帕博利珠单抗治疗EGFR基因突变阴性和ALK阴性的晚期或转移性非小细胞肺癌的预算影响分析
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篇名: 帕博利珠单抗治疗EGFR基因突变阴性和ALK阴性的晚期或转移性非小细胞肺癌的预算影响分析
TITLE: Budget impact analysis of pembrolizumab in the treatment for EGFR gene mutation-negative and anaplastic lymphoma kinase-negative locally advanced or metastatic non-small cell lung cancer
摘要: 目的 从国家医疗保障支付方的角度出发,基于真实世界数据预测将帕博利珠单抗(PEM)纳入国家医保后,其作为一线药物治疗晚期或转移性非小细胞肺癌对医保基金可能产生的影响,从而为医保部门决策提供依据。方法构建预算影响分析模型,以2023年为基线年,比较PEM未纳入医保和纳入医保后对未来5年(2024-2028年)医保基金支出的影响。目标人群为EGFR基因突变阴性和间变性淋巴瘤激酶(ALK)阴性的局部晚期或转移性非小细胞肺癌患者;测算成本主要包括药品成本、不良反应处理成本、检查费用、入院监护费用等;以广东省183家医院2020-2022年PEM的配备率作为市场份额。采用单因素敏感性分析检验基础分析结果的稳健性。结果PEM未纳入医保时,2024-2028年目标人群的医保报销金额为493362.35万~515119.83万元;若将PEM纳入医保,上述数据范围为1187197.22万~1454057.10万元;两种情境下的医保报销增额为672077.39万~960694.75万元。PEM纳入医保后的医保报销金额占当年医保基金支出的比例分别为0.2980%、0.2621%、0.2288%、0.2082%、0.1857%,医保报销增额占当年医保基金支出增加部分的1.0840%、0.9957%、0.8886%、0.8863%、0.8616%,均呈逐年递减趋势。结论若将PEM纳入医保,由于其单价较高,导致医疗支出相应增加,将对医保基金支出产生较大冲击;但是,将该药用于EGFR基因突变阴性和ALK阴性的局部晚期或转移性非小细胞肺癌患者时,其医保报销金额占当年医保基金支出的比例以及医保报销增额占当年医保基金支出增长部分的比例均逐年降低。
ABSTRACT: OBJECTIVE To predict the possible impact of pembrolizumab(PEM) as a first-line drug after being included in the national medical insurance system in the treatment of advanced or metastatic non-small cell lung cancer based on real-world data from the perspective of the national medical insurance payer, to provide a basis for the decision-making of the medical insurance department. METHODS A budget impact analysis model was constructed to compare the impact of pembrolizumab not included in medical insurance and included in medical insurance on medical insurance fund expenditure in the next five years( 2024- 2028) with 2023 as the baseline year. The target population was the patients with EGFR gene mutation-negative and anaplastic lymphoma kinase (ALK)-negative locally advanced or metastatic non-small cell lung cancer; estimated cost mainly included the cost of drugs, the cost of adverse reaction treatment, the cost of examination, the cost of admission and monitoring, etc; equipment ratio of PEM in 183 hospitals of Guangdong province from 2020 to 2022 was used as the market share. Univariate sensitivity analysis was used to test the robustness of the basic analysis results. RESULTS When PEM was not included in the medical insurance, the medical insurance reimbursement amount of the target population from 2024 to 2028 was 4 933 623.5 thousand yuan-5 151 198.3 thousand yuan, respectively. If PEM was included in the medical insurance, the above data were 11 871 972.2 thousand yuan-14 540 571.0 thousand yuan, respectively; the increase in medical insurance reimbursement under the two scenarios was 6 720 773.9 thousand yuan-9 606 947.5 thousand yuan, respectively. The proportion of medical insurance reimbursement to the medical insurance expenditure of the year after PEM was included in medical insurance was 0.298 0%, 0.262 1%, 0.228 8%, 0.208 2%, and 0.185 7%, respectively. The increase in medical insurance reimbursement accounted for 1.084 0%, 0.995 7%, 0.888 6%, 0.886 3%, and 0.861 6% of the increase in the expenditure of the medical insurance fund in the current year, all of which showed a decreasing trend year by year. CONCLUSIONS If PEM is included in medical insurance, due to its high unit price, the medical expenditure will increase accordingly, which will have a great impact on the medical insurance fund expenditure. However, when the drug is used in patients with EGFR mutation-negative and ALK-negative locally advanced or metastatic non-small cell lung cancer, the proportion of the medical insurance reimbursement amount in the current year’s medical insurance fund expenditure and the proportion of the increase in medical insurance reimbursement in the current year’s increase in medical insurance fund expenditure are decreasing year by year.
期刊: 2024年第35卷第17期
作者: 郭娅;文海棠;谢又佳;谢菲;王冰;陈永邦;杨宁;杨晨;万宁
AUTHORS: GUO Ya, WEN Haitang,XIE Youjia,XIE Fei,WANG Bing,CHEN Yongbang,YANG Ning,YANG Chen,WAN Ning
关键字: 帕博利珠单抗;非小细胞肺癌;预算影响分析;真实世界数据;EGFR基因突变阴性;间变性淋巴瘤激酶阴性;医疗保险
KEYWORDS: pembrolizumab; non-small cell lung cancer; budget impact analysis; real-world data; EGFR gene mutation-
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