Article(id=1198558166339388087, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198558165093675863, articleNumber=null, orderNo=null, doi=10.11855/j.issn.0577-7402.1133.2024.0327, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1692806400000, receivedDateStr=2023-08-24, revisedDate=null, revisedDateStr=null, acceptedDate=1697040000000, acceptedDateStr=2023-10-12, onlineDate=1763688134988, onlineDateStr=2025-11-21, pubDate=1724774400000, pubDateStr=2024-08-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763688134988, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763688134988, creator=13701087609, updateTime=1763688134988, updator=13701087609, issue=Issue{id=1198558165093675863, tenantId=1146029695717560320, journalId=1189873630562394117, year='2024', volume='49', issue='8', pageStart='855', pageEnd='976', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1763688134691, creator=13701087609, updateTime=1763689174168, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1198562525043327039, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198558165093675863, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1198562525043327040, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198558165093675863, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=889, endPage=896, ext={EN=ArticleExt(id=1198558167044031163, articleId=1198558166339388087, tenantId=1146029695717560320, journalId=1189873630562394117, language=EN, title=Construction of prognosis prediction and risk stratification model for young patients with advanced lung adenocarcinoma based on SEER database, columnId=1190310109000602400, journalTitle=Medical Journal of Chinese People’s Liberation Army, columnName=Clinical Research, runingTitle=null, highlight=null, articleAbstract=

Objective Based on data from the US SEER database, this study investigates the incidence, epidemiological characteristics, treatment modalities, prognosis assessment, and risk stratification of advanced-stage lung adenocarcinoma in young patients. Methods SEER*Stat software was used to collect the incidence rates of lung adenocarcinoma among people under 50 in the US from 2000 to 2020, with annual percentage changes (APCs) calculated using Joinpoint software. Clinical data of 4490 advanced-stage lung adenocarcinoma patients under 50 years old from the SEER database (2010-2018) were retrospectively collected and analyzed. Kaplan-Meier method was used to calculate overall survival, log-rank test to estimate survival rates, and Cox proportional hazards regression model to conduct univariate and multivariate prognostic analyses, and a nomogram model was established to predict the survival of young advanced lung adenocarcinoma patients. The predictive performance of the nomogram was evaluated using ROC curves and calibration curves. X-Tile software was used for risk stratification of the prognosis of young advanced lung adenocarcinoma patients. Results From 2000 to 2020, the incidence rates of young lung adenocarcinoma in men and women in the US decreased from 2.1/100 000 and 2.2/100 000 to 1.1/100 000 and 1.5/100 000 respectively, with APCs of -2.16 and -1.39 (P<0.05). Compared to patients aged 40 to <50 years, patients under 40 were more likely to develop bone metastasis, liver metastasis, and lung metastasis, had a higher probability of receiving chemotherapy, tumors were more likely to occur in the lower or middle lobes of the lung, but had a lower probability of receiving radiotherapy, with statistically significant differences (P<0.05). Cox regression analysis showed that gender, age, race, N stage, M stage, subsite, liver metastasis, and bone metastasis were prognostic factors for young advanced lung adenocarcinoma patients (P<0.05); male patients had worse prognosis than female patients (HR=1.17, 95%CI 1.09-1.25); African American patients had worse prognosis than Caucasian patients (HR=1.12, 95%CI 1.02-1.23), other races had better prognosis than Caucasian patients (HR=0.83, 95%CI 0.77-0.97); patients aged 40 to <50 had worse prognosis than those under 40 (HR=1.34, 95%CI 1.21-1.48); patients with bone metastasis (HR=1.29, 95%CI 1.19-1.40) and liver metastasis (HR=1.40, 95%CI 1.28-1.54) had worse prognosis, with statistically significant differences (P<0.05). Based on the above prognostic factors, a nomogram model was established to predict 1-year, 3-year, and 5-year survival with areas under the curve (AUC) of 0.717, 0.692, and 0.699 respectively, and the calibration curve was close to the 45° diagonal. According to the risk scores, patients were divided into low-risk group [1017 cases (22.7%)], medium-risk group [2871 cases (63.9%)], and high-risk group [602 cases (13.4%)]. The difference is statistically significant comparing the survival rates among three groups (P<0.0001). Conclusion Gender, age, race, N stage, M stage, subsite, liver metastasis, and bone metastasis are prognostic factors for young advanced lung adenocarcinoma patients, and the nomogram model established based on these factors has high predictive performance.

