Please wait a minute...
浙江大学学报（医学版）
浙江大学学报（医学版）  2018, Vol. 47 Issue (1): 104-109    DOI: 10.3785/j.issn.1008-9292.2018.02.15
综述     
基于人群的肿瘤登记数据评估患者生存的方法学研究进展
唐慧娟(),蒋曦依(),楼建林,陈天辉*()
浙江省医学科学院职业病防治研究所分子流行病学与癌症精准预防研究组, 浙江 杭州 310013
Methodology for survival assessment of cancer patients using population-based cancer registration data
TANG Huijuan(),JIANG Xiyi(),LOU Jianlin,CHEN Tianhui*()
Group of Molecular Epidemiology & Cancer Precision Prevention, Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, China
 全文: PDF(1288 KB)   HTML( 8 )
摘要：

评估和监测癌症患者的长期生存情况，计算存活率是评估癌症治疗效果和癌症负担的必要指标。队列法是传统的肿瘤监测数据生存分析方法，但其纳入的是往年诊断的患者，不能体现新近诊断的患者因医疗技术提高而导致的实际存活率上升。因此，近年来出现了周期分析法和基于模型的周期分析法。周期分析法纳入的病例均为感兴趣时期内的病例，能够体现新近诊断患者的实际生存情况；而基于模型的周期分析法不仅能利用已有的数据来估算存活率和分析变化趋势，还能预测未来的存活率。相较于传统的队列法，周期分析法和基于模型的周期分析法在生存分析的时效性和准确性方面更具优势。本文就队列法、周期分析法和基于模型的周期分析法的概念、原理、计算方法和应用进行综述。
关键词： 肿瘤;  登记;  存活率分析;  队列研究;  周期性;  评价研究;  综述    
Abstract:

Evaluating and monitoring long-term survival of cancer patients and reporting the survival rate are routinely employed by cancer registries. Long-term survival rate is a necessary indicator in evaluating the effect of cancer therapy and cancer burden. Cohort method is a traditional approach for survival analysis, but it essentially reflects the survival expectations of patients diagnosed many years ago, therefore survival status of cancer patients was often disclosed with delay. Given the limitation of cohort method, period analysis and model-based period analysis are subsequently proposed and gradually applied in assessment of survival rates in recent years. Period analysis includes the patients of interest period, which reflects more up-to-date estimates of long-term survival of cancer patients. While model-based period analysis can use the existing data to calculate survival rates and to assess the trend, and predict survival rates in the future. Compared with cohort approach, period analysis and model-based period analysis are better in timeliness and precision in survival analysis. This article reviews the definition and theory, calculation and application of cohort method, period analysis and model-based period analysis, in order to provide a basis on up-to-date and precise assessment of survival rates of cancer patients.
Key words: Neoplasms    Registries    Survival analysis    Cohort studies    Periodicity    Evaluation studies    Review
收稿日期: 2017-12-10 出版日期: 2018-06-12
CLC:  R181.2  
基金资助: 国家卫生和计划生育委员会科学研究基金-浙江省医药卫生重大科技计划（省部共建重点项目）(WKJ-ZJ-1714);浙江省钱江人才计划(QJD1602026)
通讯作者: 陈天辉     E-mail: tanghj@zjams.com.cn;jiangxy@zjams.com.cn;t.chen@zjams.com.cn
作者简介: 唐慧娟(1979-), 女, 主管药师, 主要从事肿瘤流行病学、药物流行病学研究; E-mail:tanghj@zjams.com.cn; https://orcid.org/0000-0002-3589-4943|蒋曦依(1991-), 女, 硕士, 研究实习员, 主要从事肿瘤流行病学研究; E-mail:jiangxy@zjams.com.cn; https://orcid.org/0000-0002-5560-0316
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
唐慧娟
蒋曦依
楼建林
陈天辉

引用本文:

唐慧娟,蒋曦依,楼建林,陈天辉. 基于人群的肿瘤登记数据评估患者生存的方法学研究进展[J]. 浙江大学学报（医学版）, 2018, 47(1): 104-109.

TANG Huijuan,JIANG Xiyi,LOU Jianlin,CHEN Tianhui. Methodology for survival assessment of cancer patients using population-based cancer registration data. J Zhejiang Univ (Med Sci), 2018, 47(1): 104-109.

