Comparative-Effectiveness of Pretreatment Lung Cancer Nodal Staging

治疗前肺癌淋巴结分期的比较有效性

• 批准号: 10551866
• 负责人: Farhood Farjah
• 金额: $ 60.06万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-17 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10551866
• 关键词: Address; Adoption; Adverse event; Biopsy; Cancer Patient; Cancer Research Network; Caring; Case Mixes; Characteristics; Classification; Clinical; Data; Databases; Diagnostic; Diagnostic Errors; Disease; Electronic Health Record; Eligibility Determination; Evaluation; Expenditure; Funding; Goals; Guidelines; Health Expenditures; Health Services Accessibility; Hospitals; Image; Infrastructure; Injury; Investigation; Learning; Level of Evidence; Life; Link; Machine Learning; Malignant Neoplasms; Malignant neoplasm of lung; Medical; Modeling; National Cancer Institute; Network Infrastructure; Nodal; Non-Small-Cell Lung Carcinoma; Observational Study; Operative Surgical Procedures; Outcome; Pathologic; Patient Care; Patient Selection; Patient-Focused Outcomes; Patients; Patterns of Care; Pilot Projects; Practice Guidelines; Procedures; Process; Recommendation; Research Design; Risk; Risk Estimate; Selection Criteria; Selection for Treatments; Serious Adverse Event; Site; Specialist; Staging; Survival Rate; Techniques; Testing; Time; Translating; Uncertainty; Unnecessary Surgery; Variant; Vital Status; Work; care costs; chemotherapy; cohort; comparative effectiveness; comparative effectiveness study; cost; data sharing; design; effectiveness evaluation; follow-up; high risk; implementation strategy; improved; lung cancer screening; lymph node biopsy; lymph nodes; models and simulation; neoplasm registry; novel; novel strategies; predictive modeling; radiological imaging; treatment optimization; trial comparing; tumor

ABSTRACT Our goal is to reduce diagnostic and treatment errors, improve survival, and increase the value of care for lung cancer patients by improving our ability to select patients who benefit from a pretreatment lymph node biopsy. Accurately determining whether cancer has spread to lymph nodes and the extent of spread (a process called nodal staging) is critical for appropriate treatment selection. Understaging can lead to omission of chemotherapy or unnecessary surgery. Overstaging can lead to unnecessary chemotherapy and omission of surgery. Diagnostic and treatment errors negatively impact survival. These errors commonly occur when using imaging alone for nodal staging. A biopsy can reduce the chances of error, but it can also result in rare, life- threatening adverse events. Each biopsy costs ~$5,000. Practice guidelines recommend selectively performing a biopsy when imaging findings suggest nodal disease. However, national biopsy rates are less than half of what they should be. Moreover, there is 25-fold facility-level variability not explained by access to care, case- mix, or clinician or facility characteristics. These findings, along with the low levels of evidence underlying guideline recommendations, suggest true clinical and scientific uncertainty over the indications for lymph node biopsy. We conducted a pilot study to better understand how well guideline recommendations select patients for biopsy and learned that guideline-concordant nodal staging selects all patients with true nodal disease for biopsy and two-thirds of patients without true nodal disease for biopsy. Additionally, we developed and validated an alternative risk-based nodal staging strategy that uses a prediction model to stratify and select patients for lymph node biopsy. Preliminary data show that it identifies nearly all patients with true nodal disease for biopsy but selects fewer patients without nodal true nodal disease for biopsy. However, the relationship between selection strategies for lymph node biopsy and patient outcomes remains unknown. We hypothesize that guideline-concordant nodal staging is associated with higher 5-year survival rates compared with guideline-discordant nodal staging (Aim I) and that risk-based nodal staging is equivalent to guideline- concordant nodal staging in terms of survival but superior in terms of lower biopsy-related adverse events and healthcare expenditures (Aim II). Testing these hypotheses will require ~4,000 patients; therefore, a trial is not feasible at this time. We will create a novel cohort of lung cancer patients using the Cancer Research Network infrastructure to conduct Aim I using an observational, comparative-effectiveness study design with advanced regression techniques and machine learning to minimize confounding. Additionally, we will use patient-level data from this cohort as model inputs in a comparative-effectiveness simulation model that we will develop to conduct Aim II. Findings from this study will lead to: 1) developing and testing implementation strategies designed to increase guideline-concordant nodal staging, 2) alternative guideline recommendations for nodal staging, and/or 3) justifying trials comparing outcomes between different nodal staging strategies.

抽象的 我们的目标是减少诊断和治疗错误、提高生存率并提高肺部护理价值 通过提高我们选择受益于治疗前淋巴结活检的患者的能力来治疗癌症患者。 准确确定癌症是否已扩散到淋巴结以及扩散的程度（这一过程称为 淋巴结分期）对于适当的治疗选择至关重要。低估可能会导致遗漏 化疗或不必要的手术。过度分期可能导致不必要的化疗和遗漏 外科手术。诊断和治疗错误会对生存产生负面影响。使用时常出现这些错误 单独成像进行淋巴结分期。活检可以减少出错的机会，但也可能导致罕见的、致命的后果。 威胁性不良事件。每次活检费用约为 5,000 美元。实践指南建议选择性地执行 当影像学结果提示淋巴结疾病时进行活检。然而，全国活检率还不到一半 他们应该是什么。此外，设施水平存在 25 倍的差异，这不能用获得护理、病例的情况来解释。 混合，或临床医生或设施特征。这些发现以及低水平的证据 指南建议，提出淋巴结适应症的真实临床和科学不确定性 活检。我们进行了一项试点研究，以更好地了解指南建议选择患者的效果如何 进行活检，并了解到符合指南的淋巴结分期会选择所有患有真正淋巴结疾病的患者进行活检 活检，三分之二的无真正淋巴结病变的患者进行活检。此外，我们还开发并 验证了另一种基于风险的淋巴结分期策略，该策略使用预测模型来分层和选择 患者进行淋巴结活检。初步数据显示，它可以识别出几乎所有患有真性淋巴结转移的患者 疾病进行活检，但选择较少的无淋巴结真性淋巴结疾病的患者进行活检。然而， 淋巴结活检的选择策略与患者结果之间的关系仍不清楚。我们 假设与指南一致的淋巴结分期与更高的 5 年生存率相关 与指南不一致的淋巴结分期（目标 I），并且基于风险的淋巴结分期相当于指南- 在生存方面一致的淋巴结分期，但在较低的活检相关不良事件和 医疗保健支出（目标 II）。检验这些假设将需要约 4,000 名患者；因此，审判不 此时可行。我们将利用癌症研究网络创建一个新的肺癌患者队列 使用具有先进技术的观察性、比较有效性研究设计来进行目标 I 的基础设施 回归技术和机器学习以尽量减少混淆。此外，我们将使用患者级别 来自该队列的数据作为我们将开发的比较有效性模拟模型的模型输入 进行目标 II。这项研究的结果将导致：1）开发和测试实施策略 旨在增加与指南一致的淋巴结分期，2) 淋巴结的替代指南建议 分期，和/或 3) 比较不同淋巴结分期策略之间结果的论证试验。