National Longitudinal Outcomes Following Surgical Therapy for Lung Cancer

描述（由申请人提供）：肺癌是美国癌症死亡率的主要原因。早期肺癌可以通过手术治愈，更多的早期肿瘤有望通过筛查项目被发现。微创方法（视频辅助胸外科手术，VATS）和有限的肺切除术（sublobar）技术可以降低肺癌手术的手术发病率，使更多的患者接受手术。然而，重要的问题仍然是关于这些手术策略的癌症切除的完整性，因此，生存结果。这是将肺癌患者与最佳手术治疗相匹配的关键障碍。胸外科医师协会（STS）的长期目标是提高肺癌外科治疗的质量。STS普通胸外科数据库（GTSD）捕获了在任何其他癌症数据库中找不到的独特患者水平的临床细节。然而，STS GTSD不提供纵向结果数据，这一限制可以通过与医疗保险和医疗补助服务中心（CMS）数据的联系来克服。我们的目标是确定肺癌切除术后长期预后的预测因素，包括手术入路和切除范围的最佳策略。我们假设：1）肺癌手术后的长期生存率根据个体患者的临床和治疗变量而变化，2）与更具侵入性的方法（开胸术）和标准切除术（肺叶切除术）相比，VATS方法和肺叶切除术与长期生存率较低无关，[3] VATS方法和肺叶切除术与标准开胸术和肺叶切除术相比具有更有利的经济结局。]本研究的基本原理是，了解风险调整后的长期结局将有助于为肺癌患者选择最佳治疗。我们的假设将通过追求三个具体目标进行测试：1）建立肺癌切除术后长期生存的风险模型。2)根据手术入路、VATS与开胸术、切除范围、肺叶切除与肺叶切除，比较早期肺癌的生存率。[3)根据早期肺癌的手术方式和切除程度比较资源使用和成本。在目标1中，已建立的算法将GTSD与CMS数据联系起来，以创建肺癌切除术后长期生存的风险模型。在目标2下，将通过倾向性分析比较VATS入路和肺叶切除术与开胸入路和肺叶切除术的长期生存率。[最后，根据目标3，将分别与开胸手术和肺叶切除术比较VATS和肺叶切除术相关的成本和资源使用。]这项研究是创新的，因为GTSD与CMS数据的联系将创建一个纵向数据源，特别适合肺癌手术的比较有效性研究。 这一贡献将是显著的，因为最有效的手术策略将根据个体患者的特征来确定。这些发现将由STS在国内和国际上传播，以推动肺癌护理的质量改善。

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer mortality in the US. Early stage lung cancer can be cured with surgery, and more early stage tumors are expected to be detected with screening programs. Minimally invasive approaches (video assisted thoracic surgery, VATS) and limited pulmonary resection (sublobar) techniques can reduce procedural morbidity for lung cancer surgery, allowing more patients to have surgery. However, important questions remain about the completeness of cancer removal with these surgical strategies and, therefore, survival outcomes. This represents a critical barrier to matching lung cancer patients with the optimal surgical treatment. A long term goal of The Society of Thoracic Surgeons (STS) is to improve quality of surgical therapy for lung cancer. The STS General Thoracic Surgery Database (GTSD) captures unique patient-level clinical detail not found in any other cancer database. However, the STS GTSD does not provide longitudinal outcomes data, a limitation that can be overcome by linkage to Centers for Medicare and Medicaid Services (CMS) data. Our objective is to identify predictors of long-term outcomes following lung cancer resection, including the optimal strategies with respect to surgical approach and extent of resection. We hypothesize that: 1) long-term survival following lung cancer surgery varies according to individual patient clinical and treatment variables, 2) VATS approaches and sublobar resections are not associated with inferior long-term survival compared to more invasive approaches (thoracotomy), and standard resections (lobectomy), and [3) VATS approaches and sublobar resections are associated with more favorable economic outcomes than standard thoracotomy and lobectomy.] The rationale of this research is that knowledge of risk-adjusted long-term out- comes will facilitate selection of optimal therapy for patients with lung cancer. Our hypotheses will be tested by pursuing three specific aims: 1) Create a risk model for long-term survival following lung cancer resection. 2) Compare survival based on surgical approach, VATS vs. thoracotomy, and extent of resection, sublobar resection vs. lobectomy, for early stage lung cancer. [3) Compare resource use and costs according to surgical approach and extent of resection for early stage lung cancer.] In Aim 1, established algorithms will link the GTSD with CMS data to create a risk model for long-term survival following lung cancer resection. Under Aim 2, VATS approaches and sublobar resections will be compared to thoracotomy approaches and lobectomies with respect to long-term survival with propensity analyses. [Lastly, under Aim 3, costs and resource use associated with VATS and sublobar resections will be compared with thoracotomy and lobectomy, respectively.] This re- search is innovative because linkage of the GTSD with CMS data will create a longitudinal data source uniquely suited for comparative effectiveness studies in lung cancer surgery. The contribution will be significant, as the most effective surgical strategies wil be determined based on individual patient characteristics. These findings will be disseminated by STS nationally and internationally to drive quality improvement in lung cancer care.