Huang Zhangheng, Tong Yuexin, Zhu Lujian, Yang Binbin, Chen Kai, Dai Peiling
Department of Orthopaedics (Spine Surgery), The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Department of Spine Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Front Immunol. 2024 Dec 13;15:1457916. doi: 10.3389/fimmu.2024.1457916. eCollection 2024.
Lung adenocarcinoma patients are often found to have developed bone metastases at the time of initial diagnosis. With the continuous development of technology, we have successfully entered the era of immunotherapy. This study aimed to determine the efficacy of immunotherapy in lung adenocarcinoma patients with bone metastases (LABM) through a multicenter retrospective analysis and to develop a novel tool to identify the population that could benefit most from immunotherapy.
To assess the impact of immunotherapy on LABM in terms of overall survival, we used analytical tools such as Kaplan-Meier analysis, Log-ranch test, and propensity score matching (PSM) method. A predictive model for constructing overall survival was constructed using Cox regression modeling. Based on this, we developed a risk classification system depicting Kaplan-Meier curves for subgroup analysis to determine the optimal beneficiary population for immunotherapy in different risk subgroups.
A total of 20073 eligible patients were enrolled in this study, of whom 8010 did not receive immunotherapy, while 12063 patients received immunotherapy. After 1:1 PSM, 15848 patients were successfully coordinated, yielding a balanced cohort. Kaplan-Meier survival curves showed significantly enhanced overall survival (P < 0.001) in patients who received immunotherapy compared to those who did not. The results of Cox regression analyses showed that age, race, sex, primary site, immunotherapy, surgery, chemotherapy, brain metastasis, liver metastasis, lung metastasis, and marital status were independent prognostic factors. The area under the curve for all three cohorts was close to 0.7, indicating that the model was well-discriminating. The calibration curves further proved that the model had a high predictive accuracy. Decision curve analysis demonstrated that the model could achieve a high net clinical benefit. The risk classification system developed based on the model successfully screened the best beneficiary population for immunotherapy.
This study provides convincing evidence that immunotherapy provides a significant survival advantage for LABM. Secondly, the clinical tools constructed in this study can help clinicians identify the optimal population to benefit from immunotherapy in LABM, thus enabling precise treatment and avoiding the waste of medical resources and over-treatment of patients.
肺腺癌患者在初次诊断时常常已发生骨转移。随着技术的不断发展，我们已成功进入免疫治疗时代。本研究旨在通过多中心回顾性分析确定免疫治疗在肺腺癌骨转移患者（LABM）中的疗效，并开发一种新工具来识别最能从免疫治疗中获益的人群。
为了评估免疫治疗对LABM总生存的影响，我们使用了Kaplan-Meier分析、Log-rank检验和倾向评分匹配（PSM）方法等分析工具。使用Cox回归模型构建总生存预测模型。在此基础上，我们开发了一个风险分类系统，描绘Kaplan-Meier曲线用于亚组分析，以确定不同风险亚组中免疫治疗的最佳受益人群。
本研究共纳入20073例符合条件的患者，其中8010例未接受免疫治疗，12063例患者接受了免疫治疗。经过1:1 PSM后，成功匹配了15848例患者，形成了一个均衡的队列。Kaplan-Meier生存曲线显示，接受免疫治疗的患者与未接受免疫治疗的患者相比，总生存显著提高（P < 0.001）。Cox回归分析结果显示，年龄、种族、性别、原发部位、免疫治疗、手术、化疗、脑转移、肝转移、肺转移和婚姻状况是独立的预后因素。所有三个队列的曲线下面积均接近0.7，表明该模型具有良好的区分度。校准曲线进一步证明该模型具有较高的预测准确性。决策曲线分析表明该模型可实现较高的净临床获益。基于该模型开发的风险分类系统成功筛选出免疫治疗的最佳受益人群。
本研究提供了令人信服的证据，表明免疫治疗为LABM患者提供了显著的生存优势。其次，本研究构建的临床工具可帮助临床医生识别LABM中最能从免疫治疗中获益的最佳人群，从而实现精准治疗，避免医疗资源的浪费和患者的过度治疗。
