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老年肝细胞癌患者总生存期的影响因素及预后列线图预测模型构建:一项基于人群的研究

伍杨, 李甜, 史婷婷, 朱玲玲, 张亚妮, 郭佩佩, 张润兵, 王顺娜, 高春, 于晓辉, 张久聪

伍杨, 李甜, 史婷婷, 朱玲玲, 张亚妮, 郭佩佩, 张润兵, 王顺娜, 高春, 于晓辉, 张久聪. 老年肝细胞癌患者总生存期的影响因素及预后列线图预测模型构建:一项基于人群的研究[J]. 肿瘤防治研究, 2024, 51(9): 756-763. DOI: 10.3971/j.issn.1000-8578.2024.24.0009
引用本文: 伍杨, 李甜, 史婷婷, 朱玲玲, 张亚妮, 郭佩佩, 张润兵, 王顺娜, 高春, 于晓辉, 张久聪. 老年肝细胞癌患者总生存期的影响因素及预后列线图预测模型构建:一项基于人群的研究[J]. 肿瘤防治研究, 2024, 51(9): 756-763. DOI: 10.3971/j.issn.1000-8578.2024.24.0009
WU Yang, LI Tian, SHI Tingting, ZHU Lingling, ZHANG Yani, GUO Peipei, ZHANG Runbing, WANG Shunna, GAO Chun, YU Xiaohui, ZHANG Jiucong. Influencing Factors of Overall Survival of Elderly Patients with Hepatocellular Carcinoma and Construction of Prediction Model of Prognosis Nomogram: A Population-Based Study[J]. Cancer Research on Prevention and Treatment, 2024, 51(9): 756-763. DOI: 10.3971/j.issn.1000-8578.2024.24.0009
Citation: WU Yang, LI Tian, SHI Tingting, ZHU Lingling, ZHANG Yani, GUO Peipei, ZHANG Runbing, WANG Shunna, GAO Chun, YU Xiaohui, ZHANG Jiucong. Influencing Factors of Overall Survival of Elderly Patients with Hepatocellular Carcinoma and Construction of Prediction Model of Prognosis Nomogram: A Population-Based Study[J]. Cancer Research on Prevention and Treatment, 2024, 51(9): 756-763. DOI: 10.3971/j.issn.1000-8578.2024.24.0009

老年肝细胞癌患者总生存期的影响因素及预后列线图预测模型构建:一项基于人群的研究

基金项目: 甘肃省青年科技基金(23JRRA1673);联勤保障部队第九四〇医院拔尖项目(2021yxky002);中央高校优秀青年团队培育项目(31920220065);兰州市青年科技人才创新重点项目(2023-2-29)
详细信息
    作者简介:

    伍杨(1998-),男,硕士在读,主要从事消化性疾病及感染性疾病的基础和临床研究,ORCID: 0009-0008-3863-4996

    通讯作者:

    张久聪(1985-),男,博士,副教授,主要从事消化性疾病及感染性疾病的基础和临床研究,E-mail: zhangjiucong@163.com,ORCID: 0000-0003-4006-3033

  • 中图分类号: R735.7

Influencing Factors of Overall Survival of Elderly Patients with Hepatocellular Carcinoma and Construction of Prediction Model of Prognosis Nomogram: A Population-Based Study

Funding: Gansu Youth Science and Technological Fund (No. 23JRRA1673); Top-notch Project of the 940th Hospital of the Joint Logistics Support Force (No. 2021yxky002); Central University Excellent Youth Team Training Project (No. 31920220065); Key Innovation Project of Young Scientific and Technological Talents in Lanzhou (No. 2023-2-29)
More Information
  • 摘要:
    目的 

    探讨影响老年(≥60岁)肝细胞癌(HCC)患者总生存期(OS)的独立危险因素并构建列线图预测模型。

    方法 

    从SEER数据库下载2005—2020年所有老年HCC患者的临床数据。根据纳排标准,将筛选后的患者随机分为训练组(70%)和验证组(30%),单因素和多因素Cox回归分析确定老年HCC患者独立危险因素并用Kaplan-Meier生存分析进一步验证。基于确定的变量,开发并验证列线图,以预测老年HCC患者6、12和24个月的OS。使用一致性指数(C指数)、校准曲线、受试者工作特征(ROC)曲线和曲线下面积(AUC)来评价预测模型的预测效率和区分能力,采用决策曲线分析(DCA)评估列线图的临床潜在应用价值。

