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Minimization of resource utilization data collected within cost-effectiveness analyses conducted alongside Canadian Cancer Trials Group phase III trials
Clinical Trials ( IF 2.7 ) Pub Date : 2021-04-19 , DOI: 10.1177/17407745211005045
Matthew C Cheung 1, 2, 3 , Kelvin Kw Chan 1, 2 , Shane Golden 4 , Annette Hay 2 , Joseph Pater 4 , Anca Prica 5 , Bingshu E Chen 4 , Natasha Leighl 5 , Nicole Mittmann 2, 6
Affiliation  

Background

Cost-effectiveness analyses embedded within randomized trials allow for evaluation of value alongside conventional efficacy outcomes; however, collection of resource utilization data can require considerable trial resources.

Methods

We re-analyzed the results from four phase III Canadian Cancer Trials Group trials that embedded cost-effectiveness analyses to determine the impact of minimizing potential cost categories on the incremental cost-effectiveness ratios. For each trial, we disaggregated total costs into component incremental cost categories and recalculated incremental cost-effectiveness ratios using (1) only the top 3 cost categories, (2) the top 5 cost categories, and (3) all cost components. Using individual trial-level data, confidence intervals for each incremental cost-effectiveness ratio simulation were generated by bootstrapping and descriptively presented with the original confidence intervals (and incremental cost-effectiveness ratios) from the publications.

Results

Drug acquisition costs represented the highest incremental cost category in three trials, while hospitalization costs represented the other consistent cost driver and the top incremental cost category in the fourth trial. Recalculated incremental cost-effectiveness ratios based on fewer cost components (top 3 and top 5) did not differ meaningfully from the original published results. Based on conventional willingness-to-pay thresholds (US$50,000–US$100,000 per quality-adjusted life-year), none of the re-analyses would have changed the original perception of whether the experimental therapies were considered cost-effective.

Conclusions

These results suggest that the collection of resource utilization data within cancer trials could be narrowed. Omission of certain cost categories that have minimal impact on incremental cost-effectiveness ratio, such as routine laboratory investigations, could reduce the costs and undue burden associated with the collection of data required for cancer trial cost-effectiveness analyses.



中文翻译:

在与加拿大癌症试验组 III 期试验一起进行的成本效益分析中收集的资源利用数据最小化

背景

随机试验中嵌入的成本效益分析允许在评估常规疗效结果的同时评估价值;然而,收集资源利用数据可能需要大量的试验资源。

方法

我们重新分析了四项 III 期加拿大癌症试验组试验的结果,这些试验嵌入了成本效益分析,以确定最小化潜在成本类别对增量成本效益比的影响。对于每项试验,我们将总成本分解为组件增量成本类别,并使用 (1) 仅前 3 个成本类别、(2) 前 5 个成本类别和 (3) 所有成本组件重新计算增量成本效益比。使用单个试验级别的数据,每个增量成本效益比模拟的置信区间是通过自举法生成的,并用出版物中的原始置信区间(和增量成本效益比)进行描述性呈现。

结果

在三项试验中,药品购置成本代表了最高的增量成本类别,而住院费用代表了另一个一致的成本驱动因素,也是第四项试验中最高的增量成本类别。基于较少的成本构成(前 3 名和前 5 名)重新计算的增量成本效益比与最初公布的结果没有显着差异。根据传统的支付意愿阈值(每个质量调整生命年 50,000 美元至 100,000 美元),没有一项重新分析会改变对实验疗法是否具有成本效益的最初看法。

结论

这些结果表明,可以缩小癌症试验中资源利用数据的收集范围。省略对增量成本效益比影响最小的某些成本类别,例如常规实验室调查,可以减少与癌症试验成本效益分析所需数据收集相关的成本和过度负担。

更新日期:2021-04-19
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