链接本文:

http://www.zjujournals.com/med/CN/10.3785/j.issn.1008-9292.2018.02.15    或    http://www.zjujournals.com/med/CN/Y2018/V47/I1/104

表 1  队列法和周期分析法感兴趣时期示意图
表 2  基于模型的周期分析法示意图
1 ZENG H , ZHENG R , GUO Y et al. Cancer survival in China, 2003-2005:a population-based study[J]. Int J Cancer, 2015, 136 (8): 1921- 1930
doi: 10.1002/ijc.29227
2 CHEN W , ZHENG R , BAADE P D et al. Cancer statistics in China, 2015[J]. CA Cancer J Clin, 2016, 66 (2): 115- 132
doi: 10.3322/caac.21338
3 LUO J , XIAO L , WU C et al. The incidence and survival rate of population-based pancreatic cancer patients:Shanghai Cancer Registry 2004-2009[J]. PLoS One, 2013, 8 (10): e76052
doi: 10.1371/journal.pone.0076052
4 BRENNER H , FRANCISCI S , DE ANGELIS R et al. Long-term survival expectations of cancer patients in Europe in 2000-2002[J]. Eur J Cancer, 2009, 45 (6): 1028- 1041
doi: 10.1016/j.ejca.2008.11.005
5 SANT M , ALLEMANI C , BERRINO F et al. Breast carcinoma survival in Europe and the United States[J]. Cancer, 2004, 100 (4): 715- 722
doi: 10.1002/cncr.v100:4
6 项永兵 . 肿瘤流行病学研究资料的统计分析[J]. 中华流行病学杂志, 1999, 19 (3): 180- 183
XIANG Yongbing . Statistical analysis of epidemiological data on cancer[J]. Chinese Journal of Epidemiology, 1999, 19 (3): 180- 183
7 BRENNER H , GEFELLER O . An alternative approach to monitoring cancer patient survival[J]. Cancer, 1996, 78 (9): 2004- 2010
doi: 10.1002/(ISSN)1097-0142
8 BRENNER H , GEFELLER O , HAKULINEN T . A computer program for period analysis of cancer patient survival[J]. Eur J Cancer, 2002, 38 (5): 690- 695
doi: 10.1016/S0959-8049(02)00003-5
9 张华, 曹志刚, 柳光宇 et al. 队列法、完全法和现时生存分析方法在乳腺癌随访研究中的应用[J]. 肿瘤, 2014, 34 (6): 550- 556
ZHANG Hua , CAO Zhigang , LIU Guangyu et al. Use of cohort analysis, complete analysis and period analysis in estimating long-term survival of breastcancer[J]. Tumor, 2014, 34 (6): 550- 556
doi: 10.3781/j.issn.1000-7431.2014.06.012
10 BRENNER H , S?DERMAN B , HAKULINEN T . Use of period analysis for providing more up-to-date estimates of long-term survival rates:empirical evaluation among 370, 000 cancer patients in Finland[J]. Int J Epidemiol, 2002, 31 (2): 456- 462
doi: 10.1093/intjepid/31.2.456
11 BRENNER H , HAKULINEN T . Up-to-date and precise estimates of cancer patient survival:model-based period analysis[J]. Am J Epidemiol, 2006, 164 (7): 689- 696
doi: 10.1093/aje/kwj243
12 BRENNER H , HAKULINEN T . Maximizing the benefits of model-based period analysis of cancer patient survival[J]. Cancer Epidemiol Biomarkers Prev, 2007, 16 (8): 1675- 1681
doi: 10.1158/1055-9965.EPI-06-1046
13 BRENNER H , GONDOS A , PULTE D . Expected long-term survival of patients diagnosed with multiple myeloma in 2006-2010[J]. Haematologica, 2009, 94 (2): 270- 275
doi: 10.3324/haematol.13782
14 GONDOS A , BRAY F , BREWSTER D H et al. Recent trends in cancer survival across Europe between 2000 and 2004:a model-based period analysis from 12 cancer registries[J]. Eur J Cancer, 2008, 44 (10): 1463- 1475
doi: 10.1016/j.ejca.2008.03.010