    结果 

    本研究最终纳入1134例老年HCC患者,训练组793例,验证组341例。年龄、临床分级、临床分期、M分期、肿瘤大小分型和放射治疗被确定为该人群的独立预后因素。构建出的列线图表现出优异的预测性能,训练组的C指数为0.745,验证组的C指数为0.704。训练组在6、12和24个月时的AUC值分别为0.785、0.788和0.798,验证组分别为0.780、0.725和0.607。从预测的生存概率到实际观测,校准曲线表现出良好的一致性。ROC曲线和DCA显示本研究提出的列线图具有较好的预测能力。

    结论 

    年龄、临床分级、临床分期、M分期、肿瘤大小分型和放疗情况均是老年HCC患者生存的重要影响因素。本研究构建的预后列线图预测模型具有良好的预测价值,可用于预测老年HCC患者OS,这将有助于老年HCC患者的个性化生存评估和临床管理。

     

    Abstract:
    Objective 

    To explore the independent risk factors that affect the overall survival (OS) of elderly patients with hepatocellular carcinoma (HCC, ≥60 years old) and build a nomogram prediction model.

    Methods 

    Clinical data of all elderly patients with HCC from the SEER database from 2005 to 2020 were downloaded from SEER database. In accordance with the inclusion and exclusion criteria, the screened patients were randomly assigned to a training group (70%) and a validation group (30%). The independent risk factors of elderly patients with HCC were determined by univariate and multivariate Cox regression analyses and further validated by Kaplan-Meier survival analysis. On the basis of the determined variables, nomograms were developed and verified to predict the OS of elderly patients with HCC at 6, 12, and 24 months. The consistency index (C index), calibration curve, receiver’s operating characteristic (ROC) curve, and area under curve (AUC) were used to evaluate the prediction efficiency and discrimination ability of the prediction model, and decision curve analysis (DCA) was used to evaluate the potential clinical application value of the nomogram.

    Results 

    A total of 1134 elderly patients with HCC were included, with 793 in the training group and 341 in the validation group. Seven variables, including age, clinical grade, clinical stage, M stage, tumor size classification, and radiotherapy, were identified as independent prognostic factors of this population. The constructed nomogram shows excellent prediction performance, with C indices of 0.745 in the training group and 0.704 in the validation group. The AUC values of the training group at 6, 12, and 24 months were 0.785, 0.788, and 0.798, respectively, and those of the validation group were 0.780, 0.725, and 0.607, respectively. The calibration curve shows good consistency from the predicted survival probability to the actual probability. The ROC curve and DCA show that the nomogram proposed in this study has good prediction ability.

    Conclusion 

    Age, clinical grade, clinical stage, M stage, tumor size classification, and radiotherapy are important influencing factors for the survival of elderly patients with HCC. The prediction model of prognosis nomogram constructed in this study has good predictive value, and it can be used to predict the OS of elderly patients with HCC, which could be helpful for individualized survival assessment and clinical management of these patients.

     

  • 结直肠肿瘤(colorectal cancer, CRC)是消化道常见的恶性肿瘤之一,其发病率和死亡率分别位列全球恶性肿瘤的第3位和第2位[1]。结直肠癌早期患者多无自觉症状,临床表现不典型,患者的生存期与诊断时疾病的分期密切相关。因此,筛选一种有效的结直肠癌的早期诊断标志物,对延长患者生存期具有重要的意义[2]。环状RNA(circRNAs)是一种新型的非编码RNA分子,它不存在3’端和5’端,直接由外显子、内含子或两者共存,反向剪切,形成一个共价闭合的连续环状结构。circRNA在外泌体和血浆中含量丰富且稳定,检测方便,且在真核生物转录组中具有组织特异性,能够对基因转录进行调控[3]。同时,有研究报道,circRNA可以与具有生物学功能的蛋白质结合进而影响细胞的生物学活性[4],并作为分子支架使得多种生物分子趋化,形成多元复合物,在细胞活动中发挥作用[5]

