Optimizing Treatment Decision Making for Patients with Localized Renal Mass

优化局部肾脏肿块患者的治疗决策

• 批准号: 10734606
• 负责人: Stephen Hembree Culp
• 金额: $ 39.61万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10734606
• 关键词: Address; Affect; Age; Algorithms; Benign; Biopsy; California; Cancer Control; Cancer Intervention; Characteristics; Clinical; Collaborations; Communities; Community Practice; Complex; Confusion; Data; Data Analyses; Data Collection; Data Set; Databases; Decision Making; Detection; Development; Diagnosis; Disease Progression; Expert Opinion; Face; Feedback; Future; Gender; Geography; Goals; Health; Health Care Costs; Health system; Healthcare; Heating; Histology; Hospitals; Image; Impairment; Individual; Institution; Internet; Kidney; Learning; Left; Life; Malignant - descriptor; Malignant Neoplasms; Medical; Medical center; Modality; Modeling; Needles; Nephrectomy; Online Systems; Operative Surgical Procedures; Outcome; Pathologic; Pathway interactions; Patient Preferences; Patient-Focused Outcomes; Patients; Persons; Process; Provider; Quality of life; Recommendation; Renal Cell Carcinoma; Renal Mass; Renal function; Resources; Rest; Risk; San Francisco; Secure; Surveys; System; Thermal Ablation Therapy; Translations; Triage; Uncertainty; Universities; Urologist; Validation; Variant; Virginia; Wisconsin; Work; cancer cell; cohort; community partnership; comorbidity; cost; cost comparison; expectation; functional decline; geographic difference; health care service utilization; individual patient; intervention cost; kidney cell; markov model; multidisciplinary; novel therapeutics; patient oriented; patient variability; personalized care; personalized management; preservation; prospective; prototype; shared database; shared decision making; side effect; tool; treatment effect; treatment optimization; treatment planning; tumor; usability; web based interface; web-based tool; willingness

Project Summary Kidney cancer, or renal cell carcinoma (RCC), is one of the 10 most common cancers in the US. In 2022, over 79,000 people will be diagnosed with RCC. Localized renal masses (LRM, tumors confined to the kidney) make up two-thirds of all RCC. Patients found to have a LRM face many choices on what to do, especially since it is not uncommon for these LRM to be benign. There are currently four ways to manage LRM – active surveillance (watching the mass but not treating it), thermal ablation (heating the mass by putting a needle in it from the outside), partial nephrectomy (surgery to cut the mass out but leave the rest of the kidney in place), and radical nephrectomy (surgery to remove the entire kidney). Patients and doctors are often confused as to which option to pursue since there have been few previous studies to guide them. It is currently recommended that the kidney be preserved in patients who may have future problems with their kidney function. However, it is hard to identify these patients, especially when they have other health issues. Current recommendations are based on “expert opinion” and it is typically left up to the doctor to decide what is best for the patient in terms of risk to the kidney and whether the cancer threatens the life of the patient over other medical conditions the patient may have. The primary goal of our study is to identify specific management plans that can be individualized for a patient with a LRM. This will make it easier for the doctor and patient to decide on the best way to manage the mass. By using a tool built with real-world information, the “trade- off” with each option (like kidney function) will be clearer to the patient, thereby helping them make the best decision. We will create an internet-based database shared between three different major academic hospitals. We will collect information about the health of the patient, how good their kidney function is, and the details of the LRM. We will assess how often biopsies are done prior to treatment of the LRM and what treatments patients tend to pursue. We will develop a set of rules for management of a LRM using a Markov decision process model and real-world patient information. We will then use this model to identify treatment decisions that are in line with patient- driven goals, including what is best for their quality of life, and approaches that minimize health care cost. Our work will enable patients and their doctors to participate in a shared-decision making process. We will create a web-based tool and assess the feasibility of community urologists helping with gathering patient information and collaboration to optimize patient management (i.e., community versus academic setting).

项目摘要 肾癌或肾细胞癌（RCC）是世界上10种最常见的癌症之一， 美方到2022年，将有超过79，000人被诊断患有RCC。局限性肾肿块（LRM， 局限于肾脏的肿瘤）占所有RCC的三分之二。发现有LRM脸的患者 很多选择，特别是因为这些LRM是良性的并不罕见。 目前有四种方法来管理LRM -主动监视（观察群众，但不 治疗它），热消融（通过从外部将针放入其中来加热肿块），局部消融（局部消融）。 肾切除术（手术切除肿块，但保留肾脏的其余部分），以及根治性手术。 肾切除术（切除整个肾脏的手术）。病人和医生经常被混淆为 选择哪一个，因为以前很少有研究指导他们。目前 建议那些将来可能有问题的患者保留肾脏。 肾功能然而，很难识别这些患者，特别是当他们有其他 健康问题。目前的建议是基于“专家意见”，它通常是左 医生决定什么对病人最好，对肾脏的风险， 癌症比患者可能患有的其它医学病症更威胁患者的生命。 我们研究的主要目标是确定具体的管理计划， 为患有LRM的患者进行个体化。这将使医生和病人更容易决定 最好的方法来管理质量。通过使用一个用真实世界信息构建的工具，“贸易- “关闭”与每个选项（如肾功能）将更清楚的病人，从而帮助他们 最好的决定我们将创建一个基于互联网的数据库， 学术医院我们将收集有关患者健康状况的信息， 肾功能和LRM的细节。我们将评估活检的频率， LRM的治疗以及患者倾向于追求的治疗方法。我们将开发一套 使用马尔可夫决策过程模型和真实世界患者的LRM管理规则 信息.然后，我们将使用该模型来确定符合患者的治疗决策- 驱动的目标，包括对他们的生活质量最有利的方法，以及最大限度地减少健康的方法 护理费用。我们的工作将使患者和他们的医生能够参与共同决策 制作过程。我们将创建一个基于网络的工具，并评估社区的可行性 泌尿科医生帮助收集患者信息和协作，以优化患者 管理（即，社区与学术环境）。