Assessing the value of screening tools: reviewing the challenges and opportunities of cost-effectiveness analysis.
Assessing the value of screening tools: reviewing the challenges and opportunities of cost-effectiveness analysis.
复制标题
DOI：
10.1186/s40985-018-0093-8
复制
发表时间：
2018
影响因子：
5.5
通讯作者：
Spackman E
中科院分区：
文献类型：
--
作者：
Iragorri N;Spackman E
筛查是预防医学的重要组成部分。理想情况下，筛查工具尽早发现患者，以便提供治疗并避免或减轻症状和其他后果，以合理的成本改善人群的健康结果。成本效益分析结合了干预措施的预期效益和成本，可用于评估筛查工具的价值。本次审查旨在评估筛选工具的最新成本效益分析，以确定当前遇到的挑战以及克服这些挑战的潜在方法。对 EMBASE 和 MEDLINE 的系统文献检索确定了 2017 年发表的筛查工具的成本效益分析。提取的数据包括人口、疾病、筛查工具、比较器、视角、时间范围、折扣和结果。对挑战和方法建议进行了叙述性综合。确定了四个关键类别：筛查途径、症状前疾病、治疗结果和非健康益处。并非所有研究都包括治疗结果； 15 项研究 (22%) 不包括诊断后的治疗。 35 人 (51.4%) 使用质量调整生命年作为主要结果。从社会角度进行的研究并未一致地报告非健康效益和成本。确定的两个重要挑战是（i）估计停留时间，即可以通过筛查测试识别患者与因症状而识别患者之间的时间，以及（ii）估计早期识别的患者的治疗效果和进展率。为了捕获筛查工具的所有重要成本和结果，应对筛查途径进行建模，包括患者治疗。此外，假阳性和假阴性患者可能会产生重大成本和后果，应纳入分析中。由于这些患者很难在常规数据源中识别，因此应使用常见的治疗模式来确定这些患者可能接受的治疗方式。重要的是，要清楚地表明假设，并在敏感性分析中测试这些假设的后果，特别是连续测试的独立性假设以及患者和提供者对指南和停留时间的遵守程度。由于很少有关于未确诊患者病情进展的数据，因此可能有必要根据确诊患者进行推断。
Screening is an important part of preventive medicine. Ideally, screening tools identify patients early enough to provide treatment and avoid or reduce symptoms and other consequences, improving health outcomes of the population at a reasonable cost. Cost-effectiveness analyses combine the expected benefits and costs of interventions and can be used to assess the value of screening tools. This review seeks to evaluate the latest cost-effectiveness analyses on screening tools to identify the current challenges encountered and potential methods to overcome them. A systematic literature search of EMBASE and MEDLINE identified cost-effectiveness analyses of screening tools published in 2017. Data extracted included the population, disease, screening tools, comparators, perspective, time horizon, discounting, and outcomes. Challenges and methodological suggestions were narratively synthesized. Four key categories were identified: screening pathways, pre-symptomatic disease, treatment outcomes, and non-health benefits. Not all studies included treatment outcomes; 15 studies (22%) did not include treatment following diagnosis. Quality-adjusted life years were used by 35 (51.4%) as the main outcome. Studies that undertook a societal perspective did not report non-health benefits and costs consistently. Two important challenges identified were (i) estimating the sojourn time, i.e., the time between when a patient can be identified by screening tests and when they would have been identified due to symptoms, and (ii) estimating the treatment effect and progression rates of patients identified early. To capture all important costs and outcomes of a screening tool, screening pathways should be modeled including patient treatment. Also, false positive and false negative patients are likely to have important costs and consequences and should be included in the analysis. As these patients are difficult to identify in regular data sources, common treatment patterns should be used to determine how these patients are likely to be treated. It is important that assumptions are clearly indicated and that the consequences of these assumptions are tested in sensitivity analyses, particularly the assumptions of independence of consecutive tests and the level of patient and provider compliance to guidelines and sojourn times. As data is rarely available regarding the progression of undiagnosed patients, extrapolation from diagnosed patients may be necessary.