    多种多样的生物学功能使circRNA可以成为一种新的诊断生物标志物和基因治疗的靶点,研究显示circRNA在多种疾病中均发挥重要作用,如乳腺癌、大肠癌、神经胶质瘤等[6-8]。前期工作中,我们通过基因芯片分析了在结直肠癌和邻近正常组织中的特征性表达情况,共有13 198个环状RNA,其中6 697个基因上调,6 501个基因下调[9]。而本研究旨在探讨hsa_circ_0018574在结肠癌组织中的表达及其对肿瘤细胞周期、增殖和凋亡的影响,为circRNA在结直肠肿瘤发生、发展机制提供数据支持。

    收集2017年6月—2018年8月在宁夏医科大学总医院结直肠外科确诊为结直肠癌的50例患者术后癌组织和癌旁组织标本。纳入标准:(1)无肿瘤病史;(2)结直肠癌组织样本病理诊断明确;(3)无艾滋病毒感染;(4)行结直肠癌肿瘤切除术;(5)收集标本前均无放疗或化疗史;(6)临床信息完整。排除标准:(1)既往腹部手术者;(2)伴有远处转移与肠梗阻者。结直肠癌组织样本储存于液氮中。所有患者在取样前都签署知情同意书,本研究已获得宁夏医科大学总医院伦理委员会的批准。

    患者组织样本总RNA的分离提取按TRIzol试剂(美国Invitrogen公司)说明书进行,NanoDrop2000分光光度计(美国Thermo Fisher Scientific公司)测定RNA的纯度和浓度,OD260/280比值为1.9~2.0。用1%甲醛变性凝胶电泳检测RNA完整性;将提取的总RNA通过反转录试剂盒(美国Thermo Fisher Scientific公司)合成cDNA,反转录体系为:1 μl总RNA(约500 ng),1 μl random primer,10 μl ddH2O,2 μl dNTP,4 μl反转录buffer,1 μl RNA酶抑制剂,1 μl反转录酶,总体积20 μl;反应条件为:25℃ 5 min,42℃ 60 min,70℃ 5 min。RNA及cDNA置于-80℃贮存备用。

    选取四对结直肠癌和癌旁组织样品RNA,利用人circRNA表达谱芯片(Human cirRNA array version 2.0,北京博奥生物有限公司)检测样品中circRNA的表达情况,该芯片包含162 351条环状RNA探针。芯片结果数据应用Feature Extraction软件(北京博奥生物有限公司)提取,采用Cluster 3.0软件进行聚类分析,GeneSpring13.0(安捷伦科技有限公司)分析差异倍数(fold change,FC)、荧光值等。初步过滤和质控去除检测结果中不达标部分,剩余数据进行筛选,筛选条件:FC≥2,P < 0.01,荧光信号值≥100。

    采用TB Green qPCR MasterMix(TaKaRa,日本)于LightCycler®480实时PCR平台进行RT-qPCR,GAPDH的表达为内参对照。引物由生工生物工程(上海)有限公司合成,hsa_circ_0018574(正向引物:5’-ACAGAAATACAGG CCGAGGAGT-3’;反向引物:5’-TGTCCGTGCCTGTGCAATTA-3’)。RT-qPCR反应的总体积为20 μl系统,每孔加入上下游引物各0.8 μl(引物浓度为10 μmol/L),TB Green qPCR MasterMix 10 μl,cDNA 2 μl,6.4 μl双蒸馏水。RT-qPCR反应条件:95℃ 30 s,95℃ 15 s,60℃ 15 s,40个循环,60℃ 2 min,收集荧光信号。基因的相对表达量采用2-ΔΔCT法进行计算。

    人结肠癌HT-29细胞由中国科学院细胞库提供,RPMI1640培养基、FBS和青/链霉素均购自美国Gibco公司,TRIzol试剂和转染试剂Lipofectamine TM2000均购自美国Invitrogen公司,将HT-29细胞接种至6孔板,待细胞贴壁12 h后,用脂质体2000将si-circ_0018574质粒转染至细胞中,使用RT-qPCR检测HT-29细胞中circ_0018574表达水平。

