Economic Evaluation of Medical Screening

E. Aas, E. Burger, K. Pedersen
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Abstract

The objective of medical screening is to prevent future disease (secondary prevention) or to improve prognosis by detecting the disease at an earlier stage (early detection). This involves examination of individuals with no symptoms of disease. Introducing a screening program is resource demanding, therefore stakeholders emphasize the need for comprehensive evaluation, where costs and health outcomes are reasonably balanced, prior to population-based implementation. Economic evaluation of population-based screening programs involves quantifying health benefits (e.g., life-years gained) and monetary costs of all relevant screening strategies. The alternative strategies can vary by starting- and stopping-age, frequency of the screening and follow-up regimens after a positive test result. Following evaluation of all strategies, the efficiency frontier displays the efficient strategies and the country-specific cost-effectiveness threshold is used to determine the optimal, i.e., most cost-effective, screening strategy. Similar to other preventive interventions, the costs of screening are immediate, while the health benefits accumulate after several years. Hence, the effect of discounting can be substantial when estimating the net present value (NPV) of each strategy. Reporting both discounting and undiscounted results is recommended. In addition, intermediate outcome measures, such as number of positive tests, cases detected, and events prevented, can be valuable supplemental outcomes to report. Estimating the cost-effectiveness of alternative screening strategies is often based on decision-analytic models, synthesizing evidence from clinical trials, literature, guidelines, and registries. Decision-analytic modeling can include evidence from trials with intermediate or surrogate endpoints and extrapolate to long-term endpoints, such as incidence and mortality, by means of sophisticated calibration methods. Furthermore, decision-analytic models are unique, as a large number of screening alternatives can be evaluated simultaneously, which is not feasible in a randomized controlled trial (RCT). Still, evaluation of screening based on RCT data are valuable as both costs and health benefits are measured for the same individual, enabling more advanced analysis of the interaction of costs and health benefits. Evaluation of screening involves multiple stakeholders and other considerations besides cost-effectiveness, such as distributional concerns, severity of the disease, and capacity influence decision-making. Analysis of harm-benefit trade-offs is a useful tool to supplement cost-effectiveness analyses. Decision-analytic models are often based on 100% participation, which is rarely the case in practice. If those participating are different from those not choosing to participate, with regard to, for instance, risk of the disease or condition, this would result in selection bias, and the result in practice could deviate from the results based on 100% participation. The development of new diagnostics or preventive interventions requires re-evaluation of the cost-effectiveness of screening. For example, if treatment of a disease becomes more efficient, screening becomes less cost-effective. Similarly, the introduction of vaccines (e.g., HPV-vaccination for cervical cancer) may influence the cost-effectiveness of screening. With access to individual level data from registries, there is an opportunity to better represent heterogeneity and long-term consequences of screening on health behavior in the analysis.
医学筛查的经济评价
医学筛查的目的是预防未来的疾病(二级预防)或通过在早期发现疾病(早期发现)来改善预后。这包括对没有疾病症状的个体进行检查。实施筛查规划需要大量资源,因此利益攸关方强调,在基于人群的实施之前,需要进行全面评估,在成本和健康结果之间取得合理平衡。以人群为基础的筛查项目的经济评估包括量化所有相关筛查策略的健康效益(例如,获得的寿命年)和货币成本。备选策略可根据开始和停止年龄、筛查频率和阳性检测结果后的随访方案而有所不同。在对所有策略进行评估后,效率边界显示了有效的策略,而具体国家的成本效益阈值用于确定最优,即最具成本效益的筛查策略。与其他预防性干预措施类似,筛查的成本是立竿见影的,而健康益处是在几年后积累起来的。因此,在估计每种策略的净现值(NPV)时,贴现的影响可能是实质性的。建议报告贴现和未贴现结果。此外,中间结果指标,如阳性检测数、发现病例数和预防事件数,可作为有价值的补充结果报告。评估替代筛查策略的成本效益通常基于决策分析模型,综合临床试验、文献、指南和登记的证据。决策分析模型可以包括来自具有中间或替代终点的试验的证据,并通过复杂的校准方法外推到长期终点,如发病率和死亡率。此外,决策分析模型是独一无二的,因为可以同时评估大量筛选方案,这在随机对照试验(RCT)中是不可行的。尽管如此,基于随机对照试验数据的筛查评估是有价值的,因为对同一个人的成本和健康效益都进行了测量,从而能够更深入地分析成本和健康效益之间的相互作用。筛查的评估涉及多个利益攸关方以及成本效益之外的其他考虑,例如分布问题、疾病严重程度和能力影响决策。损益权衡分析是补充成本效益分析的有用工具。决策分析模型通常基于100%的参与,这在实践中很少出现。如果参与的人与没有选择参与的人不同,例如,在疾病或状况的风险方面,这将导致选择偏差,并且实践中的结果可能偏离基于100%参与的结果。开发新的诊断方法或预防性干预措施需要重新评估筛查的成本效益。例如,如果一种疾病的治疗变得更有效,筛查的成本效益就会降低。同样,疫苗的引入(例如宫颈癌人乳头瘤病毒疫苗接种)可能会影响筛查的成本效益。有了从登记处获得的个人层面的数据,就有机会在分析中更好地反映筛查对健康行为的异质性和长期后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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