Influencing Factors of Overall Survival of Elderly Patients with Hepatocellular Carcinoma and Construction of Prediction Model of Prognosis Nomogram: A Population-Based Study
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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:ObjectiveTo 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.
MethodsClinical 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.
ResultsA 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.ConclusionAge, 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.
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Key words:
- Hepatocellular carcinoma /
- SEER database /
- Elderly /
- Prognostic factors /
- Nomogram
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0 引言
肝细胞癌(hepatocellular carcinoma, HCC)是肝癌最常见的病理类型,是全世界高发病率、高致死率的恶性肿瘤之一[1],在全球男性和女性的常见癌症中分别排名第5位和第9位[2],并且发病率逐年升高[3],目前已成为全球癌症导致死亡的第四大原因[4]。大多数发达国家数据显示HCC中以老年人群(≥60岁)占比最高[5],同时随着全球人口老龄化的加速,老年群体在HCC患者中将更加突出[6]。美国多项研究建议大于45岁的人群应加强筛查甲胎蛋白(alpha-fetoprotein, AFP)[7-10],以早期发现HCC,提高患者的治疗及预后。因此,对老年HCC患者的生存率进行评估和预测有助于该类患者的个性化生存评估和临床管理。有研究指出年龄、性别、种族、原发位置、TNM分期、临床分级、肿瘤大小等都可能与HCC的生存率有关[10-11],但以上研究都集中在HCC患者的整体水平上,而不是特定的老年人群,故针对这一特定年龄群体建立生存预测模型的列线图具有重要意义。本研究拟开发和验证一种列线图模型,以预测老年HCC患者总生存期(overall survival, OS)的概率并提高其预测的准确性和实用价值,有望对老年HCC患者提供个性化的生存预测,并优化患者的临床管理。
1 资料与方法
1.1 研究对象
研究数据来自美国癌症统计数据的权威SEER数据库(www.seer.cancer.gov)。通过申请注册下载SEER Stat软件(SEER Stat 8.4.2)后,根据纳入和排除标准,获得
1134 例老年HCC患者的基本信息和随访资料。1.2 纳入和排除标准
纳入标准:(1)诊断为HCC(AYA位点重新编码/WHO 2008:4.2 肝细胞癌);(2)诊断年份为2005—2020年;(3)诊断时年龄≥60岁;(4)组织学类型为肝细胞癌(ICD-O-3:8170);(5)完成随访。排除标准:(1)非原发性HCC;(2)下载数据中任一变量未知或缺失;(3)经尸检或者死亡证明确诊的患者;(4)生存时间<1个月。筛选的病例均采用美国癌症联合委员会(AJCC)第8版癌症分期系统评估诊断。
1.3 数据选择
在本研究中,每位患者提取的数据涉及19项变量。人口统计学变量包括年龄、种族、性别、单身状态、诊断年龄、诊断年份、生存时间(月)和生存状态;肿瘤的病理特征包括原发位置、组织学类型、AJCC临床分级、临床分期、TNM分期和肿瘤大小;以及相关治疗信息包括手术、化疗和放疗情况。将患者按年龄分为六组,60~64、65~69、70~74、75~79、80~84和>84岁;根据中华医学会外科学定义按照最大肿瘤直径将肿瘤大小分为微小肝癌(<20 mm)、小肝癌(20~50 mm)、大肝癌(51~100 mm)和巨大肝癌(>100 mm)四类。所有筛选的合格病例原发部位均来自于肝脏且组织学类型均为HCC。主要结局OS定义为从诊断日期到任何原因死亡的时间间隔。
1.4 统计学方法
