Department of Orthopedics, The China-Japan Union Hospital of Jilin University, No 126 Xiantai Street, Changchun, Jilin, 130033, PR China.
Department of Orthopedics, The China-Japan Union Hospital of Jilin University, No 126 Xiantai Street, Changchun, Jilin, 130033, PR China.
Asian J Surg. 2024 Jan;47(1):333-349. doi: 10.1016/j.asjsur.2023.08.198. Epub 2023 Sep 21.
The clinical management of lung cancer (LC) patients with bone metastasis (BM) is still a significant challenge. This study aimed to explore the role of primary tumor resection (PTR) on survival outcome of LC patients with BM and to develop two web-based nomograms for predicting the overall survival (OS) of LC patients with BM who received PTR and those who did not.
We enrolled LC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Propensity score matching (PSM) was then conducted to balance the baseline characteristics of covariates between patients in surgery and non-surgery groups. Next, Kaplan-Meier analysis with log-rank test was performed to evaluate the survival benefit of PTR before and after PSM methods and to explore the impact of surgical resection extent on the prognosis of LC patients with BM and clinical outcomes in patients with different metastatic patterns. Cox proportional hazard regression analysis was then applied to determine the independent prognostic factors for OS of patients receiving PTR and did not receiving PTR, respectively. Subsequently, we constructed two individualized nomograms for predicting the 12-, 18- and 24-months OS. Finally, receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were generated to evaluate discrimination, accuracy and clinical utility of the nomograms.
A total of 7747 eligible patients were included in this analysis. The survival analysis revealed that PTR was closely associated with better survival outcome among LC patients with BM(P < 0.05), while the survival benefit of PTR was suboptimal in patients presented with multiple metastases(P > 0.05). Besides, lobectomy shows best survival benefit. Two nomograms were then constructed based on independent prognostic factors of patients in the surgery group and the non-surgery group. The ROC curves showed good discrimination of the two nomograms, with the area under curve (AUC) of each time point being higher than 0.7 in both the training set and testing set. The calibration curves also demonstrated satisfactory consistency between actual survival and nomogram-predicted OS of both nomograms. The DCA showed high benefit of nomogram in a clinical context. Moreover, the study population was stratified into three groups based on the scores of the nomogram, and the survival analysis showed that this prognostic stratification was statistically significant (p < 0.05).
This study showed that surgical resection of the primary site strategy can prolong survival of LC patients with BM to some extent, depending on different sites of metastasis and highly selected patients. Furthermore, the web-based nomograms showed significant accuracy in predicting OS for patients with or without surgery, which may provide valuable insights for patients' counseling and individualized decision-making for clinicians.
肺癌(LC)伴骨转移(BM)患者的临床管理仍然是一个重大挑战。本研究旨在探讨原发肿瘤切除术(PTR)对 LC 伴 BM 患者生存结局的作用,并为接受 PTR 和未接受 PTR 的 LC 伴 BM 患者建立两种基于网络的总生存期(OS)预测列线图。
我们从 2010 年至 2015 年从监测、流行病学和最终结果(SEER)数据库中招募 LC 伴 BM 患者。然后进行倾向评分匹配(PSM)以平衡手术组和非手术组患者协变量的基线特征。接下来,进行 Kaplan-Meier 分析和对数秩检验,以评估 PTR 前后的生存获益,并探讨手术切除范围对 LC 伴 BM 患者预后和不同转移模式患者临床结局的影响。然后应用 Cox 比例风险回归分析分别确定接受 PTR 和未接受 PTR 的患者 OS 的独立预后因素。随后,我们构建了两种用于预测 12、18 和 24 个月 OS 的个体化列线图。最后,生成接收者操作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)以评估列线图的区分度、准确性和临床实用性。
共纳入 7747 例符合条件的患者。生存分析表明,PTR 与 LC 伴 BM 患者的生存结局密切相关(P<0.05),而在多发转移患者中(P>0.05),PTR 的生存获益并不理想。此外,肺叶切除术显示出最佳的生存获益。然后根据手术组和非手术组患者的独立预后因素分别构建了两种列线图。ROC 曲线显示两个列线图均具有良好的区分度,训练集和测试集的每个时间点的曲线下面积(AUC)均高于 0.7。校准曲线也显示了两个列线图的实际生存与预测 OS 之间的良好一致性。DCA 表明在临床环境中列线图具有较高的获益。此外,根据列线图的得分将研究人群分为三组,生存分析表明这种预后分层具有统计学意义(p<0.05)。
本研究表明,原发肿瘤切除术策略可以在一定程度上延长 LC 伴 BM 患者的生存时间,具体取决于不同的转移部位和高度选择的患者。此外,基于网络的列线图在预测手术或未手术患者的 OS 方面具有显著的准确性,这可能为患者咨询和临床医生的个体化决策提供有价值的见解。