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目的 基于美国SEER数据库相关数据,探究年轻肺腺癌晚期患者的发病情况、流行病学特征、治疗方式、预后评估和风险分层。方法 利用SEER*Stat软件收集2000-2020年美国<50岁人群的肺腺癌发病率,采用Joinpoint软件计算年度百分比变化(APCs)。回顾性收集SEER数据库中2010-2018年4490例<50岁的肺腺癌晚期患者临床数据进行分析。采用Kaplan-Meier法计算总生存期,log-rank检验估计生存率,采用Cox比例风险回归模型对研究队列进行单因素和多因素预后分析,并建立列线图模型预测年轻肺腺癌晚期患者的生存情况。采用ROC曲线及校准曲线评估列线图的预测效能。采用X-Tile软件对年轻肺腺癌晚期患者的预后进行风险分层。结果 2000-2020年,美国男、女年轻肺腺癌发病率由2.1/10万、2.2/10万分别下降到1.1/10万、1.5/10万,APCs分别为-2.16、-1.39(P<0.05)。与40~50岁肺腺癌晚期患者比较,<40岁患者易发生骨转移、肝转移和肺转移,接受化疗概率高,肿瘤易发生在肺下叶或中叶,但接受放疗的概率低,差异均有统计学意义(P<0.05)。Cox回归分析结果显示,性别、年龄、种族、N分期、M分期、亚部位、肝转移及骨转移是年轻肺腺癌晚期患者预后的影响因素(P<0.05);男性较女性预后差(HR=1.17,95%CI 1.09~1.25);黑人预后较白人差(HR=1.12,95%CI 1.02~1.23),其他种族预后优于白人(HR=0.83,95%CI 0.77~0.97);40~50岁患者预后较<40岁患者差(HR=1.34,95%CI 1.21~1.48);发生骨转移(HR=1.29,95%CI 1.19~1.40)和肝转移(HR=1.40,95%CI 1.28~1.54)者预后差,差异均有统计学意义(P<0.05)。基于以上预后影响因素建立列线图模型,预测年轻肺腺癌晚期患者1、3、5年的生存曲线下面积(AUC)分别为0.717、0.692和0.699,校准曲线接近45°对角线。通过风险评分可将患者分为低风险组[1017例(22.7%)]、中风险组[2871例(63.9%)]和高风险组[602例(13.4%)],3组生存概念比较,差异有统计学意义(P<0.0001)。结论 性别、年龄、种族、N分期、M分期、亚部位、肝转移和骨转移是年轻肺腺癌晚期患者的预后影响因素,据此建立的列线图模型预测效能较高。

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刘建,医学硕士,主管技师,主要从事公共卫生方面的研究

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刘建,医学硕士,主管技师,主要从事公共卫生方面的研究

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articleId=1198558166339388087, language=CN, label=图3, caption=年轻肺腺癌晚期患者Cox多因素分析结果, figureFileSmall=nu8msTpBqyck3lkI2hD4DQ==, figureFileBig=aUh86qRoWWHhdB89gpKoNQ==, tableContent=null), ArticleFig(id=1198578978786214338, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=EN, label=Fig.4, caption=The nomogram model, its calibration curve and ROC curve for prognosis of young patients with advanced lung adenocarcinoma, figureFileSmall=Uzj/jGCoGc5sqo+1HrnkbQ==, figureFileBig=G7sMDMJWfkqzjqP5E3NhCQ==, tableContent=null), ArticleFig(id=1198578978870100420, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=CN, label=图4, caption=年轻肺腺癌晚期患者预后列线图模型、校准曲线及ROC曲线

A. 列线图模型;B. 校准曲线;C. ROC曲线

, figureFileSmall=Uzj/jGCoGc5sqo+1HrnkbQ==, figureFileBig=G7sMDMJWfkqzjqP5E3NhCQ==, tableContent=null), ArticleFig(id=1198578978958180807, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=EN, label=Fig.5, caption=Risk stratification survival curves of young patients with advanced lung adenocarcinoma (n=4490), figureFileSmall=I/8h7SLjAkM31lgrnrnLRA==, figureFileBig=rn5J9zC6a3PJZLpxzBOmUg==, tableContent=null), ArticleFig(id=1198578979037872586, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=CN, label=图5, caption=年轻肺腺癌晚期患者风险分层生存曲线(n=4490), figureFileSmall=I/8h7SLjAkM31lgrnrnLRA==, figureFileBig=rn5J9zC6a3PJZLpxzBOmUg==, tableContent=null), ArticleFig(id=1198578979113370057, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=EN, label=Tab.1, caption=

