Quantifying and improving radiotherapy outcomes among Veterans

量化和改善退伍军人的放射治疗结果

• 批准号: 9892367
• 负责人: Reid Thompson
• 金额: --
• 依托单位: PORTLAND VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9892367
• 关键词: Area; Biological; Cancer Patient; Cells; Clinical; Counseling; DNA Damage; DNA Repair; Data; Defect; Development; Diagnostic Imaging; Disease; Dose; Dose Fractionation; Exposure to; General Population; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Goals; Incidence; Individual; Ionizing radiation; Left; Life; Location; Malignant Neoplasms; Measures; Modality; Nature; Normal tissue morphology; Outcome; Patients; Persons; Play; Population; Radiation; Radiation Dose Unit; Radiation exposure; Radiation therapy; Radiation-Induced Cancer; Relative Risks; Research; Resources; Risk; Risk Assessment; Role; Second Primary Cancers; Second Primary Neoplasms; Secondary to; Stratification; Susceptibility Gene; Testing; Therapeutic; Time; Treatment Efficacy; Variant; Veterans; anti-cancer; cancer risk; cancer therapy; clinical decision-making; cohort; data warehouse; genetic risk factor; genetic variant; high risk; improved; insight; neglect; palliation; programs; prospective; radiation risk; rare variant; repaired; screening; tool; treatment site; virtual

For more than a century, radiation has been used as an effective therapeutic modality for many different cancers and other diseases. Today, radiation therapy is clinically indicated for more than half of all cancer patients, with the ability to provide cure, local or regional control, and symptomatic palliation depending upon the clinical context. However, radiation can leave a lasting mark on the normal tissues left behind. In particular, it has long been known that ionizing radiation can promote cancer in otherwise normal tissue. While it is relatively rare for an individual to develop a secondary malignancy (radiation-induced cancer following treatment for a separate cancer), actual estimates of this rate vary widely according to different studies. Furthermore, patient-level discussions of secondary malignancy rates are understandably variable, neglect any understanding of the role of radiation dose or treatment site, and are generally universal assumptions not tailored to the disease or the patient themselves. My goal is to better understand the individualized risk of cancer induced by ionizing radiation. My central hypothesis is that individual genetic variability is likely to modify the risks of radiation-induced malignancy. However we have poor quantitative insights and an overall incomplete picture of the identity, nature, and effect size of genetic determinants of these risks. The ultimate goal of this proposal is to develop improved risk prediction frameworks incorporating prospective genetic stratification. This would be invaluable for treatment-related clinical decision-making, patient counseling, and tailoring post-radiation screening paradigms. I plan to test my central hypothesis by pursuing the following three Specific Aims: Aim 1. Identify a high-confidence cohort of Veterans receiving radiation therapy Aim 2. Characterize second and secondary malignancy rates within the VA Aim 3. Quantify genetic risk factors of radiation-induced secondary malignancies To accomplish these aims, I will first implement, validate, and apply automated dose quantification tools to national-level cohort data from the VA Corporate Data Warehouse (CDW), to extract radiotherapy details such as date, modality, dose, and fractionation, among other clinically important radiotherapy treatment variables. I will then identify new cancer diagnos(es) following initial cancer treatment and perform propensity matching of second cancer risk for Veterans exposed or unexposed to radiotherapy. Moreover, I will quantify second and presumed secondary malignancy rates among individuals as a function of estimated integral radiation dose. Using genetic data from the Million Veteran Program (MVP), I will measure enrichment and potential functional significance of genetic variants among a cohort of Veterans with radiation-induced secondary malignancy. I will also identify putative DNA repair defects and other rare variants in known cancer predisposition genes among Veterans with second cancers. My completion of the research described in Aims 1, 2 and 3 is expected to establish a detailed understanding of genetic risk factors for radiation-induced malignancy. Moreover, these Aims will establish a highly valuable cohort of veterans with curated radiotherapy and secondary malignancy information, along with corresponding germline genetic data. Ultimately, these resources and results are expected to have a profound impact on current radiation risk assessment frameworks, by deepening our understanding of the interplay between individual genetics and personalized risks.

一个多世纪以来，放射线一直被用作一种有效的治疗方式 对于许多不同的癌症和其他疾病。如今，放射治疗在临床上适用于 超过一半的癌症患者有能力提供治愈、局部或区域控制， 以及根据临床情况进行症状缓解。然而，辐射可能会留下 在正常组织上留下持久的痕迹。特别是，人们早就知道电离 辐射会促进其他正常组织发生癌症。虽然对于一个人来说这是相对罕见的 个体发展为继发性恶性肿瘤（治疗后放射诱发的癌症） 一种单独的癌症），根据不同的研究，对该比率的实际估计差异很大。 此外，患者层面对继发性恶性肿瘤发生率的讨论是可以理解的 变量，忽略对辐射剂量或治疗部位的作用的任何理解，并且是 一般而言，普遍的假设并不适合疾病或患者本身。 我的目标是更好地了解电离诱发癌症的个体化风险 辐射。我的中心假设是个体遗传变异可能会改变风险 辐射诱发的恶性肿瘤。然而，我们的定量洞察力和总体 对这些风险的遗传决定因素的身份、性质和影响大小的不完整描述。 该提案的最终目标是开发改进的风险预测框架 纳入前瞻性遗传分层。这对于治疗相关的疾病来说是无价的 临床决策、患者咨询和定制放射后筛查范例。 我计划通过追求以下三个具体目标来检验我的中心假设： 目标 1. 确定接受放射治疗的高可信度退伍军人群体 目标 2. 描述 VA 内的二次和继发性恶性肿瘤发生率 目标 3. 量化辐射诱发继发性恶性肿瘤的遗传风险因素 为了实现这些目标，我将首先实施、验证和应用自动剂量 来自 VA 企业数据仓库 (CDW) 的国家级队列数据的量化工具， 提取放射治疗详细信息，例如日期、方式、剂量和分割等 临床上重要的放射治疗变量。然后我将确定新的癌症诊断 初次癌症治疗后，对第二次癌症风险进行倾向匹配 接受或未接受放射治疗的退伍军人。此外，我将量化第二个和 假定的个体继发性恶性肿瘤发生率与估计积分的函数关系 辐射剂量。使用来自百万退伍军人计划 (MVP) 的遗传数据，我将测量 退伍军人群体中遗传变异的富集和潜在功能意义 患有辐射诱发的继发性恶性肿瘤。我还将识别假定的 DNA 修复缺陷和 患有第二种癌症的退伍军人中已知癌症易感基因的其他罕见变异。 我完成目标 1、2 和 3 中描述的研究预计将建立一个 详细了解辐射诱发恶性肿瘤的遗传风险因素。而且，这些 目标将建立一个非常有价值的退伍军人队列，进行精心策划的放射治疗和二次治疗 恶性肿瘤信息以及相应的种系遗传数据。最终，这些 资源和结果预计将对当前的辐射风险产生深远影响 评估框架，通过加深我们对个体之间相互作用的理解 遗传和个性化风险。