Cost-effective prevention of cardiovascular disease in developing countries
Cost-effective prevention of cardiovascular disease in developing countries
批准号:
7558039
负责人:
THOMAS A GAZIANO
金额:
$12.31万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-09-01 至 2011-11-30
关键词:
AfricanAgeAreaBlood PressureBlood TestsBlood specimenCardiovascular DiseasesCardiovascular systemCaringCessation of lifeCholesterolCosts and BenefitsCox Proportional Hazards ModelsDataDatabasesDemographic and Health SurveysDeveloped CountriesDeveloping CountriesDevelopmentDiabetes MellitusEventFutureGoalsGuidelinesHealthHumanHypertensionIndiaInternationalLaboratoriesLipidsMeasuresMentored Research Scientist Development AwardModelingObesityPhysiciansPopulationPredictive ValuePrevalencePrevention strategyProcessResearchResearch PersonnelResearch ProposalsResourcesRiskRisk FactorsSamplingScreening procedureSentinel SurveillanceSouth AfricaTestingTobaccoTrainingUnited StatesWomen&aposs HealthWorkbasecardiovascular disorder preventioncardiovascular disorder riskcareercohortcostcost effectivenesshigh riskpublic health relevancetool
中文摘要
描述(由申请人提供):具有成本效益的心血管疾病预防(CVD)对于避免发展中国家的重大痛苦和死亡是必要的。本次国际研究科学家发展奖的目的是为申请人Thomas A Gaziano做好准备,使其成为发展中国家具有成本效益的心血管疾病预防方面的独立研究者。目前的国际指南评估心血管疾病的风险是基于多种危险因素,包括胆固醇和糖尿病状况。然而,血液检测的费用和缺乏获得样本的训练有素的工作人员使这些指南在发展中国家难以为继。此外,还不清楚血液采样为其他容易获得的危险因素提供了多少额外的信息。Gaziano博士提出了一项为期三年的培训和研究计划,以继续开发一种简单的无血筛查工具,用于预测心血管疾病最高风险人群,然后在两个截然不同的发展中国家评估这种策略的成本效益。研究计划包括两个具体目标。1. 评估一组容易获得的心血管疾病危险因素——年龄、吸烟、收缩压和肥胖测量(BMI)——的预测价值,并将其与更常用的使用年龄、吸烟状况、血压、血脂和糖尿病状况的模型进行比较。分析将使用cox比例风险模型与妇女健康研究和医生健康数据库进行。2. 采用以下策略对CVD筛查进行成本效益分析:不抽血筛查、抽血筛查和第三种策略,即两步过程,首先评估不抽血筛查的风险,以确定可能从高成本抽血筛查中受益的人群子集。这一分析将部分基于印度心血管疾病哨点监测研究和南非人口与健康调查的成本和风险因素流行率数据。公共卫生相关性:80%的心血管死亡发生在发展中国家。评估高危人群是一项重要的预防战略。发展中国家用于需要实验室检测的战略的资源有限。我们进行了一项研究,以确定非基于实验室的风险预测工具是否可以像需要实验室信息的工具一样发挥作用。
英文摘要
DESCRIPTION (provided by applicant): Cost-effective prevention of cardiovascular disease (CVD) is necessary to avert significant suffering and death in developing countries. The purpose of this International Research Scientist Development Award is to prepare the applicant, Thomas A Gaziano, for a career as an independent investigator in cost-effective CVD prevention in developing countries. Current international guidelines assess risk of CVD on the basis of multiple risk factors including cholesterol and diabetes status. However, the cost of blood testing and a lack of trained staff to obtain samples make these guidelines unsustainable in developing countries. Further, it is unclear how much added information blood sampling provides to other easily obtainable risk factors. Dr. Gaziano proposes a three-year training and research proposal to continue the development of a simple bloodless screening tool for predicting those at highest risk for CVD and then to assess the cost effectiveness of such a strategy in two very different developing countries. The research plan consists of two specific aims. 1. To assess the predictive value of a set of easily obtainable risk factors for CVD --age, tobacco, systolic blood pressure, and an obesity measure (BMI)~ and compare it to the more commonly used model that uses age, tobacco status, blood pressure, lipids and diabetes status. The analysis will be conducted with the Women's Health Study and Physician's Health databases using Cox-proportional hazard modeling. 2. To conduct a cost-effective analysis of screening for CVD using the following strategies: screening without blood sampling, screening with blood sampling, and a third strategy of a two step process of first assessing risk with no blood testing to identify a subset of the population who might benefit from higher cost screening with blood testing. This analysis will be based in part on cost and risk factor prevalence data in the Sentinel Surveillance for CVD in India Study and the Demographic and Health Survey in South Africa. PUBLIC HEALTH RELEVANCE: Eighty percent of cardiovascular deaths occur in developing countries. Assessing those at high risk is an important strategy for prevention. Developing countries have limited resources for strategies that require laboratory testing. We conducted a study to determine if a non laboratory-based risk prediction tool could perform as well as one requiring laboratory information.
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