Basic data of young patients with advanced lung adenocarcinoma [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目

<40岁
(n=728)

40~50岁
(n=3762)

合计
(n=4490)

χ2P
性别0.2120.645
394(54.1)2001(53.2)2395(53.3)
334(45.9)1761(46.8)2095(46.7)
种族22.694<0.001
黑人101(13.9)588(15.6)689(15.3)
白人454(62.4)2556(67.9)3010(67.0)
其他173(23.8)618(16.4)791(17.6)
T分期15.2480.002
T1212 (29.1)945 (25.1)1157 (25.8)
T2123(16.9)803(21.3)926(20.6)
T3132(18.1)804(21.4)936(20.8)
T4261(35.9)1210(32.2)1471(32.8)
N分期8.2530.041
N0177(24.3)939(25.0)1116(24.9)
N161(8.4)231(6.1)292(6.5)
N2275(37.8)1568(41.7)1843(41.0)
N3215(29.5)1024(27.2)1239(27.6)
M分期0.2820.595
M1A220(30.2)1100(29.2)1320(29.4)
M1B508(69.8)2662(70.8)3170(70.6)
放疗3.6210.057
354(48.6)1685(44.8)2039(45.4)
374(51.4)2077(55.2)2451(54.6)
化疗22.497<0.001
134(18.4)1007(26.8)1141(25.4)
594(81.6)2755(73.2)3349(74.6)
骨转移4.5610.033
378(51.9)2115(56.2)2493(55.5)
350(48.1)1647(43.8)1997(44.5)
肺转移8.8360.003
467(64.1)2623(69.7)3090(68.8)
261(35.9)1139(30.3)1400(31.2)
脑转移0.4100.522
461(63.3)2335(62.1)2796(62.3)
267(36.7)1427(37.9)1694(37.7)
肝转移4.2540.039
580(79.7)3117(82.9)3697(82.3)
148(20.3)645(17.1)793(17.7)
分级2.4940.287
高分化21(2.9)74(2.0)95(2.1)
中分化77(10.6)396(10.5)473(10.5)
低分化630(86.5)3292(87.5)3922(87.3)
患侧1.4830.476
双侧61(8.4)278(7.4)339(7.6)
左侧285(39.1)1431(38.0)1716(38.2)
右侧382(52.5)2053(54.6)2435(54.2)
亚部位36.090<0.001
下叶200(27.5)839(22.3)1039(23.1)
主支气管26(3.6)139(3.7)165(3.7)
中叶44(6.0)164(4.4)208(4.6)
交搭跨越7(1.0)48(1.3)55(1.2)
未知175(24.0)714(19.0)889(19.8)
上叶276(37.9)1858(49.4)2134(47.5)
), ArticleFig(id=1198578979209839050, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198558166339388087, language=CN, label=表1, caption=

年轻肺腺癌晚期患者的基线信息[例(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目

<40岁
(n=728)

40~50岁
(n=3762)

合计
(n=4490)

