Multilevel factors associated with disparities in the use of targeted cancer therapies in Medicare

摘要 本申请是为了响应被标识为NOT-CA的特别利益通知（NOSI）而提交的- 23-044.识别患者的致病性变异是至关重要的，使使用的治疗和指导 预防然而，基因组癌症医学中存在重要的种族差异：例如，黑人 在获得生殖系癌症基因组服务方面存在显著差异， 任何种族/族裔群体的死亡负担。初步证据表明， 基因组靶向治疗的使用。虽然亲本R 01关注的是众所周知的生殖系差异， 癌症基因组风险测试，相当少的是知道是否有差异，在使用 基因组靶向癌症治疗。我们将评估这些差异和潜在的重要作用 健康政策因素，因为它们与医疗保险中癌症病例年龄之间的差异有关。2018年3月， 为了改善医疗保险受益人获得靶向基因组癌症治疗的机会，CMS发布了一份国家 覆盖率确定（NCD）支付基于下一代测序（NGS）的肿瘤基因组检测， 晚期或转移性癌症患者，既往无NGS检测。实施新的付款方式 医疗保险的政策旨在增加基因组靶向癌症治疗的使用。然而， 了解国家NGS测试政策的实施如何影响了 使用基因组靶向治疗。为未来围绕基因组癌症的医疗保险政策提供信息 因此，重要的是要评估覆盖政策是否公平地解决了获得有效医疗服务的问题。 考虑到在基因检测和靶向治疗方面观察到的差异，本研究将 弥补这一差距。使用最近五年的SEER-Medicare Part D数据，我们将首先记录 NCD用于NGS检测的实施是否增加了基因组靶向治疗的使用。 然后，我们将研究在使用这些疗法时是否存在种族和社会经济差异， 2018年NCD用于NGS测试。选择性基因组靶向口服抗癌药物的应用 NCD之前与之后的对比将是主要关注的结果。政策层面的变量将包括健康 保险因素，如患者的医疗保险优势登记，低收入补贴状态，以及患者 与第三方利益协调。拟议研究的具体目标是：1）比较 在医疗保险受益人中口服基因组靶向抗癌药物的使用前后 实施2018年NCD政策进行NGS测试; 2）检查种族-民族和社会经济 与保险福利设计相关的口服基因组靶向抗癌药物的使用差异。 这项研究的结果可用于为促进癌症健康公平的政策决策提供信息， 改善基因组靶向癌症治疗的可及性。这种方法可以应用于其他药物， 基因组药物，以及基于价值的医疗保健计划。

ABSTRACT This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA- 23-044. Identification of patients with pathogenic variants is crucial to enable the use of treatment and guide prevention. Yet, there are important racial disparities in genomic cancer medicine: for example, Black persons experience significant disparities in access to germline cancer genomic services and bear the largest cancer mortality burden of any racial/ethnic group. Preliminary evidence suggests that there may also be disparities in the use of genomically-targeted therapies. While the parent R01 focuses on well-known disparities in germline cancer genomic risk testing, considerably less is known about whether there are disparities in the use of genomically-targeted cancer therapies. We will assess these disparities and the potentially important role of health policy factors as they relate to disparities among cancer cases ages in Medicare. In March 2018, to improve Medicare beneficiaries’ access to targeted genomic cancer therapies, CMS issued a national coverage determination (NCD) paying for Next Generation Sequencing (NGS) based tumor genomic tests for patients with advanced or metastatic cancer and no previous NGS testing. Implementing the new payment policy by Medicare is intended to increase the use of genomically-targeted cancer treatments. However, little is known about how the implementation of the national policy for NGS testing has influenced disparities in the use of genomically-targeted therapies. To inform future healthcare coverage policies around genomic cancer medicine, it is important to assess whether the coverage policy equitably addresses access to effective treatment, given the disparities observed in both genetic testing and targeted treatments. This study will address this gap. Using the most recent five years of SEER-Medicare Part D data, we will first document whether the implementation of NCD for NGS testing has increased the use of genomically-targeted therapies. Then, we will examine whether there are racial and socio-economic disparities in the use of these therapies, accounting for the 2018 NCD for NGS testing. The use of selected genomically-targeted oral anticancer drugs before vs. after the NCD will be the primary outcome of interest. Policy-level variables will include health insurance factors such as patients’ Medicare Advantage enrollment, low-income subsidy status, and patients with coordination of benefits from third parties. The specific aims of the proposed study are to 1) compare the use of orally administered genomically-targeted cancer agents among Medicare beneficiaries before and after the implementation of the 2018 NCD policy for NGS testing; 2) examine racial-ethnic and socioeconomic disparities in the use of oral genomically-targeted cancer drugs associated with insurance benefit designs. Findings from this study can be used to inform policy decisions for advancing cancer health equity and improving access to genomically-targeted cancer therapies. This approach could be applied to other drugs and genomic medications, as well as value-based healthcare initiatives.