OBJECTIVE: To assess the prevalence of cardiovascular (CV) risk factors in Seychelles, a middle-income African country, and compare the cost-effectiveness of single-risk-factor management (treating individuals with arterial blood pressure ≥ 140/90 mmHg and/or total serum cholesterol ≥ 6.2 mmol/l) with that of management based on total CV risk (treating individuals with a total CV risk ≥ 10% or ≥ 20%). METHODS: CV risk factor prevalence and a CV risk prediction chart for Africa were used to estimate the 10-year risk of suffering a fatal or non-fatal CV event among individuals aged 40-64 years. These figures were used to compare single-risk-factor management with total risk management in terms of the number of people requiring treatment to avert one CV event and the number of events potentially averted over 10 years. Treatment for patients with high total CV risk (≥ 20%) was assumed to consist of a fixed-dose combination of several drugs (polypill). Cost analyses were limited to medication. FINDINGS: A total CV risk of ≥ 10% and ≥ 20% was found among 10.8% and 5.1% of individuals, respectively. With single-risk-factor management, 60% of adults would need to be treated and 157 cardiovascular events per 100000 population would be averted per year, as opposed to 5% of adults and 92 events with total CV risk management. Management based on high total CV risk optimizes the balance between the number requiring treatment and the number of CV events averted. CONCLUSION: Total CV risk management is much more cost-effective than single-risk-factor management. These findings are relevant for all countries, but especially for those economically and demographically similar to Seychelles.
OBJECTIVE: To assess the prevalence of cardiovascular (CV) risk factors in Seychelles, a middle-income African country, and compare the cost-effectiveness of single-risk-factor management (treating individuals with arterial blood pressure ≥ 140/90 mmHg and/or total serum cholesterol ≥ 6.2 mmol/l) with that of management based on total CV risk (treating individuals with a total CV risk ≥ 10% or ≥ 20%). METHODS: CV risk factor prevalence and a CV risk prediction chart for Africa were used to estimate the 10-year risk of suffering a fatal or non-fatal CV event among individuals aged 40-64 years. These figures were used to compare single-risk-factor management with total risk management in terms of the number of people requiring treatment to avert one CV event and the number of events potentially averted over 10 years. Treatment for patients with high total CV risk (≥ 20%) was assumed to consist of a fixed-dose combination of several drugs (polypill). Cost analyses were limited to medication. FINDINGS: A total CV risk of ≥ 10% and ≥ 20% was found among 10.8% and 5.1% of individuals, respectively. With single-risk-factor management, 60% of adults would need to be treated and 157 cardiovascular events per 100000 population would be averted per year, as opposed to 5% of adults and 92 events with total CV risk management. Management based on high total CV risk optimizes the balance between the number requiring treatment and the number of CV events averted. CONCLUSION: Total CV risk management is much more cost-effective than single-risk-factor management. These findings are relevant for all countries, but especially for those economically and demographically similar to Seychelles.
Authors: Christopher J L Murray; Jeremy A Lauer; Raymond C W Hutubessy; Louis Niessen; Niels Tomijima; Anthony Rodgers; Carlene M M Lawes; David B Evans Journal: Lancet Date: 2003-03-01 Impact factor: 79.321
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Authors: Salim Yusuf; Steven Hawken; Stephanie Ounpuu; Tony Dans; Alvaro Avezum; Fernando Lanas; Matthew McQueen; Andrzej Budaj; Prem Pais; John Varigos; Liu Lisheng Journal: Lancet Date: 2004 Sep 11-17 Impact factor: 79.321
Authors: Marshall K Tulloch-Reid; Novie O Younger; Trevor S Ferguson; Damian K Francis; Abdullahi O Abdulkadri; Georgiana M Gordon-Strachan; Shelly R McFarlane; Colette A Cunningham-Myrie; Rainford J Wilks; Simon G Anderson Journal: PLoS One Date: 2013-06-21 Impact factor: 3.240