    取HT29细胞,按600个/孔分别接种于12孔板中,放入37℃、5%CO2细胞培养箱中,3~5 d换液,培养10~15 d后弃去培养液,PBS清洗后结晶紫染色,流水冲洗后晾干,拍照计数。

    将转染后的HT-29细胞培养至对数期,按照每孔1×105个细胞接种于6孔板内。分为未转染细胞的空白对照组(control)、空载体阴性对照组(si-NC)和hsa_circ_0018574沉默组(si-circ_0018574)。在细胞培养孔内加入100 μl细胞裂解液,在冰上反应裂解30 min,使用细胞刮板收集裂解细胞。在12 000 r/min,4℃条件下离心10 min,上清液即为蛋白样本。BCA蛋白定量试剂盒检测蛋白浓度,super block调整蛋白浓度,取20 μg蛋白进行SDS-PAGE(120 g/L电泳凝胶),80 V反应40 min,120 V反应2.5 h。完成电泳后,湿转仪将凝胶上蛋白转印至PVDF膜(200 mA 1.5 h),super block封闭1 h。封闭后的PVDF膜分别加1:1 000稀释的抗体:兔抗CDK2抗体、兔抗CDK4抗体、兔抗CDK6抗体、兔抗cyclinD1抗体和兔抗cyclinE抗体(美国Abcam公司)。20 r/min平板摇床4℃孵育过夜;TBST清洗3次,每次10 min,加入HRP标记的山羊抗兔IgG(1:10 000),平板摇床室温孵育1 h;TBST清洗后,ECL发光检测,使用蛋白成像系统曝光,观察条带,以β-actin蛋白为内参蛋白观察相对表达。

    采用MUSETM Caspase-3/7试剂盒(密理博)检测细胞凋亡,收集1×106个细胞,取50 μl细胞悬液加入5 μl caspase-3/7工作液37℃培养30 min,然后加入150 μl 7-AAD工作液(武汉,普诺赛生命科技有限公司)充分混匀后上机检测。

    采用Cluster3.0软件进行聚类分析生成聚类图,火山图采用ggPlot2软件(R)进行分析。circRNA引物由circPrimer1.2软件设计。所有数据采用SPSS23.0软件进行统计学分析,数据以均数±标准差(x±s)表示,每个circRNA的实验组与对照组之间差异倍数筛选,差异表达基因采用单因素方差分析或ANOVA。ROC曲线采用SPSS23.0软件绘制,当AUC=0.5时,circRNA被定义为无诊断价值。检验水准为α= 0.05。

    circbaseID: hsa_circ_0018574,来源基因DDX21,染色体位置:chr10:70723046-70741337+,全长1 475 bp,该circRNA跨DDX21基因的4-14号外显子环化而成。引物设计必须要跨环化位点,hsa_circ_0018574(Forward: 5’-ACAGAAATACAGG CCGAGGAGT-3’;Reverse: 5’-TGTCCGTGCCTGTGCAATTA-3’)引物特异性高,跨越环化接头,见图 1

    图  1  hsa_circ_0018574的序列结构示意图
    Figure  1  Sequence structure diagram of hsa_circ_0018574

    环状RNA的siRNA设计原则:使siRNA序列跨过环状RNA的反向连接位点,首先让反向连接位点置于siRNA序列中间,降低siRNA的脱靶效应,然后将设计好的正义链和反义链通过化学方法合成,同时在siRNA的3’端添加两个TT脱氧核糖核苷酸,呈单链悬挂结构,增强siRNA序列的在体内和体外的稳定性,防止siRNA序列发生降解。本身siRNA是跨circRNA反向链接位点设计的,siRNA转染细胞后又做了定量分析确定hsa_circ_0018574表达量降低了,这就证明我们设计的siRNA就是针对hsa_circ_0018574,排除作用于其他mRNA。