χ2P
性别0.2120.645
394(54.1)2001(53.2)2395(53.3)
334(45.9)1761(46.8)2095(46.7)
种族22.694<0.001
黑人101(13.9)588(15.6)689(15.3)
白人454(62.4)2556(67.9)3010(67.0)
其他173(23.8)618(16.4)791(17.6)
T分期15.2480.002
T1212 (29.1)945 (25.1)1157 (25.8)
T2123(16.9)803(21.3)926(20.6)
T3132(18.1)804(21.4)936(20.8)
T4261(35.9)1210(32.2)1471(32.8)
N分期8.2530.041
N0177(24.3)939(25.0)1116(24.9)
N161(8.4)231(6.1)292(6.5)
N2275(37.8)1568(41.7)1843(41.0)
N3215(29.5)1024(27.2)1239(27.6)
M分期0.2820.595
M1A220(30.2)1100(29.2)1320(29.4)
M1B508(69.8)2662(70.8)3170(70.6)
放疗3.6210.057
354(48.6)1685(44.8)2039(45.4)
374(51.4)2077(55.2)2451(54.6)
化疗22.497<0.001
134(18.4)1007(26.8)1141(25.4)
594(81.6)2755(73.2)3349(74.6)
骨转移4.5610.033
378(51.9)2115(56.2)2493(55.5)
350(48.1)1647(43.8)1997(44.5)
肺转移8.8360.003
467(64.1)2623(69.7)3090(68.8)
261(35.9)1139(30.3)1400(31.2)
脑转移0.4100.522
461(63.3)2335(62.1)2796(62.3)
267(36.7)1427(37.9)1694(37.7)
肝转移4.2540.039
580(79.7)3117(82.9)3697(82.3)
148(20.3)645(17.1)793(17.7)
分级2.4940.287
高分化21(2.9)74(2.0)95(2.1)
中分化77(10.6)396(10.5)473(10.5)
低分化630(86.5)3292(87.5)3922(87.3)
患侧1.4830.476
双侧61(8.4)278(7.4)339(7.6)
左侧285(39.1)1431(38.0)1716(38.2)
右侧382(52.5)2053(54.6)2435(54.2)
亚部位36.090<0.001
下叶200(27.5)839(22.3)1039(23.1)
主支气管26(3.6)139(3.7)165(3.7)
中叶44(6.0)164(4.4)208(4.6)
交搭跨越7(1.0)48(1.3)55(1.2)
未知175(24.0)714(19.0)889(19.8)
上叶276(37.9)1858(49.4)2134(47.5)
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基于SEER数据库的年轻肺腺癌晚期患者预后预测及风险分层的模型构建
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刘建 1 , 师金 2 , 田国 3
解放军医学杂志 | 临床研究 2024,49(8): 889-896
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解放军医学杂志 | 临床研究 2024, 49(8): 889-896
基于SEER数据库的年轻肺腺癌晚期患者预后预测及风险分层的模型构建
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刘建1, 师金2, 田国3
作者信息
  • 1河北省卫生健康委综合监督服务中心,河北石家庄 050061
  • 2河北医科大学第四医院肿瘤研究所,河北石家庄 050011
  • 3河北医科大学第四医院病案室,河北石家庄 050011
  • 刘建,医学硕士,主管技师,主要从事公共卫生方面的研究

Construction of prognosis prediction and risk stratification model for young patients with advanced lung adenocarcinoma based on SEER database
Jian Liu1, Jin Shi2, Guo Tian3
Affiliations
  • 1Service Center of Comprehensive Supervision, Health Commission of Hebei Province, Shijiazhuang, Hebei 050061, China
  • 2Cancer Research Institute, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China
  • 3Medical Records Room, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China
出版时间: 2024-08-28 doi: 10.11855/j.issn.0577-7402.1133.2024.0327
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目的 基于美国SEER数据库相关数据,探究年轻肺腺癌晚期患者的发病情况、流行病学特征、治疗方式、预后评估和风险分层。方法 利用SEER*Stat软件收集2000-2020年美国<50岁人群的肺腺癌发病率,采用Joinpoint软件计算年度百分比变化(APCs)。回顾性收集SEER数据库中2010-2018年4490例<50岁的肺腺癌晚期患者临床数据进行分析。采用Kaplan-Meier法计算总生存期,log-rank检验估计生存率,采用Cox比例风险回归模型对研究队列进行单因素和多因素预后分析,并建立列线图模型预测年轻肺腺癌晚期患者的生存情况。采用ROC曲线及校准曲线评估列线图的预测效能。采用X-Tile软件对年轻肺腺癌晚期患者的预后进行风险分层。结果 2000-2020年,美国男、女年轻肺腺癌发病率由2.1/10万、2.2/10万分别下降到1.1/10万、1.5/10万,APCs分别为-2.16、-1.39(P<0.05)。与40~50岁肺腺癌晚期患者比较,<40岁患者易发生骨转移、肝转移和肺转移,接受化疗概率高,肿瘤易发生在肺下叶或中叶,但接受放疗的概率低,差异均有统计学意义(P<0.05)。Cox回归分析结果显示,性别、年龄、种族、N分期、M分期、亚部位、肝转移及骨转移是年轻肺腺癌晚期患者预后的影响因素(P<0.05);男性较女性预后差(HR=1.17,95%CI 1.09~1.25);黑人预后较白人差(HR=1.12,95%CI 1.02~1.23),其他种族预后优于白人(HR=0.83,95%CI 0.77~0.97);40~50岁患者预后较<40岁患者差(HR=1.34,95%CI 1.21~1.48);发生骨转移(HR=1.29,95%CI 1.19~1.40)和肝转移(HR=1.40,95%CI 1.28~1.54)者预后差,差异均有统计学意义(P<0.05)。基于以上预后影响因素建立列线图模型,预测年轻肺腺癌晚期患者1、3、5年的生存曲线下面积(AUC)分别为0.717、0.692和0.699,校准曲线接近45°对角线。通过风险评分可将患者分为低风险组[1017例(22.7%)]、中风险组[2871例(63.9%)]和高风险组[602例(13.4%)],3组生存概念比较,差异有统计学意义(P<0.0001)。结论 性别、年龄、种族、N分期、M分期、亚部位、肝转移和骨转移是年轻肺腺癌晚期患者的预后影响因素,据此建立的列线图模型预测效能较高。

