Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
Centre for Health Economics and Policy Analysis, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
BMJ. 2022 Jun 22;377:e069573. doi: 10.1136/bmj-2021-069573.
To assess the association between industry sponsorship (drug, medical device, and biotechnology companies) and cost effectiveness results in cost effectiveness analysis (CEA).
Registry based analysis DATA SOURCE: The Tufts Cost-Effectiveness Analysis Registry was used to identify all CEAs published in Medline between 1976 and 2021.
CEAs that reported incremental cost effectiveness ratio (ICER) using quality adjusted life year and provided sufficient information about the magnitude or location of the ICER.
Descriptive analyses were used to describe and compare the characteristics of CEAs with and without industry sponsorship. Logistic regression was used to identify the association between industry sponsorship and the cost effective conclusion using selected threshold values ($50 000 (£40 511; €47 405), $100 000, and $150 000). Robust linear regression was used to assess the association between industry sponsorship and the magnitude of ICER. All regression analyses were adjusted for disease and study design characteristics.
8192 CEAs were eligible and included in the analysis, with 2437 (29.7%) sponsored by industry. Industry sponsored CEAs were more likely to publish ICERs below $50 000 (adjusted odds ratio 2.06, 95% confidence interval 1.82 to 2.33), $100 000 (2.95, 2.52 to 3.44), and $150 000 (3.34, 2.80 to 3.99) than non-industry sponsored studies. Among 5877 CEAs that reported positive incremental costs and quality adjusted life years, ICERs from industry sponsored studies were 33% lower (95% confidence interval -40 to -26) than those from non-industry sponsored studies.
Sponsorship bias in CEAs is significant, systemic, and present across a range of diseases and study designs. Use of CEAs conducted by independent bodies could provide payers with more ability to negotiate lower prices. This impartiality is especially important for countries that rely on published CEAs to inform policy making for insurance coverage because of limited capacity for independent economic analysis.
评估行业赞助(制药、医疗器械和生物技术公司)与成本效益分析(CEA)中成本效益结果之间的关联。
基于登记处的分析
使用 Tufts 成本效益分析登记处来确定 1976 年至 2021 年间在 Medline 上发表的所有 CEA。
报告增量成本效益比(ICER)并使用质量调整生命年(QALY)的 CEA,并提供关于 ICER 幅度或位置的足够信息。
描述性分析用于描述和比较有和没有行业赞助的 CEA 的特征。使用逻辑回归来确定行业赞助与使用选定阈值(50000 美元[40511 英镑;47405 欧元]、100000 美元和 150000 美元)的成本效益结论之间的关联。稳健线性回归用于评估行业赞助与 ICER 幅度之间的关联。所有回归分析均根据疾病和研究设计特征进行调整。
8192 项 CEA 符合条件并纳入分析,其中 2437 项(29.7%)由行业赞助。行业赞助的 CEA 更有可能发布低于 50000 美元(调整后的优势比 2.06,95%置信区间 1.82 至 2.33)、100000 美元(2.95,2.52 至 3.44)和 150000 美元(3.34,2.80 至 3.99)的 ICER,而非行业赞助研究。在报告了增量成本和质量调整生命年的 5877 项 CEA 中,来自行业赞助研究的 ICER 比非行业赞助研究低 33%(95%置信区间-40 至-26)。
CEA 中的赞助偏见是显著的、系统性的,存在于多种疾病和研究设计中。使用独立机构进行的 CEA 可以为支付者提供更多的能力来协商更低的价格。对于那些由于独立经济分析能力有限而依赖已发表的 CEA 来为保险覆盖范围制定政策的国家来说,这种公正性尤为重要。