    本研究共收集了4例结直肠癌患者的肿瘤组织(C1-C4)和相邻癌旁正常组织(N1-N4)进行测序分析,通过微阵列基因芯片对这4对结直肠癌患者肿瘤组织及癌旁正常组织进行表达谱芯片分析。获得差异表达的circRNA,其中高表达6 697个,低表达6 501个,见图 2A。按照差异倍数(FC值)≥5和P < 0.01,筛选5个表达上调,5个表达下调的circRNA,筛选确定hsa_circ_0018574,见图 2B。通过RT-qPCR在50对结直肠癌及癌旁组织中验证发现,hsa_circ_0018574在结直肠癌组织中显著上调(P < 0.01),见图 2C

    图  2  微阵列分析hsa_circ_0018574在结肠癌组织中的表达
    Figure  2  Microarray assay of hsa_circ_0018574 expression in CRC tissues
    A: volcano diagram, Y-axis: -log10 (P value), X-axis: log2 (FC: multiple of difference), where red, green, and black represent the up-regulation gene, down-regulation gene, and the gene with no significant difference, respectively; B: clustering diagram: red and green represent high and low expressions, respectively (C1–C4: colorectal cancer tissues, N1–N4: adjacent normal tissues); C. the expression of hsa_circ_0018574 in CRC tissues by RT-qPCR. ***: P < 0.01.

    转染si-circ_0018574 48 h后,与Control组、si-NC组相比,实验组(si-circ_0018574组)在转染si-circ_0018574后,HT29细胞内circRNA_0018574的表达水平明显降低(P < 0.01),见图 3

    图  3  转染si-circ_0018574后结肠肿瘤细胞中circRNA_0018574的表达
    ***: P < 0.01.
    Figure  3  The expression level of circRNA_0018574 after si-circ_0018574 transfection

    结果显示,与si-NC组相比,沉默circRNA_0018574结肠癌细胞增殖和集落形成能力明显降低,差异有统计学意义(P < 0.01),见图 4

    图  4  平板克隆实验观察si-circ_0018574转染后HT29细胞集落形成能力
    ***: P < 0.01.
    Figure  4  Colony formation assay to observe the colony forming ability of HT29 cells after transfection of si-circ_0018574

    Western blot结果显示,si-circ_0018574组的CDK2、CDK4、CDK6以及cyclinD1、cyclinE周期蛋白较si-NC组显著下调(均P < 0.01),见图 5

    图  5  Western blot法检测si-circ_0018574对HT29细胞周期相关蛋白表达的影响
    ***: P < 0.01.
    Figure  5  The expression of HT29 cells cycle-associated proteins after transfection of si-circ_0018574 was detected by Western blot analysis

    流式细胞术细胞凋亡实验表示,CASPASE-3/7是促进细胞凋亡的因子,而与阴性对照组si-NC相比,转染si-circ_0018574后的人结肠癌HT29细胞凋亡加速,差异有统计学意义(P < 0.01),见图 6

    图  6  流式细胞术观察转染si-circ_0018574后HT29细胞凋亡情况
    ***: P < 0.01.
    Figure  6  Flow cytometry assay to observe the apoptosis of HT29 cells after transfection of si-circ_0018574

    结肠癌是全球范围内常见恶性肿瘤之一,具有发病率高及早期症状隐匿等特点。肿瘤的发生、发展涉及多基因介导和多酶促反应参与的复杂生物学调控机制。既往研究显示,癌基因的激活或抑癌基因表达的降低、失活均可增强肿瘤恶性进展,如促进癌细胞增殖及转移等[10]。结肠癌诊疗技术(手术切除联合放、化疗)虽在不断进步和完善,但患者预后仍较差。因此,探寻结肠癌新型生物治疗靶标,尤其对于早期筛查结直肠癌患者是当前临床研究攻克的重点。

