Identifying Subgroups with Localized Kidney Cancer Who Can Defer Surgery

确定可以推迟手术的局限性肾癌亚组

• 批准号: 8112853
• 负责人: Brian L Egleston
• 金额: $ 8.84万
• 依托单位: FOX CHASE CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8112853
• 关键词: Accounting; Aftercare; Blood Vessels; Cancer Etiology; Cerebrum; Cessation of life; Characteristics; Chronic Kidney Failure; Clinical effectiveness; Comorbidity; Data; Databases; Decision Making; Detection; Disease; Goals; Guidelines; Heterogeneity; Incidence; Individual; Intervention; Investigation; Kidney; Knowledge; Life Expectancy; Link; Literature; MRI Scans; Malignant Neoplasms; Medical; Medicare; Methods; Modeling; Nephrectomy; Operative Surgical Procedures; Outcome; Patients; Renal Mass; Renal carcinoma; Research; Risk; Staging; Stratification; Subgroup; Survival Rate; Ultrasonography; Unnecessary Surgery; Work; X-Ray Computed Tomography; arm; base; clinical care; hazard; improved; insight; model development; mortality; novel; older patient; prognostic; tool; tumor

DESCRIPTION (provided by applicant): The incidence of localized kidney cancer has been increasing for the past several decades. Much of this increase is likely due to the detection of small tumors found incidentally after ultrasound, CT scans, or MRI scans ordered for non-kidney cancer related reasons. This suggests two possibilities:1) many tumors that would previously have been found at a later stage are simply being found at earlier stages, and 2) tumors that would never have progressed to a symptomatic or lethal stage are now being found. The possibility that biologically inconsequential small renal masses are now being detected has opened a debate concerning the benefits of active surveillance prior to or in lieu of surgical or other interventions for the treatment of small localized renal masses. Many patients who are treated with surgery will die from other diseases within five years of treatment. The survival benefit of therapy for kidney cancer is hence modest for patients who would die within five years regardless of therapy. Further, there is some evidence that certain treatments might actually worsen survival outcomes in some patients with localized kidney cancer. Radical nephrectomy, for example, has been associated with an increased risk of chronic kidney disease (CKD) compared to partial nephrectomy. Given the debate surrounding the appropriateness of treatment for localized kidney cancer, particularly among older patients and those with comorbidities, better prognostic models are needed to identify who might benefit from active surveillance (also called observation). The goal of this work is to improve prognostic modeling by developing models that can classify individuals according to their underlying hazard of death either with or without treatment. We will apply the models using linked SEER-Medicare data. The importance of accounting for heterogeneity of progression or mortality rates has already been noted in the medical decision making literature. However, such methods often assume that individuals are either rapid or slow disease progressors. This research, in contrast, proposes the development of models that can identify four potential survival rate groups in the investigation of clinical effectiveness: 1) those that have long survival with or without treatment who can therefore be observed, 2) those that have short survival without treatment but long survival with treatment who should hence undergo immediate intervention, 3) those that have long survival without treatment but short survival with treatment who should be observed, and 4) those that have short survival with or without treatment who can avoid unnecessary surgery. Further, we assume that relatively long and short survival hazards can vary between treatment arms. We propose using principal stratification and Rubin's causal model as conceptual tools for this investigation. This project will further knowledge concerning heterogeneity in survival rates among those with localized kidney cancer. PUBLIC HEALTH RELEVANCE: This work will improve prognostic modeling of localized kidney cancer outcomes by developing models that can classify individuals according to their underlying hazard of death either with or without treatment. Those whose life expectancy would not change or would worsen with treatment could be spared surgery.

描述（由申请人提供）：在过去的几十年中，局部肾癌的发生率一直在增加。这种增加的大部分可能是由于在超声检查，CT扫描或MRI扫描后偶然发现的小肿瘤的大部分增加可能引起的，该肿瘤是出于与非基德尼癌症相关的原因而命令的。这表明了两种可能性：1）以前在较晚阶段发现的许多肿瘤只是在较早的阶段发现，而2）现在已经发现了永远不会发展为有症状或致命阶段的肿瘤。现在正在检测到生物学上无关紧要的小肾脏肿块的可能性，就在治疗小型局部肾脏肿块治疗手术或其他干预措施之前或代替了手术或其他干预措施之前的主动监视益处的辩论。许多接受手术治疗的患者会在治疗五年内死于其他疾病。因此，治疗对肾癌的生存益处对于在五年内死亡的患者适度不适用。此外，有一些证据表明，某些疗法实际上可能会使某些局部肾脏癌患者的生存结果恶化。例如，与部分肾切除术相比，自由基肾切除术与慢性肾脏疾病（CKD）的风险增加有关。鉴于围绕局部肾癌治疗的适当性的辩论，尤其是在老年患者和合并症的患者中，需要更好的预后模型来确定谁可以从主动监测中受益（也称为观察）。 这项工作的目的是通过开发可以根据或没有治疗对个人对死亡的潜在危害进行分类的模型来改善预后建模。我们将使用链接的SEER-MEDICARE数据应用模型。在医学决策文献中已经注意到了会计有关进展或死亡率异质性的重要性。但是，这种方法通常假定个体是快速或缓慢的疾病进步者。相反，这项研究提出了可以在临床有效性调查中识别四个潜在的存活率组的模型的发展：1）那些可以观察到的长期生存的人，可以观察到的那些长期生存的人，2）那些在没有治疗的情况下却有短期生存但与治疗长期生存的患者那些可以接受治疗的治疗长期待遇，而在不接受治疗的情况下进行治疗或能够避免的这一疗程很长的人，而他们应该避免使用短期生存，而他们的生存时间则是在那些可以避免的，而他们可以在短期内生存，而他们的生存能力则可以避免。不必要的手术。此外，我们假设相对较长且短暂的生存危害在治疗臂之间会有所不同。我们建议使用主要分层和鲁宾的因果模型作为此研究的概念工具。该项目将进一步了解局部肾癌患者的生存率异质性。 公共卫生相关性：这项工作将通过开发可以根据自己的潜在死亡危害或不接受治疗对个体进行分类的模型来改善局部肾癌结果的预后建模。那些预期寿命不会改变或因治疗而恶化的人可能会保留手术。