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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 |
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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.
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Received: 10 December 2017
Published: 12 June 2018
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Corresponding Authors:
CHEN Tianhui
E-mail: tanghj@zjams.com.cn;jiangxy@zjams.com.cn;t.chen@zjams.com.cn
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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
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
|
|
[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
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