Drug cost avoidance analysis of cancer clinical trials in Spain: a study on cost contributors and their impact

西班牙癌症临床试验药物成本规避分析:成本构成因素及其影响研究

阅读:5

Abstract

OBJECTIVE: Analyze the cost contributors and their impact on the drug cost avoidance (DCA) resulting from cancer clinical trials over the period of 2015-2020 in a tertiary-level hospital in Spain (HCUVA). METHODS: We performed a cross-sectional, observational, retrospective study of a total of 53 clinical trials with 363 patients enrolled. We calculated the DCA from the price of the best standard of care (i.e.: drugs that the institution would otherwise fund). A linear regression model was used to determine cost contributors and estimate their impact. RESULTS: The total DCA was ~ 4.9 million euros (31 clinical trials; 177 enrollees), representing ~ 30% and ~ 0,05% approximately of the annual pharmaceutical expenditures at the HCUVA and for the Spanish Health System, respectively. Cancer type analysis showed that lung cancer had the highest average DCA by trial, indicating that treatments in these trials were the most expensive. Linear regression analysis showed that the number of patients in a trial did not significantly affect that trial's DCA. Instead, cancer type, phase trials, and intention of treatment were significant cost contributors to DCA. Compared to digestive cancer trials, breast and lung trials were significantly more expensive, (p < 0.05 and p < 0.1, respectively). Phase III trials were more expensive than Phase II (p < 0.01) and adjuvant trials were less expensive than palliative (p < 0.05). CONCLUSION: We studied cost contributors that significantly impacted the estimated DCA from cancer clinical trials. Our work provides the groundwork to explore DCA contributors with potential to enhance public relations material and serve as a negotiating tool for budgeting, thus playing an important role to inform decisions about resource allocation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。