所有数据均使用SPSS 25.0和R软件(版本4.2.3)进行统计分析。为确保模型的稳定性和区分度,R软件以7∶3的比例将患者随机分为训练组和验证组。χ2检验和Fisher精确检验比较两组之间的基线特征,并对与预后相关变量进行单因素Cox分析,纳入P<0.05的变量进行多因素Cox分析,以确定老年HCC患者的独立预后因素。对数秩检验进行Kaplan-Meier分析验证独立预后因素与OS的相关性。此外,采用确定的独立预后因素建立列线图模型,Harrell一致性指数(C指数)评估区分观测结果和预测结果的能力。受试者工作特征(ROC)曲线和曲线下面积(AUC)评价模型的预测效率。根据1 000次迭代的自举重采样执行的校准曲线,以图形方式评估预测生存期和实际生存期之间的一致性。决策曲线分析(DCA)评估列线图的临床应用价值。P<0.05(双侧)为差异有统计学意义。
2 结果
2.1 临床病理特征
最终入选1 134例患者。随机分为训练组(793例)和验证组(341例)。两组差异均衡,患者的基线数据见表1。在肿瘤特征方面,老年HCC患者多为Ⅱ级(54.14%)、1B期(39.95%)、T1期(50.09%)、N0期(90.04%)和M0期(89.42%),肿瘤大小分型则多以20 mm以上多见(93.56%)。少数患者接受放疗(25.22%)、化疗(31.39%)和手术治疗(1.32%)。
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 Ⅰ 323(28.48) 227(28.63) 96(28.15) Ⅱ 614(54.14) 429(54.10) 185(54.25) Ⅲ 193(17.02) 135(17.02) 58(17.01) Ⅳ 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. 2.2 老年HCC患者的独立预后因素
单因素Cox分析结果显示,9项变量与老年HCC患者的OS相关,包括年龄、临床分级、临床分期、TNM分期、肿瘤大小和放化疗情况(均P<0.05)。进一步多因素Cox分析结果确定6项变量作为独立预后因素,包括年龄、临床分级、临床分期、M分期、肿瘤大小和放疗情况,见表2。同时对上述因素进行Kaplan-Meier生存分析,发现临床分级、M分期及放疗情况与老年HCC患者的OS明显相关,结果与单因素Cox分析和多因素Cox分析结果一致,见图1。
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 carcinomaUnivariate 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 Ⅰ 0.60(0.46-0.77) <0.001 0.65(0.50-0.85) 0.002 Ⅱ Ref Ref Ⅲ 1.49(1.16-1.92) 0.002 1.17(0.89-1.53) 0.266 Ⅳ 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 2.3 列线图的开发和验证
根据确定的独立预后因素,构建列线图预测老年HCC患者6、12和24个月的OS,见图2。对列线图的整体性能进行评估,训练组的C指数为0.745(95%CI: 0.719~0.772),验证组的C指数为0.704(95%CI: 0.664~0.744),表明该预测模型具有足够的判别能力。ROC曲线显示,训练组6、12和24个月的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,表明预测模型具有良好的区分能力,见图3。此外,训练组和验证组的校准曲线显示,实际观测结果与列线图预测的结果高度一致,说明模型的校准度较好,见图4。列线图DCA曲线显示,列线图的辨别能力在训练组和验证组中较好,表明构建的列线图模型具有较好的预测能力,见图5。
3 讨论
随着全球人口老龄化,老年人患HCC的风险更加突出[12],这无疑对老年HCC患者的临床管理提出了新的挑战。基于这些考虑,老年HCC患者值得作为代表性人群进行个体化探索其预后独立影响因素。
列线图是一种易使用的可视化统计模型,可结合多个预测因子,为临床医生和患者提供个性化的生存预测。由于其易使用和可靠的鉴别能力,被广泛用于预测各种恶性肿瘤的OS[13-17]。有研究探讨了HCC相关危险因素,但大多集中在HCC患者整体水平上,并不是特定老年人群,且针对该类特定人群所构建的生存预测模型较少,因此HCC患者的生存预测仍然存在不确定性[10-11]。此外,在临床中仅使用经验评估OS并不准确,故目前仍缺乏对老年HCC患者的预后因素和生存趋势的分析。为了解决这个问题,我们使用基于人群的数据库来确定独立预后因素,并开发构建相关列线图来预测老年HCC患者预后的OS概率,并进一步验证其预测准确性和实用价值。
