laboratory-based risk scores in 7 countries representing nearly one-half of the world's population.


METHODS
We calculated 10-year CVD risk scores for 47,466 persons with cross-sectional data collected from 16 different cohorts in 9 countries. The performance of the non-laboratory-based risk score was compared with 4 laboratory-based risk scores: Pooled Cohort Risk Equations (ASCVD [Atherosclerotic Cardiovascular Disease]), Framingham, and SCORE (Systematic Coronary Risk Evaluation) for high- and low-risk countries. Rankings of each score were compared using Spearman rank correlations. Based on these correlations, we measured concordance between individual absolute CVD risk as measured by the Harvard NHANES (National Health and Nutrition Examination Survey) risk score, and the 4 laboratory-based risk scores, using both the conventional Framingham risk thresholds of >20% and the recent ASCVD guideline threshold of >7.5%.


RESULTS
The aggregate Spearman rank correlations between the non-laboratory-based risk score and the laboratory-based scores ranged from 0.915 to 0.979 for women and from 0.923 to 0.970 for men. When applying the conventional Framingham risk threshold of >20% over 10 years, 92.7% to 96.0% of women and 88.3% to 92.8% of men were equivalently characterized as "high" or "low" risk. Applying the recent ASCVD guidelines risk threshold of >7.5% resulted in risk characterization agreement for women ranging from 88.1% to 94.4% and from 89.0% to 93.7% for men.


CONCLUSIONS
The correlation between non-laboratory-based and laboratory-based risk scores is very high for both men and women. Potentially large numbers of high-risk individuals could be detected with relatively simple tools.
Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA; Center for Health Decision Science, Harvard T.H. Chan School of Public Boston, MA, USA. Electronic address: tgaziano@partners.org.
Thomas A
TA
Gaziano
Center for Health Decision Science, Harvard T.H. Chan School of Public Boston, MA, USA.
Shafika
S
Abrahams-Gessel
Center for Health Decision Science, Harvard T.H. Chan School of Public Boston, MA, USA.
Sartaj
S
Alam
Centre for Global Health Research, St. Michael's Hospital, Toronto, Ontario, Canada.
Dewan
D
Alam
Centre for Chronic Disease Control, Gurgaon, India.
Mohammed
M
Ali
Duke Clinical Research Institute, Durham, NC, USA.
Gerald
G
Bloomfield
CRONICAS Center of Excellence for Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
Rodrigo M
RM
Carrillo-Larco
Centre for Chronic Disease Control, Gurgaon, India; Public Health Foundation of India, Gurgaon, India.
Prabhakaran
P
Dorairaj
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina.
Laura
L
Gutierrez
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina.
Vilma
V
Irazola
Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Division of Diabetic Medicine and Endocrinology, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Naomi S
NS
Levitt
CRONICAS Center of Excellence for Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru.
J Jaime
JJ
Miranda
CRONICAS Center of Excellence for Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
Antonio
A
Bernabe-Ortiz
Center for Health Decision Science, Harvard T.H. Chan School of Public Boston, MA, USA.
Ankur
A
Pandya
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina.
Adolfo
A
Rubinstein
Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Krisela
K
Steyn
St. John's Medical College and Research Institute, St. John's National Academy of Health Sciences, Bangalore, India.
Denis
D
Xavier
The George Institute for Global Health at Peking University Health Science Center, Beijing, China; Duke Global Health Institute, Global Health Research Center, Duke Kunshan University, Kunshan, China.
Lijing L
LL
Yan
D000328:Adult; D000367:Age Factors; D000368:Aged; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology*; D002681:China; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D003362:Cost-Benefit Analysis; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000453:epidemiology*; D050171:Dyslipidemias / Q000097:blood / Q000453:epidemiology*; D005260:Female; D014943:Global Health; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000453:epidemiology*; D007194:India; D007630:Kenya; D008297:Male; D008875:Middle Aged; D010154:Pakistan; D018570:Risk Assessment / Q000379:methods*; D012737:Sex Factors; D012907:Smoking / Q000453:epidemiology*; D013019:South Africa; D013020:South America
D008076:Cholesterol, HDL; D002784:Cholesterol