    circRNA为单链共价环状结构,这种封闭环形结构使其具有独特的稳定性、进化保守性、多样性以及在不同组织、生长阶段中的特异性。有研究发现,许多circRNA参与结直肠癌的发生、发展、侵袭与转移[11]。例如,circDDX17在结直肠癌组织中明显下调,并与不良的临床病理参数有关[12]。miR-876-5p可以识别circRNA CDR1as,其作为miR-876-5p的“海绵”,反向负调控CDR1as在肝癌中的表达和功能,抑制肝癌细胞的增殖、迁移和侵袭[13]。随着生命科学技术的不断进步,circRNA越来越多的功能被不断挖掘出来。目前,已发现circRNA的表达谱与结直肠癌患者的临床病理学特征有关,如组织分化、TNM分类和远处转移等[14];circRNA的差异表达也通过肿瘤相关信号通路调节结直肠癌细胞的增殖和进展[15];由于circRNA不易被核酸酶降解,具有保守性高、细胞内稳定性高的特点,为其作为诊断癌症的理想生物标志物奠定了基础[16]

    本研究采用circRNA表达谱芯片技术检测在结直肠肿瘤组织和癌旁组织标本中差异表达的circRNA,该芯片包含13 198条环状RNA探针,经过微阵列基因芯片筛选,确定hsa_circ_0018574为研究目标。对结直肠肿瘤组织及癌旁正常组织进行表达谱芯片分析和RT-qPCR结果显示,hsa_circ_0018574在人结直肠肿瘤组织中的表达明显高于癌旁组织。

    在确定circ_0018574在结直肠癌中的保守性和稳定性,并对其在结直肠癌中的功能进行预测后,本研究进一步通过circ_0018574沉默技术研究其对人结直肠癌HT29细胞增殖、周期及凋亡的影响。平板克隆法实验结果表明,将si-circ_0018574和空载体转染至HT29细胞中,si-circ_0018574能够明显抑制人结肠癌HT29细胞的增殖能力和克隆形成能力。细胞周期停滞与许多细胞周期调节蛋白和细胞周期相关激酶的表达有关。之前有研究表明,细胞依赖性激酶(cyclin dependent kinases, CDKs)CDK2、CDK4和CDK6是细胞由G1期转入S期的重要调节因子,而且cyclinD和cyclinE通过结合CDK4和CDK6,进而调节其活性,调控细胞周期进展[17-18]。本实验结果显示,转染si-circ_0018574后,人结肠癌HT29细胞中CDK2、CDK4、CDK6以及cyclinD1和cyclinE周期蛋白表达明显降低。提示干扰circRNA_0018574可延长细胞周期的S期,阻滞于G1/S期,抑制纺锤体形成,以减少细胞分裂,进而抑制结直肠癌细胞的增殖作用。Caspase在凋亡信号的作用下首先激活启动型Caspase引发Caspase级联反应,然后通过活化的Caspase裂解底物导致细胞凋亡[19-20]。MUSE DEVD caspase-3/7试剂含一种DNA结合染料,该染料与DEVD肽底物相连,当它与DEVD结合时,染料不能结合DNA。活性Caspase-3/7在细胞内的裂解导致染料释放,移位到细胞核,染料与DNA结合,并表现出高荧光。当观察到Caspase-3/7参数的荧光增加时,很容易获得细胞中存在活性Caspase-3/7的信息。在流式细胞术细胞凋亡实验中,转染si-circ_0018574后可以促进人结肠癌HT29细胞凋亡,通过抑制其表达可延缓肿瘤的发展。

    综上所述,has-circ_0018574在结直肠肿瘤患者组织和细胞中高表达,si-circ_0018574能够显著抑制人结肠癌HT29细胞增殖和克隆形成能力,将HT29细胞阻滞于G1/S期,减少细胞分裂,促进细胞凋亡。这些结果为结直肠肿瘤的早期诊断、治疗及预后评估提供新的证据,但has_circ_0018574在结直肠肿瘤中的靶基因及调节机制尚不清楚,仍需要进一步深入研究。

    Competing interests: The authors declare that they have no competing interests.
    利益冲突声明:
    所有作者均声明不存在利益冲突。
    作者贡献:
    伍 杨:软件分析、文章撰写与修改
    李甜、史婷婷、朱玲玲:收集整理数据
    张亚妮、郭佩佩、张润兵:检索文献
    王顺娜、高春:文章校对与修改
    于晓辉、张久聪:指导写作、提供基金支持
  • 图  1   老年肝细胞癌患者的Kaplan-Meier生存曲线