15 GONDOS A , BRAY F , HAKULINENT et al. Trends in cancer survival in 11 European populations from 1990 to 2009:a model-based analysis[J]. Ann Oncol, 2009, 20 (3): 564- 573
16 GONDOS A , HOLLECZEK B , ARNDT V et al. Trends in population-based cancer survival in Germany:to what extent does progress reach older patients?[J]. Ann Oncol, 2007, 18 (7): 1253- 1259
doi: 10.1093/annonc/mdm126
17 GONDOS A , KRILAVICIUTE A , SMAILYTE G et al. Cancer surveillance using registry data:Results and recommendations for the Lithuanian national prostate cancer early detection programme[J]. Eur J Cancer, 2015, 51 (12): 1630- 1637
doi: 10.1016/j.ejca.2015.04.009
18 SIRRI E , CASTRO F A , KIESCHKE J et al. Recent trends in survival of patients with pancreatic cancer in germany and the United States[J]. Pancreas, 2016, 45 (6): 908- 914
doi: 10.1097/MPA.0000000000000588
19 BRENNER H , GONDOS A , ARNDT V . Recent major progress in long-term cancer patient survival disclosed by modeled period analysis[J]. J Clin Oncol, 2007, 25 (22): 3274- 3280
doi: 10.1200/JCO.2007.11.3431
20 马雅婷, 连士勇, 刘志才 et al. 河南省林州市食管癌人群现时生存分析[J]. 中华预防医学杂志, 2009, 43 (12): 1100- 1104
MA Yating , LIAN Shiyong , LIU Zhicai et al. Period survival analysis of esophageal cancer in Linzhou city of Henan province[J]. Chinese Journal of Preventive Medicine, 2009, 43 (12): 1100- 1104
doi: 10.3760/cma.j.issn.0253-9624.2009.12.012
21 马雅婷, 连士勇, 刘志才 et al. 河南省林州市人群胃癌的现时生存分析[J]. 肿瘤, 2009, 29 (7): 650- 653
MA Yating , LIAN Shiyong , LIU Zhicai et al. Period survival analysis of stomach cancer in the population of Linzhou city of Henan province[J]. Tumor, 2009, 29 (7): 650- 653
22 张欣峰, 娄清涛, 陆建邦 et al. 现时生存分析方法的应用实践与评价[J]. 中国卫生统计, 2011, 28 (1): 26- 28
ZHANG Xinfeng , LOU Qingtao , LU Jianbang et al. The application and evaluation of period survival analysis[J]. Chinese Journal of Health Statistics, 2011, 28 (1): 26- 28
[1] 陈蓉, 何永超, 张放, 陆殷昊, 何懿. 疾病预防控制机构卫生应急能力评估指标体系构建[J]. 浙江大学学报（医学版）, 2018, 47(2): 137-142.
[2] 蒋曦依, 李璐, 唐慧娟, 陈天辉. 结直肠癌高危人群多因素风险预测模型及评价[J]. 浙江大学学报（医学版）, 2018, 47(2): 194-200.
[3] 党莹, 林瑜亮, 孙红军, 孙建军, 李长栋, 荔志云. 异甘草素通过下调基质金属蛋白酶抑制人脑胶质瘤干细胞迁移和侵袭[J]. 浙江大学学报（医学版）, 2018, 47(2): 181-186.
[4] 潘宗富, 方琦璐, 张轶雯, 李莉, 黄萍. 基于生物信息学的未分化甲状腺癌关键发病机制及其潜在干预靶点研究[J]. 浙江大学学报（医学版）, 2018, 47(2): 187-193.
[5] 杨涛, 李傅冬, 何凡. 浙江省人感染H7N9禽流感疫情半定量风险评估[J]. 浙江大学学报（医学版）, 2018, 47(2): 131-136.
[6] 何玉贤, 郑良荣. 脊髓电刺激对心肌缺血和心肌梗死作用的研究进展[J]. 浙江大学学报（医学版）, 2018, 47(2): 201-206.
[7] 吕丹丹, 应可净. 自噬在肺动脉高压发生和发展中的调节作用[J]. 浙江大学学报（医学版）, 2018, 47(2): 207-212.
[8] 蒋滟蕲, 杨雅兰, 杨婷, 李玥伶, 陈莉玲, 燕锦, 杨艳芳. UCP2 rs659366位点多态性与结直肠癌术后患者生存结局的关系[J]. 浙江大学学报（医学版）, 2018, 47(2): 143-149.
[9] 刘婷婷,王凌霄,杨晓辉,姚智卿,蔡慧珍. MyD88非依赖性信号通路在枸杞多糖抑制糖尿病小鼠肿瘤坏死因子α中的作用[J]. 浙江大学学报（医学版）, 2018, 47(1): 35-40.
[10] 凌静,李红蕊,陈玮琳. 蛋白泛素化修饰调控炎性肠疾病发生和发展的研究进展[J]. 浙江大学学报（医学版）, 2018, 47(1): 82-88.
[11] 丁京京,卢韵碧. 受体相互作用蛋白家族在炎症中的作用研究进展[J]. 浙江大学学报（医学版）, 2018, 47(1): 89-96.
[12] 谢娴,徐小方,王琪,卢韵碧,吴明,张纬萍. FK866对非小细胞肺癌细胞迁移的影响[J]. 浙江大学学报（医学版）, 2018, 47(1): 1-9.
[13] 张毓川,陈玮. Vav1对T细胞的调控作用及其与相关疾病的关系[J]. 浙江大学学报（医学版）, 2018, 47(1): 75-81.
[14] 王佳静,谷海瀛. 幽门螺杆菌的基因分型技术及其应用[J]. 浙江大学学报（医学版）, 2018, 47(1): 97-103.
[15] 杨静娟,吴峰峰,陈江华,杨毅. 脓毒性急性肾损伤小鼠线粒体DNA损伤修复相关基因的筛选[J]. 浙江大学学报（医学版）, 2018, 47(1): 41-50.