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）：在过去的几十年里，局部肾癌的发病率一直在上升。这一增长的很大一部分可能是由于在为非肾癌相关原因而进行的超声、CT扫描或核磁共振扫描后偶然发现的小肿瘤。这表明了两种可能性：1)以前在晚期发现的许多肿瘤只是在早期被发现，2)永远不会发展到有症状或致命阶段的肿瘤现在被发现。生物学上无关紧要的肾小肿块现在被发现的可能性，引发了一场关于在治疗局部肾小肿块之前或代替手术或其他干预措施的积极监测的好处的辩论。许多接受手术治疗的病人会在5年内死于其他疾病。因此，对于那些无论接受何种治疗都会在5年内死亡的患者来说，肾癌治疗的生存益处是有限的。此外，有证据表明，某些治疗方法实际上可能会使一些局部肾癌患者的生存结果恶化。例如，与部分肾切除术相比，根治性肾切除术与慢性肾脏疾病（CKD）的风险增加有关。考虑到围绕局部肾癌治疗的适宜性的争论，特别是在老年患者和有合并症的患者中，需要更好的预后模型来确定谁可能从主动监测（也称为观察）中受益。这项工作的目标是通过开发模型来改进预后建模，这些模型可以根据患者接受或不接受治疗的潜在死亡风险对个体进行分类。我们将使用关联的SEER-Medicare数据应用模型。在医疗决策文献中已经注意到考虑进展或死亡率异质性的重要性。然而，这些方法通常假设个体是快速或缓慢的疾病进展者。相比之下，本研究提出了开发模型，可以在临床疗效调查中确定四种潜在存活率组：1)无论治疗与否生存时间较长的患者，因此可以观察；2)不治疗生存时间较短但治疗后生存时间较长，因此应该立即进行干预；3)不治疗生存时间较长但治疗后生存时间较短的患者，应该观察；4)无论治疗与否生存时间较短的患者，可以避免不必要的手术。此外，我们假设在不同的治疗组中，相对较长和较短的生存风险是不同的。我们建议使用主要分层和鲁宾的因果模型作为本研究的概念工具。该项目将进一步了解局部肾癌患者生存率的异质性。