    Figure  1   Kaplan-Meier survival curves of elderly patients with hepatocellular carcinoma

    图  2   老年肝细胞癌患者6、12和24个月总生存期的预测列线图

    Figure  2   Predictive nomogram of overall survival of elderly patients with hepatocellular carcinoma at 6, 12, and 24 months

    图  3   训练组(A~C)和验证组(D~F)6、12和24个月的ROC曲线图

    Figure  3   ROC curves of training set (A-C) and validation set (D-F) at 6, 12, and 24 months

    图  4   训练组(A~C)和验证组(D~F)6、12和24个月的OS校准曲线

    Figure  4   OS calibration curves of training set (A-C) and validation set (D-F) at 6, 12, and 24 months

    图  5   训练组(A~C)和验证组(D~F)6、12和24个月的DCA曲线

    Figure  5   DCA curves of training set (A-C) and validation set (D-F) at 6, 12, and 24 months

    表  1   老年肝细胞癌患者训练组和验证组的临床病理特征[n (%)]

    Table  1   Clinicopathological characteristics of elderly patients with hepatocellular carcinoma in training set and validation set (n (%))

    Total (n=1134) Training set (n=793) Validation set (n=341) χ2 P
    Age(years) 11.916 0.036
    60-64 254(22.4) 162(20.43) 92(26.98)
    65-69 274(24.16) 205(25.85) 69(20.23)
    70-74 243(21.43) 168(21.19) 75(21.99)
    75-79 169(14.9) 125(15.76) 44(12.90)
    80-84 118(10.41) 86(10.84) 32(9.38)
    >84 76(6.7) 47(5.93) 29(8.50)
    Ethnicity 0.057 0.972
    Black 135(11.9) 95(11.98) 40(11.73)
    White 836(73.72) 583(73.52) 253(74.19)
    Others 163(14.37) 115(14.50) 48(14.08)
    Gender 0.821 0.365
    Female 276(24.34) 187(23.58) 89(26.10)
    Male 858(75.66) 606(76.42) 252(73.90)
    Single status 0.240 0.624
    No 656(57.85) 455(57.38) 201(58.94)
    Yes 478(42.15) 338(42.62) 140(41.06)
    Clinical grade 0.847
    323(28.48) 227(28.63) 96(28.15)
    614(54.14) 429(54.10) 185(54.25)
    193(17.02) 135(17.02) 58(17.01)
    4(0.35) 2(0.25) 2(0.59)
    Clinical stage 9.126 0.167
    1A 72(6.35) 49(6.18) 23(6.74)
    1B 453(39.95) 320(40.35) 133(39.00)
    2A 160(14.11) 104(13.11) 56(16.42)
    3A 176(15.52) 117(14.75) 59(17.30)
    3B 86(7.58) 65(8.20) 21(6.16)
    4A 67(5.91) 55(6.94) 12(3.52)
    4B 120(10.58) 83(10.47) 37(10.85)
    T stage 3.099 0.377
    T1 568(50.09) 401(50.57) 167(48.97)
    T2 188(16.58) 125(15.76) 63(18.48)
    T3 232(20.46) 158(19.92) 74(21.70)
    T4 146(12.87) 109(13.75) 37(10.85)
    N stage 6.148 0.046
    N0 1021(90.04) 703(88.65) 318(93.26)
    N1 99(8.73) 80(10.09) 19(5.57)
    NX 14(1.23) 10(1.26) 4(1.17)
    M stage 0.037 0.847
    M0 1014(89.42) 710(89.53) 304(89.15)
    M1 120(10.58) 83(10.47) 37(10.85)
    Tumor size(mm) 3.163 0.367
    <20 73(6.44) 48(6.05) 25(7.33)
    21-50 398(35.1) 275(34.68) 123(36.07)
    51-100 400(35.27) 292(36.82) 108(31.67)
    >100 263(23.19) 178(22.45) 85(24.93)
    Radiotherapy 0.022 0.881
    No 848(74.78) 592(74.65) 256(75.07)
    Yes 286(25.22) 201(25.35) 85(24.93)
    Chemotherapy 0.477 0.490
    No 778(68.61) 549(69.23) 229(67.16)
    Yes 356(31.39) 244(30.77) 112(32.84)
    Surgery <0.001 >0.999
    No 1119(98.68) 783(98.74) 336(98.53)
    Yes 15(1.32) 10(1.26) 5(1.47)
    Notes: χ2: Chi-square test; −: Fisher exact.
    下载: 导出CSV

