您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(医学版)》

山东大学学报(医学版) ›› 2017, Vol. 55 ›› Issue (6): 37-41.doi: 10.6040/j.issn.1671-7554.0.2017.367

• • 上一篇    下一篇

部分分布竞争风险模型及其在健康风险评估中的应用

王金涛1,2,3,苏萍2,3,袁中尚2,3,薛付忠2,3   

  1. 1. 山东大学(威海)数学与统计学院统计学系, 山东 威海 264200;2. 山东大学公共卫生学院生物统计学系, 山东 济南 250012;3. 山东大学齐鲁生物医学大数据研究中心, 山东 济南 250012
  • 收稿日期:2017-04-27 出版日期:2017-06-10 发布日期:2017-06-10
  • 通讯作者: 薛付忠. E-mail:xuefzh@sdu.edu.cn E-mail:xuefzh@sdu.edu.cn
  • 基金资助:
    山东大学青年学者未来计划建设项目(2016WLJH23)

Sub-distribution hazard model and its applications in health risk assessment

WANG Jintao1,2,3, SU Ping2,3, YUAN Zhongshang2,3, XUE Fuzhong2,3   

  1. 1. Department of Statistics, School of Mathematics and Statistics, Shandong University, Weihai 264200, Shandong, China;
    2. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    3. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China
  • Received:2017-04-27 Online:2017-06-10 Published:2017-06-10

摘要: 目的 介绍部分分布竞争风险模型原理及其在健康风险评估中的应用。 方法 介绍部分分布竞争风险模型如何解决慢性病风险评估中的竞争风险问题,进一步结合山东省多中心缺血性脑卒中病例随访队列,阐明部分分布竞争风险模型的实用性。 结果 部分分布风险模型充分考虑了竞争风险的影响,将竞争结局融入风险集(risk set)定义,而不是武断地将竞争结局的出现当作删失值处理,其建模效果优于传统的Cox模型。依托山东多中心缺血性脑卒中病例随访队列,将其用于缺血性脑卒中死亡结局风险评估,显示出良好的实用性。 结论 部分分布竞争风险模型能够建立协变量和累积发病率函数间的直接关系,较好地处理了健康风险评估的竞争风险问题,具有很强的实用性。

关键词: 健康风险评估, 竞争风险, Cox模型, 部分分布竞争风险模型

Abstract: Objective To introduce the theory of sub-distribution hazard model and its applications in health risk assessment. Methods Given that competing risks are commonly encountered in health risk assessment, we have introduced the sub-distribution hazard model, and further evaluate itsefficiency and application based on the Shandong Multi-center cohort of hemorrhagic cerebral apoplexy. Results Under the framework of competing risk, the sub-distribution hazard model took the competing endpoint into the construction of the risk set, other than treating the competing endpoint simply as the censoring. Thus, it can have better performance than the traditional Cox model. Based on the Shandong Multi-center cohort of hemorrhagic cerebral apoplexy, it showed a good practicability in risk assessment of stroke death. Conclusion The sub-distribution hazard model can directly link the covariates with the cumulative incidence function, and can efficiently deal with the competing risk problem.

Key words: Health risk assessment, Cox model, Sub-distribution hazard model, Competing risks

中图分类号: 

