RTI Health Solutions, 3040 Cornwallis Road, Post Office Box 12194, Research Triangle Park, NC 27709-2194, USA.
Pharmacoeconomics. 2013 Apr;31(4):289-304. doi: 10.1007/s40273-013-0037-6.
Decision-analytic modelling is often used to examine the economics associated with using a specific treatment. As a result, it is important to understand structural and methodological approaches used in published decision-analytic models for examining the cost effectiveness of 5α-reductase inhibitors (5ARIs) for prostate cancer (PCa) chemoprevention. This understanding allows us to provide recommendations for using decision modelling in future economic evaluations of chemoprevention for PCa.
A review of the published literature was performed using MEDLINE and the Cochrane Library to identify studies involving mathematical decision models that evaluated 5ARIs for PCa chemoprevention. Published articles were reviewed and key modelling components were extracted and summarized. Recommendations for developing future decision models to examine the economic consequences of PCa chemoprevention were presented.
We identified seven published models of PCa chemoprevention. All the models identified used a Markov framework with time horizons ranging from 4 years to lifetime. Due to the wide range of patient risk groups examined, PCa risk data were taken from the Surveillance, Epidemiology, and End Results (SEER) and other databases or estimates published in relevant clinical trials. Treatment effects included change in the incidence of high- and low-grade PCa and impacts on benign prostate hyperplasia. Adverse events were considered to affect compliance, discontinuation and quality of life. Quality-of-life impacts were similar among studies. Examination of modelling parameter sensitivities was comprehensive.
Published models have examined the cost effectiveness of PCa chemoprevention; however, limitations exist. Decision models should take into account the full PCa clinical pathway when compiling health states. The time horizon should be long enough to consider the full benefit of chemoprevention while allowing actual time receiving the drug to occur from the start of the model until a man's life expectancy is less than 10 years. Baseline PCa risk should be specific to the population of concern. Models should examine the impact on both low- and high-grade tumours and account for the impact of 5ARIs on benign prostatic hyperplasia. Because chemoprevention has an upfront effect, the structure of the model should be constructed so that the downstream effect of avoiding or delaying recurrence can be considered. Adverse events due to chemoprevention should be considered through compliance, discontinuation or quality-of-life impact, and understanding the impact of avoiding PCa and benign prostatic hyperplasia events are important model properties.
决策分析模型常用于评估使用特定治疗方法的经济学价值。因此，了解已发表的决策分析模型中用于评估 5α-还原酶抑制剂（5ARIs）在前列腺癌（PCa）化学预防中的成本效益的结构和方法学方法非常重要。这种理解使我们能够为未来使用决策模型进行 PCa 化学预防的经济评估提供建议。
使用 MEDLINE 和 Cochrane 图书馆对已发表的文献进行综述，以确定涉及评估 5ARIs 用于 PCa 化学预防的数学决策模型的研究。审查已发表的文章，并提取和总结关键建模组件。提出了用于开发未来决策模型以检查 PCa 化学预防的经济后果的建议。
我们确定了 7 项已发表的 PCa 化学预防模型。所有确定的模型均使用具有 4 年至终生时间范围的 Markov 框架。由于所检查的患者风险组范围广泛，因此从监测、流行病学和最终结果（SEER）和其他数据库或相关临床试验中发表的估计中获取了 PCa 风险数据。治疗效果包括高等级和低等级 PCa 的发病率变化以及对良性前列腺增生的影响。不良事件被认为会影响依从性、停药和生活质量。研究之间的生活质量影响相似。对建模参数敏感性的检查是全面的。
已发表的模型已经研究了 PCa 化学预防的成本效益；然而，存在局限性。在编制健康状况时，决策模型应考虑完整的 PCa 临床途径。时间范围应足够长，以考虑化学预防的全部益处，同时允许药物实际开始使用的时间从模型开始到一个人的预期寿命小于 10 年。基础 PCa 风险应特定于关注人群。模型应检查低等级和高等级肿瘤的影响，并考虑 5ARIs 对良性前列腺增生的影响。由于化学预防具有前期效果，因此应构建模型的结构，以便可以考虑避免或延迟复发的下游效果。应通过依从性、停药或生活质量影响考虑因化学预防而产生的不良事件，并且了解避免 PCa 和良性前列腺增生事件的影响是模型的重要特性。