    表  2   老年肝细胞癌患者总生存期的单因素和多因素Cox比例风险回归分析

    Table  2   Univariate and multivariate Cox proportional hazard regression analyses of overall survival of elderly patients with hepatocellular carcinoma

    Univariate analysis Multivariate analysis
    HR(95%CI) P HR(95%CI) P
    Age(years)
    60-64 1.29(0.95-1.74) 0.106 1.11(0.81-1.52) 0.529
    65-69 Ref Ref
    70-74 1.56(1.16-2.09) 0.004 1.82(1.34-2.47) <0.001
    75-79 1.36(0.97-1.89) 0.071 1.21(0.85-1.73) 0.286
    80-84 1.25(0.87-1.80) 0.234 1.36(0.93-1.98) 0.109
    >84 1.40(0.90-2.20) 0.137 1.33(0.83-2.13) 0.230
    Ethnicity
    Black Ref
    White 0.95(0.70-1.28) 0.733
    Others 0.73(0.49-1.09) 0.129
    Gender
    Male Ref
    Female 1.04(0.82-1.31) 0.763
    Single status
    Yes Ref
    No 0.91(0.74-1.11) 0.353
    Clinical grade
    0.60(0.46-0.77) <0.001 0.65(0.50-0.85) 0.002
    Ref Ref
    1.49(1.16-1.92) 0.002 1.17(0.89-1.53) 0.266
    1.02(0.25-4.11) 0.978 1.28(0.30-5.51) 0.741
    Clinical stage
    1A 0.98(0.60-1.62) 0.948 0.46(0.24-0.89) 0.020
    1B Ref Ref
    2A 0.93(0.64-1.35) 0.697 0.89(0.41-1.96) 0.774
    3A 2.09(1.55-2.82) <0.001 1.90(0.99-3.66) 0.055
    3B 3.13(2.23-4.41) <0.001 2.33(1.21-4.50) 0.012
    4A 2.60(1.78-3.81) <0.001 2.88(1.41-5.91) 0.004
    4B 5.82(4.27-7.92) <0.001 5.57(3.27-9.51) <0.001
    T stage
    T1 Ref Ref
    T2 1.15(0.84-1.56) 0.385 1.03(0.52-2.05) 0.926
    T3 2.18(1.70-2.81) <0.001 0.71(0.40-1.28) 0.261
    T4 3.07(2.34-4.04) <0.001 0.97(0.56-1.71) 0.928
    N stage
    N0 Ref Ref
    N1 2.22(1.67-2.96) <0.001 0.63(0.36-1.11) 0.110
    NX 3.76(1.93-7.32) <0.001 0.76(0.34-1.71) 0.510
    M stage
    M0 Ref Ref
    M1 4.12(3.15-5.39) <0.001 NA(NA-NA)
    Tumor size(mm)
    <20 0.73(0.46-1.15) 0.174 1.38(0.74-2.58) 0.307
    21-50 0.51(0.39-0.67) <0.001 0.62(0.46-0.83) 0.002
    51-100 Ref Ref
    >100 2.18(1.72-2.75) <0.001 1.96(1.52-2.54) <0.001
    Radiotherapy
    No Ref Ref
    Yes 0.64(0.50-0.82) <0.001 0.63(0.48-0.81) <0.001
    Chemotherapy
    No Ref Ref
    Yes 0.76(0.62-0.94) 0.011 1.16(0.92-1.45) 0.207
    Surgery
    No Ref
    Yes 0.30(0.08-1.22) 0.092
    下载: 导出CSV
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  • 收稿日期:  2024-01-07
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  • 刊出日期:  2024-09-24

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