年轻  /  肺腺癌  /  预后  /  预测模型  /  风险分层

Objective Based on data from the US SEER database, this study investigates the incidence, epidemiological characteristics, treatment modalities, prognosis assessment, and risk stratification of advanced-stage lung adenocarcinoma in young patients. Methods SEER*Stat software was used to collect the incidence rates of lung adenocarcinoma among people under 50 in the US from 2000 to 2020, with annual percentage changes (APCs) calculated using Joinpoint software. Clinical data of 4490 advanced-stage lung adenocarcinoma patients under 50 years old from the SEER database (2010-2018) were retrospectively collected and analyzed. Kaplan-Meier method was used to calculate overall survival, log-rank test to estimate survival rates, and Cox proportional hazards regression model to conduct univariate and multivariate prognostic analyses, and a nomogram model was established to predict the survival of young advanced lung adenocarcinoma patients. The predictive performance of the nomogram was evaluated using ROC curves and calibration curves. X-Tile software was used for risk stratification of the prognosis of young advanced lung adenocarcinoma patients. Results From 2000 to 2020, the incidence rates of young lung adenocarcinoma in men and women in the US decreased from 2.1/100 000 and 2.2/100 000 to 1.1/100 000 and 1.5/100 000 respectively, with APCs of -2.16 and -1.39 (P<0.05). Compared to patients aged 40 to <50 years, patients under 40 were more likely to develop bone metastasis, liver metastasis, and lung metastasis, had a higher probability of receiving chemotherapy, tumors were more likely to occur in the lower or middle lobes of the lung, but had a lower probability of receiving radiotherapy, with statistically significant differences (P<0.05). Cox regression analysis showed that gender, age, race, N stage, M stage, subsite, liver metastasis, and bone metastasis were prognostic factors for young advanced lung adenocarcinoma patients (P<0.05); male patients had worse prognosis than female patients (HR=1.17, 95%CI 1.09-1.25); African American patients had worse prognosis than Caucasian patients (HR=1.12, 95%CI 1.02-1.23), other races had better prognosis than Caucasian patients (HR=0.83, 95%CI 0.77-0.97); patients aged 40 to <50 had worse prognosis than those under 40 (HR=1.34, 95%CI 1.21-1.48); patients with bone metastasis (HR=1.29, 95%CI 1.19-1.40) and liver metastasis (HR=1.40, 95%CI 1.28-1.54) had worse prognosis, with statistically significant differences (P<0.05). Based on the above prognostic factors, a nomogram model was established to predict 1-year, 3-year, and 5-year survival with areas under the curve (AUC) of 0.717, 0.692, and 0.699 respectively, and the calibration curve was close to the 45° diagonal. According to the risk scores, patients were divided into low-risk group [1017 cases (22.7%)], medium-risk group [2871 cases (63.9%)], and high-risk group [602 cases (13.4%)]. The difference is statistically significant comparing the survival rates among three groups (P<0.0001). Conclusion Gender, age, race, N stage, M stage, subsite, liver metastasis, and bone metastasis are prognostic factors for young advanced lung adenocarcinoma patients, and the nomogram model established based on these factors has high predictive performance.

