Vanstraelen Stijn, Tan Kay See, Adusumilli Prasad S, Bains Manjit S, Bott Matthew J, Downey Robert J, Gomez Daniel R, Gray Katherine D, Huang James, Isbell James M, Molena Daniela, Park Bernard J, Rimner Andreas, Rusch Valerie W, Shaverdian Narek, Sihag Smita, Wu Abraham J, Jones David R, Rocco Gaetano
Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
Ann Surg. 2024 Oct 1. doi: 10.1097/SLA.0000000000006552.
To generate a prediction model for selection of treatment modality for early-stage non-small cell lung cancer (NSCLC).
Stereotactic body radiotherapy (SBRT) and minimally invasive surgery (MIS) are used in the local treatment of early-stage NSCLC. However, selection of patients for either SBRT or MIS remains challenging, due to the multitude of factors influencing the decision-making process.
We analyzed 1291 patients with clinical stage I NSCLC treated with intended MIS or SBRT from January 2020 to July 2023. A prediction model for selection for SBRT was created based on multivariable logistic regression analysis. The receiver operating characteristic curve analysis stratified the cohort into 3 treatment-related risk categories. Post-procedural outcomes, recurrence and overall survival (OS) were investigated to assess the performance of the model.
In total, 1116 patients underwent MIS and 175 SBRT. The prediction model included age, performance status, previous pulmonary resection, MSK-Frailty score, FEV1 and DLCO, and demonstrated an area-under-the-curve of 0.908 (95%CI, 0.876-0.938). Based on the probability scores (n=1197), patients were stratified into a low-risk (MIS, n=970 and SBRT, n=28), intermediate-risk (MIS, n=96 and SBRT, n=53) and high-risk category (MIS, n=10 and SBRT, n=40). Treatment modality was not associated with OS (HR of SBRT, 1.67 [95%CI: 0.80-3.48]; P=0.20).
Clinical expertise can be translated into a robust predictive model, guiding the selection of stage I NSCLC patients for MIS versus SBRT and effectively categorizing them into three distinct risk groups. Patients in the intermediate category could benefit most from multidisciplinary evaluation.
生成一个用于早期非小细胞肺癌（NSCLC）治疗方式选择的预测模型。
立体定向体部放疗（SBRT）和微创手术（MIS）用于早期NSCLC的局部治疗。然而，由于影响决策过程的因素众多，选择接受SBRT或MIS治疗的患者仍然具有挑战性。
我们分析了2020年1月至2023年7月期间接受意向性MIS或SBRT治疗的1291例临床I期NSCLC患者。基于多变量逻辑回归分析创建了一个SBRT选择预测模型。通过受试者工作特征曲线分析将队列分为3个与治疗相关的风险类别。研究术后结果、复发和总生存期（OS）以评估模型的性能。
共有1116例患者接受了MIS，175例接受了SBRT。预测模型包括年龄、体能状态、既往肺切除术、MSK衰弱评分、第一秒用力呼气容积（FEV1）和一氧化碳弥散量（DLCO），曲线下面积为0.908（95%CI，0.876 - 0.938）。根据概率得分（n = 1197），患者被分为低风险组（MIS，n = 970，SBRT，n = 28）、中风险组（MIS，n = 96，SBRT，n = 53）和高风险组（MIS，n = 10，SBRT，n = 40）。治疗方式与OS无关（SBRT的风险比，1.67 [95%CI：0.80 - 3.48]；P = 0.20）。
临床专业知识可以转化为一个强大的预测模型，指导I期NSCLC患者MIS与SBRT的选择，并有效地将他们分为三个不同的风险组。中间类别的患者可能从多学科评估中获益最大。
