Comparative assessment of absolute cardiovascular disease risk characterization from non-laboratory-based risk assessment in South African populations

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• 作者：Thomas A Gaziano (16) (16)
  Ankur Pandya (14)
  Krisela Steyn (15) (16)
  Naomi Levitt (15) (16)
  Willie Mollentze (16)
  Gina Joubert (14)
  Corinna M Walsh (15)
  Ayesha A Motala (16)
  Annamarie Kruger (14)
  Aletta E Schutte (15)
  Datshana P Naidoo (16)
  Dorcas R Prakaschandra (14)
  Ria Laubscher (15)
  
• 关键词：Cardiovascular disease ; Prevention ; Cholesterol ; Stroke ; Coronary heart disease
• 刊名：BMC Medicine
• 出版年：2013
• 出版时间：December 2013
• 年：2013
• 卷：11
• 期：1
• 全文大小：969KB
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• 作者单位：Thomas A Gaziano (16) (16)
  Ankur Pandya (14)
  Krisela Steyn (15) (16)
  Naomi Levitt (15) (16)
  Willie Mollentze (16)
  Gina Joubert (14)
  Corinna M Walsh (15)
  Ayesha A Motala (16)
  Annamarie Kruger (14)
  Aletta E Schutte (15)
  Datshana P Naidoo (16)
  Dorcas R Prakaschandra (14)
  Ria Laubscher (15)
  
  16. Chronic Diseases Initiative for Africa, Department of Medicine, University of Cape Town, Observatory, Cape Town, 7925, South Africa
  14. Department of Biomedical and Clinical Technology, Durban University of Technology, University of KwaZulu-Natal, Mazisi Kunene Road, Durban, 4041, South Africa
  15. Biostatistics Unit, Medical Research Council, Francie van Zijl Drive, Tygerberg, 7505, South Africa
  

文摘

Background All rigorous primary cardiovascular disease (CVD) prevention guidelines recommend absolute CVD risk scores to identify high- and low-risk patients, but laboratory testing can be impractical in low- and middle-income countries. The purpose of this study was to compare the ranking performance of a simple, non-laboratory-based risk score to laboratory-based scores in various South African populations. Methods We calculated and compared 10-year CVD (or coronary heart disease (CHD)) risk for 14,772 adults from thirteen cross-sectional South African populations (data collected from 1987 to 2009). Risk characterization performance for the non-laboratory-based score was assessed by comparing rankings of risk with six laboratory-based scores (three versions of Framingham risk, SCORE for high- and low-risk countries, and CUORE) using Spearman rank correlation and percent of population equivalently characterized as ‘high-or ‘low-risk. Total 10-year non-laboratory-based risk of CVD death was also calculated for a representative cross-section from the 1998 South African Demographic Health Survey (DHS, n = 9,379) to estimate the national burden of CVD mortality risk. Results Spearman correlation coefficients for the non-laboratory-based score with the laboratory-based scores ranged from 0.88 to 0.986. Using conventional thresholds for CVD risk (10% to 20% 10-year CVD risk), 90% to 92% of men and 94% to 97% of women were equivalently characterized as ‘high-or ‘low-risk using the non-laboratory-based and Framingham (2008) CVD risk score. These results were robust across the six risk scores evaluated and the thirteen cross-sectional datasets, with few exceptions (lower agreement between the non-laboratory-based and Framingham (1991) CHD risk scores). Approximately 18% of adults in the DHS population were characterized as ‘high CVD risk-(10-year CVD death risk >20%) using the non-laboratory-based score. Conclusions We found a high level of correlation between a simple, non-laboratory-based CVD risk score and commonly-used laboratory-based risk scores. The burden of CVD mortality risk was high for men and women in South Africa. The policy and clinical implications are that fast, low-cost screening tools can lead to similar risk assessment results compared to time- and resource-intensive approaches. Until setting-specific cohort studies can derive and validate country-specific risk scores, non-laboratory-based CVD risk assessment could be an effective and efficient primary CVD screening approach in South Africa.