基于治疗前多维度参数的列线图预测小细胞肺癌患者铂类化疗的总生存期  

Nomogram prediction of overall survival in small cell lung cancer patients treated with platinum-based chemotherapy:based on pre-treatment multi-parameter

作　　者：叶若雷 苏燕萍 毛艳菲 张轶虹 张莹[3] 徐艳艳[2] 骆松梅[2] YE Ruolei;SU Yanping;MAO Yanfei;ZHANG Yihong;ZHANG Ying;XU Yanyan;LUO Songmei(College of Pharmacy,Zhejiang Chinese Medical University,Hangzhou 310000,China;Department of Pharmacy,the Fifth Affiliated Hospital of Wenzhou Medical University,Lishui 323000,China;Department of Radiology,the Fifth Affiliated Hospital of Wenzhou Medical University,Lishui 323000,China;Zhejiang Key Laboratory of Imaging Diagnosis and Interventional Minimally invasive Research,the Fifth Affiliated Hospital of Wenzhou Medical University,Lishui 323000,China)

机构地区：[1]浙江中医药大学药学院,浙江杭州310000 [2]温州医科大学附属第五医院药学部,浙江丽水323000 [3]温州医科大学附属第五医院放射科,浙江丽水323000 [4]温州医科大学附属第五医院浙江省影像诊断与介入微创研究重点实验室,浙江丽水323000

出　　处：《温州医科大学学报》2024年第7期589-597,共9页Journal of Wenzhou Medical University

基　　金：浙江省医药卫生科技计划项目(2023KY418);丽水市公益性技术应用研究项目(2023SJZC092)。

摘　　要：目的:探讨基于治疗前多维度参数构建的列线图在预测小细胞肺癌(SCLC)患者铂类化疗总生存期(OS)的应用价值。方法:回顾性分析温州医科大学附属第五医院2014年2月至2023年2月经病理证实为SCLC,且一线治疗方式为规律铂类化疗的患者155例,对入组患者进行电话随访以获取OS。采用7:3比例将所有患者随机分为训练组(n=111)和验证组(n=44)。所有患者治疗前均接受胸部CT平扫及各项血液学检查。采用最小绝对收缩与选择算子(LASSO)回归对各项因素进行特征筛选,而后经单因素及多因素Cox回归分析筛选预测SCLC患者铂类化疗OS的独立预测因素,绘制列线图。绘制时间依赖性受试者工作特征(TimeROC)曲线、时间依赖曲线下面积(TimeAUC)图、校准曲线及决策曲线分析(DCA)评估模型效能和临床价值,Kaplan-Meier曲线分析高、低风险组对患者预后的影响。结果:训练组中,LASSO回归初筛后共得到5个与SCLC铂类化疗预后相关的因素,分别为性别、美国退伍军人肺癌研究组(VALSG)分期、铂敏感性、细胞角蛋白十九片段(Cyfra21-1)、血小板,以上特征经单因素及多因素Cox回归分析显示,均为预测SCLC患者铂类化疗OS的独立预后因素(P<0.05)。构建的列线图模型预测6、12、18个月OS的AUC值分别是训练组0.90(0.82~0.97),0.84(0.73~0.91),0.88(0.83~0.92);验证组0.80(0.66~0.94),0.82(0.69~0.96),0.86(0.72~0.95)。校准曲线显示,列线图预测概率与实际值之间具有较好的一致性,DCA结果表明模型的临床应用价值较高。训练组、验证组的Kaplan-Meier曲线均显示高风险组的患者与较短的总生存期相关(P<0.001)。结论:基于治疗前多维度参数构建的列线图可以为SCLC铂类化疗患者的OS预测提供一定的指导价值。Objective:To investigate the application value of a nomogram constructed based on pre-treatment multi-parameter in predicting the overall survival(OS)of patients with small cell lung cancer(SCLC)undergoing platinum-based chemotherapy.Methods:A retrospective analysis was carried out on a cohort of 155 patients diagnosed with SCLC confirmed through pathology at the Fifth Affiliated Hospital of Wenzhou Medical University from February 2014 to February 2023.These patients received first-line chemotherapy based on platinum compounds.Telephone follow-ups were conducted to gather OS data for the included patients.Patients were randomly divided into a training set(n=111)and a validation set(n=44)at a ratio of 7:3.Prior to treatment,all patients underwent chest CT scans and various hematological examinations.The least absolute shrinkage and selection operator(LASSO)regression was utilized for feature selection among factors.Following this,univariate and multivariate Cox regression analyses were utilized to identify independent predictors predicting OS in patients with SCLC.Subsequently,a nomogram was constructed based on the identified factors.The performance and clinical value of the model were evaluated using time-dependent receiver operating characteristic(Time ROC)curve analysis,Time-dependent AUC curve,calibration curve,and decision curve analysis(DCA).The Kaplan-Meier curve was used to analyze the impact of high versus low-risk groups on patient prognosis.Results:Following LASSO screening in the training set,five features associated with prognosis of SCLC platinum-based chemotherapy were identified:gender,Veterans’Administration Lung Study Group(VALSG)staging,platinum sensitivity,cytokeratin 19 fragment(Cyfra21-1),and platelet count.These features were determined through univariate and multivariate Cox regression analyses to be independent predictors for predicting OS in SCLC patients undergoing platinum-based chemotherapy(P<0.05).The constructed nomogram prediction model demonstrated AUC values for predicting 6,1

关 键 词：小细胞肺癌 生物标记物 铂类化疗 列线图 总生存期 

分 类 号：R734.2[医药卫生—肿瘤]