Basu Sanjay, Millett Christopher, Vijan Sandeep, Hayward Rodney A, Kinra Sanjay, Ahuja Rahoul, Yudkin John S
Prevention Research Center, Centers for Health Policy, Primary Care and Outcomes Research, Center on Poverty and Inequality, and Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
School of Public Health, Imperial College London, London, United Kingdom; Public Health Foundation of India, Delhi, India.
PLoS Med. 2015 May 19;12(5):e1001827; discussion e1001827. doi: 10.1371/journal.pmed.1001827. eCollection 2015 May.
Like a growing number of rapidly developing countries, India has begun to develop a system for large-scale community-based screening for diabetes. We sought to identify the implications of using alternative screening instruments to detect people with undiagnosed type 2 diabetes among diverse populations across India.
We developed and validated a microsimulation model that incorporated data from 58 studies from across the country into a nationally representative sample of Indians aged 25-65 y old. We estimated the diagnostic and health system implications of three major survey-based screening instruments and random glucometer-based screening. Of the 567 million Indians eligible for screening, depending on which of four screening approaches is utilized, between 158 and 306 million would be expected to screen as "high risk" for type 2 diabetes, and be referred for confirmatory testing. Between 26 million and 37 million of these people would be expected to meet international diagnostic criteria for diabetes, but between 126 million and 273 million would be "false positives." The ratio of false positives to true positives varied from 3.9 (when using random glucose screening) to 8.2 (when using a survey-based screening instrument) in our model. The cost per case found would be expected to be from US$5.28 (when using random glucose screening) to US$17.06 (when using a survey-based screening instrument), presenting a total cost of between US$169 and US$567 million. The major limitation of our analysis is its dependence on published cohort studies that are unlikely fully to capture the poorest and most rural areas of the country. Because these areas are thought to have the lowest diabetes prevalence, this may result in overestimation of the efficacy and health benefits of screening.
Large-scale community-based screening is anticipated to produce a large number of false-positive results, particularly if using currently available survey-based screening instruments. Resource allocators should consider the health system burden of screening and confirmatory testing when instituting large-scale community-based screening for diabetes.
与越来越多快速发展的国家一样，印度已开始建立一个大规模的基于社区的糖尿病筛查系统。我们试图确定在印度不同人群中使用替代筛查工具来检测未确诊的2型糖尿病患者的影响。
我们开发并验证了一个微观模拟模型，该模型将来自全国58项研究的数据纳入了一个具有全国代表性的25至65岁印度人样本。我们估计了三种主要的基于调查的筛查工具和基于随机血糖仪筛查的诊断及卫生系统影响。在5.67亿符合筛查条件的印度人中，根据所采用的四种筛查方法中的哪一种，预计有1.58亿至3.06亿人将被筛查为2型糖尿病“高风险”，并被转诊进行确诊检测。预计这些人中2600万至3700万人将符合糖尿病国际诊断标准，但1.26亿至2.73亿人将为“假阳性”。在我们的模型中，假阳性与真阳性的比例从3.9（使用随机血糖筛查时）到8.2（使用基于调查的筛查工具时）不等。预计每发现一例病例的成本将从5.28美元（使用随机血糖筛查时）到17.06美元（使用基于调查的筛查工具时），总成本在1.69亿至5.67亿美元之间。我们分析的主要局限性在于其依赖已发表的队列研究，而这些研究不太可能完全覆盖该国最贫困和最偏远的农村地区。由于这些地区被认为糖尿病患病率最低，这可能导致对筛查效果和健康益处的高估。
预计大规模的基于社区的筛查会产生大量假阳性结果，特别是如果使用目前可用的基于调查的筛查工具。资源分配者在开展大规模的基于社区的糖尿病筛查时应考虑筛查和确诊检测的卫生系统负担。