young  /  adenocarcinoma of lung  /  prognosis  /  prediction model  /  risk stratification
刘建, 师金, 田国. 基于SEER数据库的年轻肺腺癌晚期患者预后预测及风险分层的模型构建. 解放军医学杂志, 2024 , 49 (8) : 889 -896 . DOI: 10.11855/j.issn.0577-7402.1133.2024.0327
Jian Liu, Jin Shi, Guo Tian. Construction of prognosis prediction and risk stratification model for young patients with advanced lung adenocarcinoma based on SEER database[J]. Medical Journal of Chinese People’s Liberation Army, 2024 , 49 (8) : 889 -896 . DOI: 10.11855/j.issn.0577-7402.1133.2024.0327
2020年全球癌症统计报告(GLOBOCAN2020)显示,肺癌依然是全球死亡原因居第一位的恶性肿瘤。据估计,2023年美国新发肺癌238 340例,肺癌导致的死亡达127 070例[1]。按组织学亚型,肺癌可分为小细胞肺癌和非小细胞肺癌(NSCLC),分别占所有肺癌的15%和85%;NSCLC可进一步分为鳞状细胞癌、腺癌和大细胞癌,其中腺癌更为常见,也是人群中最多见的肺癌类型[2-3]。NSCLC确诊时的中位年龄>60岁,常被认为是老年人的疾病;约40%的NSCLC患者最初诊断为Ⅳ期[4]。近几十年来,随着民众健康意识的提高和低剂量CT筛查的开展,肺癌患者中年轻人占比有上升趋势[5-6],但目前尚无公认的年轻肺癌的年龄定义。根据既往研究,本研究将<50岁的肺癌患者定义为年轻肺癌[7-11]。有研究显示,<40岁的年轻肺癌患者预后较老年患者差[12];但也有报道,<40岁的年轻肺癌患者总体生存率高于老年患者[13]。关于年轻肺腺癌近年的发病情况,年轻肺腺癌晚期患者的流行病学特征、治疗方式、预后评估及不同年龄组间生存比较等的研究仍比较欠缺。本研究基于美国国立癌症研究所的SEER(Surveillance,Epidemiology,and End Results Program)数据库中美国肺癌患者的相关数据,探讨年轻肺腺癌晚期患者的临床特征及预后相关因素,并构建预后列线图,以期更好地预测其生存情况,及早识别高风险患者,并推荐分层治疗管理。
回顾性收集SEER数据库中2010-2018年4490例根据病理确诊为年轻肺腺癌晚期的患者信息。纳入标准:(1)国际肿瘤疾病分类第3版(ICD-O-3)的组织学代码为C33.0-C34.9,形态学代码为8140-8384;(2)肿瘤分期为Ⅳ期;(3)年龄<50岁。排除标准:(1)肿瘤非远端转移;(2)诊断年龄、放疗、分级、种族、生存状态、生存月等其他变量信息缺失或未知。本研究不包括与人类受试者的互动,也不使用SEER数据库中的个人识别信息,因此豁免机构审查委员会的批准和患者知情同意。
利用SEER*Stat软件中的“Rate section”模块,计算2000-2020年美国每10万人口中年轻肺腺癌患者的发病率,并根据2000名美国标准人口进行年龄调整。使用Joinpoint软件计算年度百分比变化(APCs)。
分析年轻肺腺癌晚期患者的年龄、性别、种族、诊断年份、组织学亚型、分期、放疗、化疗、生存时间、生存状态和死亡原因等。收集所有年轻肺腺癌晚期患者的死亡日期或最后接触日期。最后接触日期定义为2018年12月31日。总生存期定义为从诊断到因任何原因死亡的时间。随访终止时间为以下任何一种情况首先出现:失访、死亡或2018年12月31日。种族分为白人、黑人和其他种族(美洲印第安人、阿拉斯加原住民、亚裔或太平洋岛民)。
采用Kaplan-Meier 法计算总生存期,采用 log-rank 检验估计生存率;对各变量进行风险比例假设,采用Cox比例风险回归模型对研究队列进行单因素和多因素分析,探讨年轻肺腺癌晚期患者的预后影响因素。在Cox比例风险回归模型的基础上,采用列线图预测年轻肺腺癌晚期患者的生存情况。利用X-Tile软件对年轻肺腺癌晚期患者的预后进行风险分层,将其分为高、中、低风险组,并分析3组患者的生存概率差异。
采用R软件(R Core Team,2020)进行统计分析及绘图。计数资料以例(%)表示,多组间比较采用χ2检验或Fisher确切概率法,进一步两两比较采用Scheffe法。采用ROC曲线及校准曲线评估列线图的预测效果。P<0.05为差异有统计学意义(双侧检验)。
