期刊文献+

病例对照家系研究中发病年龄的家庭相关分析方法 被引量:1

Familial Correlations of Age at Onset in Case-Control Family Study
下载PDF
导出
摘要 目的探讨失效时间的关联测量和病例对照家系研究中发病年龄家庭相关的分析方法。方法分层Cox模型用于估计病例对照家系研究中肝癌发病年龄的交叉比。结果显示先证者和父亲、母亲、同胞间发病年龄的家庭相关有统计学意义,而先证者和配偶间发病年龄的家庭相关没有统计学意义。结论分层Cox模型可用于病例对照家系研究中发病年龄的家庭相关估计。 Objective To explore familial association measure for age at onset in case-control family study. Methods Cross-Ratios (CRs) that were estimated by stratified Cox model were used to measure familial correlation of age at onset in case-control family study for liver cancer. Results Familial correlation of ages at onset between the probands and their father, mother and siblings were statistically significant and that between the probands and their spouses was not statistically significant.Conclusion Familial correlation for ages at onset in case-control family study of chronic disease can be analysed using stratified Cox model.
出处 《中国卫生统计》 CSCD 北大核心 2005年第4期194-196,共3页 Chinese Journal of Health Statistics
基金 国家自然科学基金资助项目(39930160) 复旦大学研究生创新基金(CQF206801)
关键词 病例对照家系研究 发病年龄 家庭相关分析方法 交叉比 Case-control family study, Age at onset Cross ratio, Familial correlation
  • 引文网络
  • 相关文献

参考文献8

  • 1Cox DR. Regression models and life tables (with discussion). J R StatSoc, Ser B, 1972, 34 : 187-220.
  • 2Clayton DG. A model for association in bivariate life tables and its applica-tion in epidemiological studies of familial tendency in chronic disease incidence. Biometrika, 1978, 65 : 141-151.
  • 3Hsh L, Prentice RL, Zhao LP, et al. On dependence estimation using correlated failure time data from case-control family studies. Biometrika,1999, 86:743-753.
  • 4Hsh L, Prentice RL, Stanford JL. Some further results on incorporatingrisk factor information in assessing the dependence between paired failure times arising from casecontrol family studies: an application to prostatecancer. Star in Med, 2002, 21 : 863-876.
  • 5Lin DY. Cox regression analysis of multivariate failure time data: the marginal approach. Star in Med, 1994, 13:2233-2247.
  • 6SAS OnlineDoc, Version 8, SAS/STAT User's Guide.
  • 7Liang KY. Estimating effects of probands' characteristics on familialrisk: I. Adjustment for censoring and correlated ages at onset. Genet Epidemio, 1991, 8 : 329-338.
  • 8Oakes D. Bivariate survival models induced by frailties. J Am Stat Asso,1989, 84: 487-493.

同被引文献11

  • 1Gao YH, Jiang QW, Zhou XF, et al. HBV infection and familial aggregation of liver cancer: An analysis of casecontrol family study[J].Cancer Causes and Control , 2004,15:845 - 850.
  • 2Yu MW, Chang HC, Liaw YF, et al. Familial risk of hepatocellular carcinoma among chronic hepatitis B carriers and their relatives[J]. J Natl Cancer Inst ,2000,92:1 159- 1 164.
  • 3Chan AO, Yuen MF, Lam CM, et al. Prevalence and characteristics of familial hepatocellular carcinoma caused by chronic hepatitis B infection in Hong Kong [J]. Aliment Pharmacol Ther, 2004,19:401 - 6.
  • 4Pankratz VS, Andrade M, Therneau TM. Random-effects Cox proportional hazards model: general variance components methods for time-to-event data[J].Genet Epidemiol, 2005, 28:97 - 11)9.
  • 5Scurrah K J, Palmer LJ, Burton PR. Variance components analysis for pedigree-based censored survival data, using generalized linear mixed models (GLMMs) and Gibbs sampling in BUGS[J]. Genet Epidemiol,2000,19,127 - 148.
  • 6Sargent DJ. A general frame work for random effects survival analysis in the Cox proportional hazards setting [J].Biometrics, 1998,54 : 1486 - 1497.
  • 7Cheng YB,Gao F,Khoo KS. Age at diagnosis and the choice of survival analysis methods in cancer epidemiology[J]. J Clin Epidemiol,2003,56:38 - 43.
  • 8Burton PR, Palmer LJ, Jacobs K, et al. Ascertainment adjustment: where does it take us?[J]. Am J Hum Genet, 2001,67:1 505 - 1 514.
  • 9Burton PR. Comment on " Ascertainment adjustment in complex diseases"[J]. Genet Epidemiol,2002,23:214 - 218.
  • 10Glidden DV, Liang KY. Ascertainment adjustment in complex diseases[J].Genet Epidemiol, 2002,23 : 201 - 208.

引证文献1

二级引证文献2

;
使用帮助 返回顶部