  • R195
[1] Tomaselli, Gordon F. Prevention of cardiovascular disease and stroke: meeting the challenge[J]. JAMA, 2011, 306(19):2147-2148.
[2] Pendlebury, Sarah T, Peter M. Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: a systematic review and meta-analysis[J]. Lancet Neurol, 2009, 8(11):1006-1018.
[3] Kinlay S. Changes in stroke epidemiology, prevention, and treatment[J]. Circulation, 2011, 124(19): 494-496.
[4] Jia Q Liu L, Wang Y. Risk factors and prevention of stroke in the Chinese population[J]. J Stroke Cerebrovasc Dis, 2011, 20(5):395-400.
[5] Lengeler C, Armstrong-Schellenberg J, D'alessandro U, et al. Relative versus absolute risk of dying reduction after using insecticide-treated nets for malaria control in Africa[J]. Trop Med Int Health, 1998, 3(4):286-290.
[6] Easton DF, Peto J, Babiker AG. Floating absolute risk: an alternative to relative risk in survival and case-control analysis avoiding an arbitrary reference group[J]. Stat Med, 1991, 10(7):1025-1035.
[7] Halpern MT, Gillespie BW, Warner KE. Patterns of absolute risk of lung cancer mortality in former smokers[J]. J Natl Cancer Inst, 1993, 85(6):457-464.
[8] Malenka DJ, Baron JA, Johansen S, et al. The framing effect of relative and absolute risk[J]. J Gen Intern Med, 1993, 8(10):543-548.
[9] Plummer M. Improved estimates of floating absolute risk[J]. Stat Med, 2004, 23(1):93-104.
[10] Seshadri S, Wolf PA. Lifetime risk of stroke and dementia: current concepts, and estimates from the Framingham Study[J]. Lancet Neurol, 2007, 6(12):1106-1114.
[11] Gail MH. Personalized estimates of breast cancer risk in clinical practice and public health[J]. Stat Med, 2011, 30(10):1090-1104.
[12] Prentice RL, Kalbfleisch JD, Peterson Jr AV, et al. The analysis of failure times in the presence of competing risks[J]. Biometrics, 1978, 34(4):541-554.
[13] Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk[J]. Ann Stat, 1988, 16(3):1141-1154.
[14] Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk[J]. JASA, 1999, 94(446):496-509.
[15] Cox DR. Regression models and life-tables[J]. J R Stat Soc, 1972, 34(2):187-220.
[16] Shen Q, Jin B, Min J, et al. Cox model and its application to prognostic analysis of malignant melanoma[J]. Journal of Nanjing Railway Medical College, 1987, 2(9):871-879.
[17] Gamel JW, McLean IW, Greenberg RA. Interval-by-interval cox model analysis of 3680 cases of intraocular melanoma shows a decline in the prognostic value of size and cell type over time after tumor excision[J]. Cancer, 1988, 61(3):574-579.
[18] Therneau TM. Proceedings of the first Seattle symposium in biostatistics: survival analysis[J]. 1997: 51-84. doi:10.1007/978-1-4684-6316-3
[19] Chevret S. Logistic or Cox model to identify risk factors of nosocomial infection: still a controversial issue[J]. Intensive Care Med, 2001, 27(10):1559-1560.
[20] Guo X, Chen M, Ding L, et al. Application of Cox model in coagulation function in patients with primary liver cancer[J]. Hepatogastroenterology, 2010, 58(106):326-330.
[21] Beyersmann J, Schumacher M. Time-dependent covariates in the proportional subdistribution hazards model for competing risks[J]. Biostatistics, 2008, 9(4):765-776.