根据SEER数据库中选取的<50岁肺腺癌患者数据,2000-2020年,美国男、女肺腺癌发病率由2.1/10万、2.2/10万分别下降到1.1/10万、1.5/10万,APCs分别为-2.16、-1.39(P<0.05);其中40~50岁男、女肺腺癌发病率由8.5/10万、8.3/10万分别下降到3.8/10万、5.3/10万,APCs分别为-2.7、-1.5(P<0.05,图1)。近20年间,<40岁女性肺腺癌发病率的波动较男性更加明显。
与40~50岁肺腺癌晚期患者相比,<40岁患者易发生骨转移、肝转移和肺转移,接受化疗的概率高,肿瘤容易发生在下叶或中叶,但接受放疗的概率低,差异均有统计学意义(P<0.05,表1)。
经Cox单因素回归分析及比例风险假设检验后,不同性别、年龄、种族、N分期、M分期、亚部位、肝转移及骨转移的年轻肺腺癌晚期患者生存率差异均有统计学意义(P<0.05,图2)。Cox多因素分析结果显示,与女性年轻肺腺癌晚期患者比较,男性预后较差(HR=1.17,95%CI 1.09~1.25);不同种族患者比较,黑人预后较白人差(HR=1.12,95%CI 1.02~1.23),其他种族预后优于白人(HR=0.83,95%CI 0.77~0.97);与<40岁患者比较,40~50岁患者的预后较差(HR=1.34,95%CI 1.21~1.48)。与无区域淋巴结转移患者比较,同侧纵隔内及(或)隆突下淋巴结转移(N2分期)的患者预后较差(HR=1.15,95%CI 1.05~1.26),对侧纵隔、肺门、同侧或对侧前斜角肌及锁骨上淋巴结转移(N3分期)患者预后也更差(HR=1.16,95%CI 1.03~1.27)。与远处转移局限于胸腔内的患者比较,远处转移在胸腔外(M1B分期)的患者预后较差(HR=1.16,95%CI 1.07~1.27)。对于晚期患者,骨转移(HR=1.29,95%CI 1.19~1.40)和肝转移(HR=1.40,95%CI 1.28~1.54)患者的预后较无转移患者差,差异均有统计学意义(P<0.01)。就亚部位而言,与肺下叶的腺癌比较,主支气管(HR=1.37,95%CI 1.13~1.65)和肺上叶(HR=1.18,95%CI 1.08~1.30)的腺癌预后较差(P<0.01),而肺中叶的腺癌预后差异无统计学意义(P>0.05,图3)。
基于年轻肺腺癌晚期患者的预后危险因素构建列线图模型。根据列线图可得到每个因素对应的分值,通过分值相加得到的总分定位在总分轴上即可确定患者1、3、5年总体生存的估计概率。在生存列线图中,种族对预后的影响最为明显,其次是亚部位、肝转移、年龄、性别等;而远端转移(N3、M1B分期)对预后的影响较小(图4A)。ROC曲线显示,预后列线图135年的曲线下面积(AUC)分别为0.717、0.692和0.699,校准曲线接近 45°对角线(图4B、C)。
使用X-tile软件计算列线图总分与预后相关的最佳截断值,将4490例年轻肺腺癌晚期患者分为低风险组1017例(22.7%,总分<158.24分)、中风险组2871例(63.9%,总分158.24~223.70分)和高风险组602例(13.4%,总分223.75~288.99分),3组生存概率比较差异有统计学意义(P<0.0001,图5)。
虽然相关文献报道,美国SEER数据库中不到5%的肺癌患者在诊断时年龄<50岁[8],但是,鉴于肺癌的高发病率和病死率,对年轻肺癌患者的研究仍值得关注。美国国立综合癌症网络(National Comprehensive Cancer Network,NCCN)2022年版筛查指南建议>50岁且有高危因素的人群常规行低剂量CT筛查,对年青群体则为“不推荐”[14]
本研究结果显示,2000-2020年美国年轻肺腺癌患者的发病率逐年下降,这与另一篇基于SEER数据库的2000-2019年0~54岁肺癌发病率数据基本一致[15]。需要注意的是,<40岁女性肺腺癌发病率的波动较男性更加明显。可能的原因为:(1)非吸烟肺癌在年轻女性中发病率较高,在过去十年中,非吸烟者的肺癌诊断率增高1倍,而多种非吸烟风险因素与肺癌的发展有关,包括肺癌致癌物、室内烹饪烟雾和二手烟等[16-17];(2)青年女性表达胃泌素释放肽受体基因,可提高女性对烟草等致癌物的敏感性,仅需摄入少量致癌物就可能诱发肺癌的发生;(3)NSCLC可能有家族倾向,相关研究显示,一级女性亲属的患病风险往往高于一级男性亲属,提示了肺癌家族史在无吸烟史家庭中的影响[18]。此外,年轻时患肺癌通常与遗传风险有关。据报道,女性携带易感性多态性和位点及关键驱动基因[如TP53和Kirsten大鼠肉瘤病毒癌基因同源物(Kirsten rat sarcoma viral oncogene homolog,KRAS)]的突变频率更高[19-20]
