Integration of Geriatric Measures Alongside Disease-Based Measures to Advance Precision Oncology for Older Veterans with Multiple Myeloma

尽管领先的癌症组织，如美国临床学会 肿瘤学现在建议对所有患有癌症的老年人进行老年评估，这些 由于以下方面的限制，评估在退伍军人管理局和其他地方尚未得到广泛采用 资源、老年病专业知识和忙碌的肿瘤学诊所的时间。退伍军人事务部的国家精度 肿瘤学计划正在描绘骨髓瘤和其他癌症的肿瘤遗传学特征 以前所未有的方式治疗疾病和个性化治疗。然而，真正个性化的癌症 对老年退伍军人的治疗必须不仅基于肿瘤的“基因”，而且还基于老年人 “表型。”克拉克·杜蒙蒂埃博士是一名老年病学家和临床研究员，专注于 将老年措施转变为肿瘤学。为CDA-2提出的研究将推动Dr。 Dumontier的长期目标是开发可行和有效的工具来帮助VA肿瘤学家整合 虚弱和多发病与骨髓瘤特异性因素一起提高肿瘤的精确度 患有骨髓瘤的老年退伍军人。此应用程序的目标是以电子方式测量 退伍军人中年龄在65岁以上的新发骨髓瘤患者的虚弱和多发病 从2004年至今，使用退伍军人管理局全国整合的医疗保健数据 卫生系统。初步研究结果表明，虚弱和多发病可以很快 使用诊断和程序代码以及来自电子健康记录的数据进行评估 (电子健康记录)。目标1将确定电子脆弱性指数VA-FI是否可以独立预测 老年骨髓瘤退伍军人的死亡率和住院率，以及它是否改变了这种影响 对这些结果进行初步治疗。分析将包括重要的骨髓瘤特异性因素 例如三胞胎或双胞胎化疗、分期和细胞遗传学、社会人口统计学变量 和预见性实验室。目标2将确定多发病模式是否独立地预测 骨髓瘤的死亡率和住院率，以及它们是否改变了特定方案的效果 对这些结果的看法。机器学习分析将应用于67种慢性病 在退伍军人数据库中进行测量，以确定这些模式及其对老年退伍军人的影响 骨髓瘤。目标3将开发和验证死亡率的预测性风险模型，该模型包含 虚弱和多发病与骨髓瘤特异性因素。一旦经过验证，该模型将被 转化为嵌入退伍军人事务部电子病历的临床决策支持工具。此工具将帮助退伍军人管理局 肿瘤学家快速评估虚弱和多发病并提高个体化预后 以及对患有骨髓瘤的老年退伍军人的治疗决定。有指导的研究和培训 本CDA-2中描述的计划将加速Dumontier博士发展成为独立的 退伍军人事务部老年肿瘤学研究员。他的导师团队包括简·德雷弗博士和尼基尔 Munshi、Michael Gaziano和Mary Brophy--老年病学、肿瘤学和大数据科学领域的领导者 来自新英格兰老年研究教育临床中心(GRECC)的 麻省退伍军人流行病学研究和信息中心(Maveric)，以及 弗吉尼亚国家精准肿瘤学项目。在这些导师的指导下，在 与Maveric合作，Dumontier博士将继续进行培训，以提供(1)经验 具有大型数据库调查；(2)高级统计分析和机器方面的专业知识 学习；(3)项目管理和多学科协作；(4)沟通， 领导技能和职业发展。这项培训和指导研究将为 作为一名退伍军人管理局临床研究员，他有竞争力获得退伍军人事务部荣誉奖。

Although leading cancer-focused organizations such as the American Society of Clinical Oncology now recommend geriatric assessments for all older adults with cancer, these assessments have not been widely adopted within VA and elsewhere due to limitations in resources, geriatrics expertise, and time in busy oncology clinics. The VA National Precision Oncology Program is profiling tumor genetics in myeloma and other cancers to characterize disease and personalize therapy in unprecedented fashion. However, truly personalized cancer treatment for older Veterans must be based not only on tumor “genotype,” but also on older adult “phenotype.” Dr. Clark DuMontier is a geriatrician and clinical investigator focused on integrating geriatric measures into oncology. The research proposed for this CDA-2 will advance Dr. DuMontier’s long-term goal of developing feasible and valid tools to help VA oncologists integrate frailty and multimorbidity alongside myeloma-specific factors to advance precision oncology for older Veterans with myeloma. The objectives of this application are to electronically measure frailty and multimorbidity in over 5000 Veterans age ³ 65 years with myeloma newly treated in VA from 2004-present using healthcare data that is readily available within VA’s nationally integrated health system. Preliminary findings demonstrate that frailty and multimorbidity can be rapidly assessed using diagnostic and procedural codes and data from the electronic health record (EHR). Aim 1 will determine whether an electronic frailty index, the VA-FI, independently predicts mortality and hospitalizations in older Veterans with myeloma, and whether it modifies the effect of initial therapy on these outcomes. Analyses will include important myeloma-specific factors such as triplet or doublet chemotherapy, stage and cytogenetics, sociodemographic variables, and prognostic labs. Aim 2 will determine whether multimorbidity patterns independently predict mortality and hospitalizations in myeloma, and whether they modify the effect of specific regimens on these outcomes. A machine learning analysis will be applied to 67 chronic conditions measured within the VA database to define these patterns and their impact in older Veterans with myeloma. Aim 3 will develop and validate a predictive risk model for mortality that incorporates frailty and multimorbidity with myeloma-specific factors. Once validated, this model will be translated into a clinical decision support tool embedded in the VA EHR. This tool will help VA oncologists to rapidly estimate frailty and multimorbidity and enhance individualized prognosis and treatment decisions for older Veterans with myeloma. The mentored research and training program described in this CDA-2 will accelerate Dr. DuMontier’s development into an independent VA investigator in geriatric oncology. His mentorship team includes Drs. Jane Driver, Nikhil Munshi, Michael Gaziano, and Mary Brophy—leaders in geriatrics, oncology, and big data science from the New England Geriatric Research Education Clinical Center (GRECC), the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), and the VA National Precision Oncology Program. Under the guidance of these mentors and in collaboration with MAVERIC, Dr. DuMontier will pursue training that will provide (1) experience with large database investigation; (2) expertise in advanced statistical analyses and machine learning; (3) project management and multidisciplinary collaboration; and (4) communication, leadership skills, and professional development. This training and mentored research will prepare him to be competitive for a VA Merit Award toward independence as a VA clinician investigator.