本研究确定了与老年HCC患者预后相关的6项独立影响因素,包括年龄、临床分级、临床分期、M分期、肿瘤大小和放疗情况。结果表明,70~74岁年龄组的HCC患者的OS最短(HR=1.82,95%CI: 1.34~2.47),而年龄≥75岁的患者相较于70~74岁患者的OS反而有所改善,分析其主要原因可能与该类患者样本较少有关,同时该类患者通常营养状况更差,生理储备进一步减少,基础疾病更复杂以及对治疗的耐受性差等,反而更加配合治疗以延续生命,这可能是该类患者OS改善的原因之一[18]。另一方面,老年患者免疫功能下降,使肿瘤细胞更容易逃避免疫系统监视,因此,原发性老年HCC在疾病早期往往更具侵袭性,导致预后更差[19-20],综上表明,年龄与HCC患者预后较差具有明显的相关性。此外,我们发现在老年HCC患者中,性别、种族、单身状态与预后无关,与既往一些HCC整体人群研究矛盾[10-11],分析其原因可能为本研究人群更具有针对性。在特定老年群体中,上述三项因素不再具有较大影响,建议以后可针对此点进一步行亚组分析探究其原因。
肿瘤特征往往也会影响其预后,低级别HCC通常被认为是惰性肿瘤,而高级别HCC通常不利于患者生存[21]。本研究也证实了这一点,临床分期中高级别HCC患者的预后更差,其中4B期患者的OS最差(HR=5.57,95%CI: 3.27~9.51),并且临床分级和临床分期被确定为独立危险因素。然而,我们发现4A期较3B期具有更长的OS,分析原因可能为3B期具有淋巴结转移,分化不良而更具侵袭性,这一特征导致局部复发和转移的风险更高[22],故OS更短。同时临床分级4级生存曲线在25个月左右转为直线下降,这与纳入数据占比太少且处于同一时间死亡有关。此外,有研究表明,肿瘤分期和肿瘤大小可以预测患者预后[23-25]。本研究结果显示M分期和肿瘤大小是老年HCC患者的独立预后因素。在初步诊断时存在远处转移意味着疾病已经发展到晚期,癌症治疗效果较差[26-27]。同时,较大的肿瘤可能代表更长的肿瘤生长期,这增加了转移的可能性并使手术完全切除变得困难,同样图1显示肿瘤大小为0~20 mm的患者可能具有更好的OS,可能与样本分布占比有关,另外,肿瘤较小的患者多处于疾病早期阶段,由此导致肿瘤大小与OS呈非正相关趋势。
经单因素和多因素分析,放疗也被确定为老年HCC患者的独立预后因素,且生存分析也显示放疗与老年HCC患者的OS明显相关。手术切除有利于提高HCC患者的长期生存[28],但本研究发现手术治疗并非老年HCC患者的危险预后因素,并且有文献指出[29-30]临床上单独接受手术患者数量较少,大多数患者为手术联合放化疗治疗,且本样本非手术治疗患者占比98.68%,样本分布不均,故仅手术治疗是否为老年HCC患者的独立预后因素还需未来多数据研究。此外,有趣的是,化疗情况在单因素分析中具有意义,而在多因素分析中却显示无意义,这也与临床HCC治疗通常未采用单独化疗有关[31],由此导致各变量间相关性较大,统计结果与临床表现差异,建议未来针对此点进行亚组分析研究。最后,基于上述独立预后因素,本研究构建的预测模型可以通过结合确定的独立预测因子来量化老年HCC患者的OS概率。并且我们评估了模型的预测准确性和临床实用性,ROC曲线和DCA曲线均表明该列线图具有较好的预测能力。
本研究仍然存在一定局限性:第一,作为一项回顾性研究,潜在的选择偏倚不可避免;第二,未使用独立的大规模数据进行外部验证;第三,列线图为临床医生提供了相对参考,临床上可能还存在与老年HCC患者预后相关的其他因素(如生化指标等),本研究未作分析;第四,数据大部分来源于美国,且白种人占比最高,对亚洲人的预测精准度可能还需在临床进一步验证。
本研究构建的预后列线图预测模型具有良好的预测价值,可以较准确地预测老年HCC患者的OS,这将帮助医生和患者制定治疗计划和后续策略,有助于老年HCC患者的个性化生存评估和临床管理。
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 -
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 Ⅰ 323(28.48) 227(28.63) 96(28.15) Ⅱ 614(54.14) 429(54.10) 185(54.25) Ⅲ 193(17.02) 135(17.02) 58(17.01) Ⅳ 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. 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 Ⅰ 0.60(0.46-0.77) <0.001 0.65(0.50-0.85) 0.002 Ⅱ Ref Ref Ⅲ 1.49(1.16-1.92) 0.002 1.17(0.89-1.53) 0.266 Ⅳ 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 -
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1. 李甜,伍杨,张江明,席春生. 老年肾透明细胞癌患者发生肺转移的列线图预测模型构建. 国际肿瘤学杂志. 2024(12): 755-762 . 百度学术
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