在年龄方面,本研究结果显示,<40岁肺腺癌晚期患者的总体生存期优于40~50岁患者;与以往部分研究一致,这些研究显示年龄是肺腺癌患者生存的影响因素[21-23]。有研究显示,与老年肺癌患者比较,青年患者更易发生淋巴结转移,但其5年生存率差异无统计学意义[24];另有报道年轻肺癌患者预后较老年患者差[25]。这可能是由于年轻肺癌患者较老年患者的肿瘤细胞分裂更活跃,肿瘤倍增时间短,易发生淋巴结转移,且治疗效果和长期预后差,也可能与年轻肺癌患者的年龄分组不同有关[26]。就性别而言,年轻女性晚期肺癌生存率优于男性,一项Meta分析结果也显示,部分针对性治疗可能受性别的影响,女性的生存结局更好,这可能与不同激素和受体表达水平的差异、EGFR突变率高或对于治疗的敏感度高有关[27-29]。除了性别是年轻肺腺癌晚期患者的独立预后因素外,种族因素也不容忽视。本研究发现,与其他种族人群相比,黑人和白人的预后均较差。这与之前另一报道的SEER数据库中其他种族人群预后更好的结果一致[30]
晚期肺癌患者常见的转移部位是脑、骨、肝及呼吸系统,远端脏器转移可能是肺腺癌晚期患者独立的预后影响因素[31]。研究显示,有远端器官转移的肺癌患者生存期普遍短于无器官转移者,患者发生器官转移多提示肿瘤侵袭性较强,预后较差[32]。肝转移是NSCLC患者常见且预后较差的转移类型,晚期肝转移的发生率可达20%左右[23,33]。年轻患者发生肝转移的风险较高,原因可能是其拥有较好的血管生成微环境,由此可促进肿瘤生长和转移,同时肿瘤需要更具侵袭性才能逃脱年轻个体的免疫监测[34]。本研究肝转移患者的总体生存率较低,与以往的研究结果一致[35-36]
肺腺癌患者早期一般无明显症状,易发生转移而侵犯神经、淋巴管和血管等,预后较差[37]。因此,探究年轻肺腺癌晚期患者预后的相关危险因素并建立预测模型,可为临床医师实施个体化干预提供科学依据,以改善预后。与传统的统计分析相比,列线图更为直观简便,有利于临床医师安排个体化治疗和应对患者咨询。因此,本研究通过分析年轻肺腺癌晚期患者预后相关因素,构建列线图预后模型。本研究基于SEER数据库应用大样本量的年轻肺腺癌晚期患者临床数据;AUC曲线、校准曲线提示预测模型判别准确性较高,模型的预测值与真实值的一致性较好;预测模型可根据风险评分将患者分为不同的风险亚组,可更好地预测肺腺癌患者的个体化生存情况。
本研究存在的局限性:(1)SEER数据库中未提供患者的吸烟史、恶性肿瘤家族史和基因突变情况;(2)SEER数据库对于晚期肺腺癌的治疗信息记录相对简单,无法获取化疗用药及频率、靶向治疗等情况;(3)本研究建立的预后预测模型未进行外部验证,模型的外推性尚待进一步确认。
综上所述,年轻肺腺癌晚期患者总体预后较差,性别、年龄、种族、N分期、M分期、亚部位、肝转移、骨转移、肺转移和化疗均是患者预后的独立危险因素,本研究据此建立了年轻肺腺癌晚期患者的预后预测模型,并依据风险评分将患者分为高中低3个风险亚组,可为肺腺癌患者的个体化治疗提供参考。本研究基于美国SEER数据库中年轻肺腺癌晚期患者的数据,我国此类人群的危险因素及预后将是未来研究的重要方向。此外,国内外的肺癌筛查推荐年龄多为40岁甚至45岁以上,探索适合中国年轻居民的肺癌筛查方案也是当前肺癌防治研究的重要任务之一。
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doi: 10.11855/j.issn.0577-7402.1133.2024.0327
  • 接收时间:2023-08-24
  • 首发时间:2025-11-21
  • 出版时间:2024-08-28
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  • 收稿日期:2023-08-24
  • 录用日期:2023-10-12
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    1河北省卫生健康委综合监督服务中心,河北石家庄 050061
    2河北医科大学第四医院肿瘤研究所,河北石家庄 050011
    3河北医科大学第四医院病案室,河北石家庄 050011
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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