JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2017, Vol. 55 ›› Issue (6): 42-46.doi: 10.6040/j.issn.1671-7554.0.2017.368

Previous Articles     Next Articles

Cause-specific hazard model and its applications in health risk assessment

WANG Tingting1,2, WANG Jintao1,2,3, YUAN Zhongshang1,2, SU Ping1,2, XUE Fuzhong1,2   

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

PDF (PC)

620

Abstract: Objective To introduce the theory of cause-specific 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 cause-specific hazard model from the perspective of modeling principle and parameter estimator, and further evaluate the efficiency and application based on the Shandong Multi-center cohort of hemorrhagic cerebral apoplexy. Results Under the framework of competing risk, the cause-specific hazard model constructed the cox-type survival model for each cause-specific endpoint. The parameter estimator can be obtained from the partial likelihood and thus have good properties, this can make sure that the absolute risk is accurate. Based on the Shandong Multi-center cohort of hemorrhagic cerebral apoplexy, it showed a good practicability in risk assessment of stroke death. Conclusion When competing risk can not be ignored, the cause-specific hazard model are preferred in health risk assessment.

Key words: Health risk assessment, Competing risks, Cox model, Cause-specific hazard model

CLC Number: 

  • 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, Scott. 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] Cox DR. Regression models and life-tables[J]. J R Stat Soc, 1972, 34(2):187-220.
[15] 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.
[16] 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.
[17] Therneau TM. Proceedings of the first Seattle symposium in biostatistics: survival analysis[J]. 1997, 1205(473): 51-84. doi:10.1007/978-1-4684-6316-3.
[18] 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.
[19] 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.
[20] Sengupta D. Review of modeling survival data: extending the Cox model[J]. Technometrics, 2012, 44(1):85-86.
[21] Venables WN, Ripley BD. Modern applied statistics with S-PLUS[M]. Dordrecht:Springer Science & Business Media, 2013.
[22] 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.
[23] Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk[J]. JASA, 1999, 94(446): 496-509.
[24] Putter H, Fiocco M, Geskus RB. Tutorial in biostatistics: competing risks and multi-state models[J]. Stat Med, 2007, 26(11): 2389-2430.
[25] Ruan PK, Gray RJ. Analyses of cumulative incidence functions via non-parametric multiple imputation[J]. Stat Med, 2008, 27(27): 5709-5724.
[26] Allignol A, Beyersmann J. Software for fitting nonstandard proportional subdistribution hazards models[J]. Biostatistics, 2010, 11(4):674-675.
[27] 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.
[28] 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] CAO Jin, JI Xiaokang, SUN Xiubin, JIANG Zheng, XUE Fuzhong. The relationship between γ-glutamyltransferase and hyperuricemia: a cohort study [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 124-128.
[2] WANG Jintao, SU Ping, YUAN Zhongshang, XUE Fuzhong. Sub-distribution hazard model and its applications in health risk assessment [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 37-41.
[3] XU Yibo, JI Xiaokang, LI Xiangyi, SHEN Zhenwei, XUE Fuzhong. Analysis on the relationship between urine pH and metabolic syndrome [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(12): 82-85.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd