Department of Public Health, Erasmus MC, Erasmus University, Rotterdam, the Netherlands (JFO’M, JvR, MvB)
Department of Health Policy and Management, Trinity College Dublin, Dublin, Ireland (JFO’M)
Med Decis Making. 2013 Apr;33(3):407-14. doi: 10.1177/0272989X12453503. Epub 2012 Aug 27.
Models used in cost-effectiveness analysis (CEA) of screening programs may include 1 or many birth cohorts of patients. As many screening programs involve multiple screens over many years for each birth cohort, the actual implementation of screening often involves multiple concurrent recipient cohorts. Consequently, some advocate modeling all recipient cohorts rather than 1 birth cohort, arguing it more accurately represents actual implementation. However, reporting the cost-effectiveness estimates for multiple cohorts on aggregate rather than per cohort will fail to account for any heterogeneity in cost-effectiveness between cohorts. Such heterogeneity may be policy relevant where there is considerable variation in cost-effectiveness between cohorts, as in the case of cancer screening programs with multiple concurrent recipient birth cohorts, each at different stages of screening at any one point in time.
The purpose of this study is to illustrate the potential disadvantages of aggregating cost-effectiveness estimates over multiple cohorts, without first considering the disaggregate estimates. Analysis. We estimate the cost-effectiveness of 2 alternative cervical screening tests in a multicohort model and compare the aggregated and per-cohort estimates. We find instances in which the policy choices suggested by the aggregate and per-cohort results differ. We use this example to illustrate a series of potential disadvantages of aggregating CEA estimates over cohorts.
Recent recommendations that CEAs should consider the cost-effectiveness of more than just a single cohort appear justified, but the aggregation of estimates across multiple cohorts into a single estimate does not.
用于筛查计划成本效益分析（CEA）的模型可能包括 1 个或多个患者队列。由于许多筛查计划涉及每个患者队列多年进行多次筛查，因此实际的筛查实施通常涉及多个同时存在的受检者队列。因此，一些人主张对所有受检者队列进行建模，而不是对 1 个出生队列进行建模，认为这样更能准确地反映实际实施情况。然而，将多个队列的成本效益估计值汇总而不是按队列分别报告，将无法说明队列之间成本效益的任何异质性。如果队列之间的成本效益存在显著差异，例如存在多个同时存在的受检者出生队列的癌症筛查计划，每个队列在任何特定时间都处于不同的筛查阶段，那么这种异质性可能与政策相关。
本研究的目的是说明在不首先考虑非汇总估计值的情况下，汇总多个队列的成本效益估计值可能带来的潜在缺点。分析。我们在多队列模型中估计了两种替代的宫颈癌筛查检测方法的成本效益，并比较了汇总和按队列的估计值。我们发现了一些情况下，汇总和按队列的结果所建议的政策选择存在差异。我们使用这个例子来说明汇总队列的 CEA 估计值可能存在的一系列潜在缺点。
最近的建议认为，CEA 应该考虑不仅仅是单个队列的成本效益，这似乎是合理的，但将多个队列的估计值汇总为一个单一的估计值并不可行。
