Michaeli Daniel Tobias, Michaeli Thomas
Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany.
Schumpeter School of Business and Economics, University of Wuppertal, Wuppertal, Germany.
Pharmacoeconomics. 2025 Apr;43(4):415-427. doi: 10.1007/s40273-024-01448-x. Epub 2024 Dec 30.
For US Medicare and Medicaid, single drug prices do not reflect the value of supplemental indications. Value-based indication-specific and weighted-average pricing has been suggested for drugs with multiple indications. Under indication-specific pricing, a distinct price is assigned to the differential value a drug offers in each indication. Under weighted-average pricing, a single drug price is calculated that reflects the value and/or volume of each indication. This study estimates price reductions and cost savings for cancer drugs under value-based indication-specific pricing and weighted-average pricing.
We collected data on US Food and Drug Administration (FDA)-approved cancer drugs and indications (2003-2020) from FDA labels, the Global Burden of Disease study, clinicaltrials.gov, and Medicare and Medicaid. A multivariable regression analysis, informed by characteristics of original indications, was used to predict value-based indication-specific prices for supplemental indications. These indication-specific prices were combined with each indication's prevalence data to estimate value-based weighted-average prices and potential cost savings under each policy.
We identified 123 cancer drugs with 308 indications. Medicare and Medicaid spent a total of $28.2 billion on these drugs in 2020. Adopting value-based indication-specific pricing would increase drug prices by an average of 3.9%, with cost savings of $3.0 billion (10.6%). However, 43.7% higher prices for ultra-rare diseases would increase spending by 16.8% ($44 million). Adopting value-based weighted-average pricing would reduce prices by an average of 4.6% and spending by $3.0 billion (10.6%). Under weighted-average pricing, prices for and spending on ultra-rare diseases would be reduced by 22.6% and $55 million, respectively.
Value-based indication-specific and weighted-average pricing could help to align the value and price of new indications, thereby reducing expenditure on drugs with multiple indications.
对于美国医疗保险和医疗补助计划而言，单一药品价格无法反映补充适应症的价值。对于具有多种适应症的药物，有人建议采用基于价值的适应症特定定价和加权平均定价。在适应症特定定价下，会为药物在每种适应症中所提供的差异价值赋予一个独特的价格。在加权平均定价下，会计算出一个反映每种适应症的价值和/或用量的单一药品价格。本研究估计了基于价值的适应症特定定价和加权平均定价下癌症药物的价格降低幅度和成本节约情况。
我们从美国食品药品监督管理局（FDA）标签、全球疾病负担研究、临床试验.gov以及医疗保险和医疗补助计划中收集了有关FDA批准的癌症药物和适应症（2003 - 2020年）的数据。利用基于原始适应症特征的多变量回归分析来预测补充适应症基于价值的适应症特定价格。这些适应症特定价格与每种适应症的患病率数据相结合，以估计每种政策下基于价值的加权平均价格和潜在成本节约情况。
我们识别出123种癌症药物，共有308种适应症。2020年，医疗保险和医疗补助计划在这些药物上总共花费了282亿美元。采用基于价值的适应症特定定价将使药品价格平均上涨3.9%，成本节约30亿美元（10.6%）。然而，超罕见疾病的价格上涨43.7%将使支出增加16.8%（4400万美元）。采用基于价值的加权平均定价将使价格平均降低4.6%，支出减少30亿美元（10.6%）。在加权平均定价下，超罕见疾病的价格和支出将分别降低22.6%和5500万美元。
基于价值的适应症特定定价和加权平均定价有助于使新适应症的价值与价格相匹配，从而减少具有多种适应症药物的支出。
