Bone is one of the most common metastatic sites of advanced lung cancer, and the median survival time is significantly shorter than that of patients without metastasis. This study aimed to identify prognostic factors associated with survival and construct a practical nomogram to predict overall survival (OS) in lung cancer patients with bone metastasis (BM).

We extracted the patients with BM from lung cancer between 2011 and 2015 from the Surveillance, Epidemiology, and End Result (SEER) database. Univariate and multivariate Cox regressions were performed to identify independent prognostic factors for OS. The variables screened by multivariate Cox regression analysis were used to construct the prognostic nomogram. The performance of the nomogram was assessed by receiver operating characteristic (ROC) curve, concordance index (C-index), and calibration curves, and decision curve analysis (DCA) was used to assess its clinical applicability.

A total of 7861 patients were included in this study and were randomly divided into training (n=5505) and validation (n=2356) cohorts using R software in a ratio of 7:3. Cox regression analysis showed that age, sex, race, grade, tumor size, histological type, T stage, N stage, surgery, brain metastasis, liver metastasis, chemotherapy and radiotherapy were independent prognostic factors for OS. The C-index was 0.723 (95% CI: 0.697-0.749) in the training cohorts and 0.738 (95% CI: 0.698-0.778) in the validation cohorts. The AUC of both the training cohorts and the validation cohorts at 3-month (0.842 vs 0.859), 6-month (0.793 vs 0.814), and 1-year (0.776 vs 0.788) showed good predictive performance, and the calibration curves also demonstrated the reliability and stability of the model.

The nomogram associated with the prognosis of BM from lung cancer was a reliable and practical tool, which could provide risk assessment and clinical decision-making for individualized treatment of patients.

骨是晚期肺癌最常见的转移部位之一，中位生存时间明显短于无转移患者。本研究旨在确定与生存相关的预后因素，并构建实用的列线图来预测肺癌骨转移 (BM) 患者的总体生存 (OS)。

我们从监测、流行病学和最终结果 (SEER) 数据库中提取了 2011 年至 2015 年期间患有肺癌的 BM 患者。进行单变量和多变量 Cox 回归以确定 OS 的独立预后因素。通过多变量 Cox 回归分析筛选的变量用于构建预后列线图。通过受试者工作特征（ROC）曲线、一致性指数（C-index）和校准曲线评估列线图的性能，并使用决策曲线分析（DCA）评估其临床适用性。

本研究共纳入 7861 名患者，并使用 R 软件以 7:3 的比例随机分为训练组（n=5505）和验证组（n=2356）。Cox回归分析显示，年龄、性别、种族、分级、肿瘤大小、组织学类型、T分期、N分期、手术、脑转移、肝转移、化疗和放疗是OS的独立预后因素。训练组的 C 指数为 0.723（95% CI：0.697-0.749），验证组的 C 指数为 0.738（95% CI：0.698-0.778）。训练队列和验证队列在 3 个月（0.842 对 0.859）、6 个月（0.793 对 0.814）和 1 年（0.776 对 0.788）的 AUC 均显示出良好的预测性能，校准曲线也显示模型的可靠性和稳定性。

与肺癌BM预后相关的列线图是一种可靠实用的工具，可为患者的个体化治疗提供风险评估和临床决策。