| 姜炜,马筑,李青松,等.晚期非小细胞肺癌胸部放疗长期生存患者的临床特征及Nomogram预测模型构建[J].中华放射医学与防护杂志,2023,43(3):189-197.Jiang Wei,Ma Zhu,Li Qingsong,et al.Long-term survival patients with advanced non-small cell lung cancer receiving thoracic radiotherapy: clinical characteristics and the construction of a nomogram prognostic model[J].Chin J Radiol Med Prot,2023,43(3):189-197 |
| 晚期非小细胞肺癌胸部放疗长期生存患者的临床特征及Nomogram预测模型构建 |
| Long-term survival patients with advanced non-small cell lung cancer receiving thoracic radiotherapy: clinical characteristics and the construction of a nomogram prognostic model |
| 投稿时间：2022-12-08 |
| DOI：10.3760/cma.j.cn112271-20221208-00478 |
| 中文关键词: 晚期非小细胞肺癌 放射治疗 Nomogram模型 |
| 英文关键词:Advanced non-small cell lung cancer Radiotherapy Nomogram model |
| 基金项目: |
| 作者 | 单位 | E-mail | | 姜炜 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 马筑 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 李青松 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 耿一超 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 罗大先 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 杨文刚 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 陈霞霞 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 欧阳伟炜 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 胡银祥 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | | | 苏胜发 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | sushengfa2005@163.com | | 卢冰 | 贵州医科大学附属医院 贵州医科大学附属肿瘤医院胸部肿瘤科 贵州医科大学临床医学院肿瘤学教研室, 贵阳 550000 | |
|
| 摘要点击次数: 2957 |
| 全文下载次数: 1302 |
| 中文摘要: |
| 目的 分析晚期非小细胞肺癌（NSCLC）化疗联合原发肿瘤放疗长期生存患者的临床特征，并建立Nomogram预测模型，为晚期NSCLC治疗决策的制定提供一定的参考依据。方法 回顾性分析2003年1月至2012年5月参加两项前瞻性临床研究的260例NSCLC患者作为训练集，2014年1月至2020年8月贵州省医科大学附属肿瘤医院收治的138例NSCLC患者作为验证集。总生存时间（OS）≥18个月定义为长期生存（LTS），比较LTS患者与非LTS患者的临床特征，组间临床特征及治疗相关参数的比较采用χ2检验，logistic回归进行多因素分析，应用RStudio构建列线图模型。结果 训练集患者的中位OS为13.4个月（95%CI：11.9~14.9），1、2和3年的OS率分别为55.4%、19.1%和11.9%。LTS组87例，非LTS组173例。单因素分析显示，KPS评分、T状态、转移器官数、转移病灶数、脑转移、骨转移、化疗周期数、原发肿瘤生物等效剂量（BED）、血红蛋白水平、血小板计数、血浆D-二聚体、纤维蛋白原水平、乳酸脱氢酶及肺免疫预后指数（LIPI）是影响LTS的预测因素（χ2=4.72~12.63，P<0.05）。多因素分析显示，化疗周期数≥4、BED≥70 Gy、血小板≤220×109/L、D-二聚体定量≤0.5 mg/L及良好LIPI评分是LTS的独立预测因素（P=0.002、0.036、0.005、0.008、0.002）。将多因素分析有意义的参数构建列线图模型，训练队列及验证队列一致性指数（C-index，C指数）分别为0.750和0.727。校正曲线分析结果显示，Nomogram模型预测晚期NSCLC胸部放疗长期生存的概率与实际长期生存概率的吻合度高，受试者工作特征曲线（ROC）分析及决策曲线（DCA）分析显示，复合预测模型的效益比单一预测模型的效益更好。结论 化疗周期数、BED、血小板计数、化疗前D-二聚体及LIPI评分是影响晚期NSCLC胸部放疗患者长期生存的独立预测因素，基于这些预后因素构建的Nomogram模型为筛选胸部放疗受益患者提供了便捷、直观且个性化的预测模型。 |
| 英文摘要: |
| Objective To analyze the clinical characteristics of long-term survival patients with advanced non-small cell lung cancer (NSCLC) treated with chemotherapy combined with primary tumor radiotherapy, and to establish a Nomogram prognostic model, aiming to provide a certain reference for making a decision about the treatment of advanced NSCLC.Methods A retrospective analysis was made on the data of 260 NSCLC patients who participated in two prospective clinical studies from January 2003 to May 2012 and the data of 138 NSCLC patients admitted to the Affiliated Cancer Hospital of Guizhou Medical University from January 2014 to August 2020. The former 260 cases were used as a training set and the latter 138 cases were used as the validation set. The overall survival (OS) of ≥ 18 months was defined as long-term survival (LTS). The clinical characteristics of LTS patients were compared with those with OS less than 18 months. The clinical characteristics and treatment-related parameters between the two types of patients were compared using the χ2 test. A multivariate analysis was made using logistic regression, and a nomogram model was built using RStudio.Results The median OS of the training set was 13.4 months (95% CI:11.9-14.9), with 1-, 2-, and 3-year OS rates of 55.4%, 19.1%, and 11.9%, respectively. In the training set, 87 cases had LTS and were classified as the LTS group, while 173 cases had OS less than 18 months and were classified as the non-LTS group. The univariate analysis showed that the prognostic factors affecting LST included the KPS score, T status, the number of metastatic organs, the number of metastatic lesions, brain metastasis, bone metastasis, the number of chemotherapy cycles, the biologically effective dose (BED) to the primary tumor, hemoglobin level, platelet count, plasma D-dimer, fibrinogen level, lactate dehydrogenase, and lung immune prognostic index (LIPI; χ2=4.72-12.63, P < 0.05). The multivariable analysis showed that the independent prognostic factors of LTS included a number of chemotherapy cycles ≥ 4, BED ≥ 70 Gy, platelets ≤ 220×109/L, D-dimer ≤ 0.5 mg/L, and a good LIPI score (P=0.002, 0.036, 0.005, 0.008, and 0.002). A nomogram model was established using the meaningful parameters obtained in the multivariable analysis, determining that the training and validation sets had a consistency index (C-index) of 0.750 and 0.727, respectively. As shown by the analytical result of the corrected curves, for the advanced NSCLC patients treated with thoracic radiotherapy, their LTS probability predicted using the nomogram prognostic model was highly consistent with their actual LTS probability. Both the analytical result of the receiver operating characteristic (ROC) curves and the decision curve analysis (DCA) result showed that the composite prediction model was more beneficial than a single prediction model.Conclusions For patients with advanced NSCLC treated with thoracic radiotherapy, the independent prognostic factors of LTS included the number of chemotherapy cycles, BED, platelet count, pre-chemotherapy D-dimer, and LIPI score. The Nomogram prognostic model built based on these prognostic factors is a convenient, intuitive, and personalized prediction model used to screen patients who can benefit from thoracic radiotherapy. |
| HTML 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
|
|
|