[22] Beyersmann J, Dettenkofer M, Bertz H, et al. A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards[J]. Stat Med, 2007, 26(30):5360-5369.
[23] Grambauer N, Schumacher M, Beyersmann J. Proportional subdistribution hazards modeling offers a summary analysis, even if misspecified[J]. Stat Med, 2010, 29(7-8):875-884.
[24] Katsahian S, Resche-Rigon M, Chevret S, et al. Analysing multicentre competing risks data with a mixed proportional hazards model for the subdistribution[J]. Stat Med, 2006, 25(24): 4267-4278.
[25] Li W, Xue X, Long Y. An additive subdistribution hazards model for competing risks data[J]. Commun Stat Theory Methods, 2017. doi:10.1080103610926.2.16.1277759.
[26] Zhou B, Fine J, Laird G. Goodness-of-fit test for proportional subdistribution hazards model[J]. Stat Med, 2013, 32(22):3804-3811.
[27] Therneau T. A package for survival analysis in S. version 2.38; 2015[CP/OL]. URL:http://cran. r-project. org/web/packages/survival/index. html[accessed 2016-06-17] [WebCite Cache ID 6iKkaCcfO] , 2016.
[28] Gray RJ. Modeling survival data: extending the Cox model[J]. JASA, 2002, 44(457):85-86.
[29] Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk[J]. JASA, 1999, 94(446):496-509.
[30] Putter H, Fiocco M, Geskus RB. Tutorial in biostatistics: competing risks and multi-state models[J]. Stat Med, 2007, 26(11):2389-2430.
[31] Ruan PK, Gray RJ. Analyses of cumulative incidence functions via non-parametric multiple imputation[J]. Stat Med, 2008, 27(27):5709-5724.
[32] Allignol A, Beyersmann J. Software for fitting nonstandard proportional subdistribution hazards models[J]. Biostatistics, 2010, 11(4):674-675.
[33] De Wreede LC, Fiocco M, Putter H. The mstate package for estimation and prediction in non-and semi-parametric multi-state and competing risks models[J]. Comput Methods Programs Biomed, 2010, 99(3):261-274.
[34] de Wreede LC, Fiocco M, Putter H. Mstate:an R package for the analysis of competing risks and multi-state models[J]. J Stat Softw, 2011, 38(7):1-30.
[1] 王停停,王金涛,袁中尚,苏萍,薛付忠. 原因别竞争风险模型及其在健康风险评估中的应用[J]. 山东大学学报(医学版), 2017, 55(6): 42-46.
[2] 许艺博,季晓康,李向一,申振伟,薛付忠. 尿液pH与代谢综合征的相关性[J]. 山东大学学报(医学版), 2016, 54(12): 82-85.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 王利红,连方,张宁. 改良Hemistraw与Cryoleaf法对人卵和胚胎玻璃化保存效果的比较[J]. 山东大学学报(医学版), 2009, 47(12): 70 -73 .
[2] 郑妮1,王传新1,邓小梅2,张建1,阚士峰1,张欣1,李伟1,杜鲁涛1. HLA-G在宫颈癌组织中的表达及临床意义[J]. 山东大学学报(医学版), 2010, 48(2): 128 -130 .
[3] 陈锋1,何生松1,吴梅梅1,邱荣元1,杨凯凯1,王鹏2. 不同转染方式对GFP表达质粒在小鼠肝脏的表达影响[J]. 山东大学学报(医学版), 2010, 48(1): 17 -20 .
[4] 张燎1,诸葛春耕1,梅银生2,张君2. 不同正畸力作用下牙周组织中碱性成纤维细胞生长因子表达的实验研究[J]. 山东大学学报(医学版), 2010, 48(1): 34 -37 .
[5] 刘萌1,鲁燕霞1,江虹1,石寿森2,杨乐金1,刘欣1,张茜1,潘芳1. 音乐治疗对应激哮喘大鼠免疫功能的影响[J]. 山东大学学报(医学版), 2010, 48(1): 56 .
[6] 王莎莎,邵杨,张栋,王利江,姜淑娟. TBNA在支气管腔外病变中的临床应用价值[J]. 山东大学学报(医学版), 2010, 48(1): 120 -122 .
[7] 贾欣永,李国栋,董海燕. 2009年山东省消化内镜治疗技术演示研讨会纪要[J]. 山东大学学报(医学版), 2010, 48(1): 164 .
[8] 李国华1,2, 王翠兰1. 高血糖对缺血性脑血管病预后的预测价值[J]. 山东大学学报(医学版), 2010, 48(4): 1 -4 .
[9] 黄坤玲1,王立启2,朱世明2. 伴代谢综合征高血压患者微量白蛋白尿和血清高分子量脂联素的变化[J]. 山东大学学报(医学版), 2010, 48(4): 78 -82 .
[10] 宋静,张超,梁婷,陈富强,侯桂华. 抗MIF单克隆抗体的制备及其放射性碘标记方法[J]. 山东大学学报(医学版), 2010, 48(5): 28 -31 .