Semiparametric copula-based regression modeling of semi-competing risks data

References

• Albert, J. M., D. D. Liu, Y. Shen, I.-W. Pan, Y. T. Shih, K. E. Hoffman, T. A. Buchholz, S. H. Giordano, and B. D. Smith. 2012. Nomogram to predict the benefit of radiation for older patients with breast cancer treated with conservative surgery. Journal of Clinical Oncology 30 (23):2837–43. doi:10.1200/JCO.2011.41.0076.
   PubMed Web of Science ®Google Scholar
• Chen, M. C., and K. Bandeen-Roche. 2005. A diagnostic for association in bivariate survival models. Lifetime Data Analysis 11 (2):245–64. doi:10.1007/s10985-004-0386-8.
   PubMed Web of Science ®Google Scholar
• Chen, Y. H. 2012. Maximum likelihood analysis of semicompeting risks data with semiparametric regression models. Lifetime Data Analysis 18 (1):36–57. doi:10.1007/s10985-011-9202-4.
   PubMed Web of Science ®Google Scholar
• Chubak, J., O. Yu, G. Pocobelli, L. Lamerato, J. Webster, M. N. Prout, M. Ulcickas Yood, W. E. Barlow, and D. S. Buist. 2012. Administrative data algorithms to identify second breast cancer events following early-stage invasive breast cancer. Journal of the National Cancer Institute 104 (12):931–40. doi:10.1093/jnci/djs233.
   PubMedGoogle Scholar
• Ding, A. A., G. Shi, W. Wang, and J. J. Hsieh. 2009. Marginal regression analysis for semi-competing risks data under dependent censoring. Scandinavian Journal of Statistics 36 (3):481–500. doi:10.1111/j.1467-9469.2008.00635.x.
   Web of Science ®Google Scholar
• Early Breast Cancer Trialists’ Collaborative Group (EBCTCG), Darby, S., P. McGale, C. Correa, C. Taylor, R. Arriagada, M. Clarke, D. Cutter, C. Davies, M. Ewertz, J. Godwin, et al. 2011. Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: Meta-analysis of individual patient data for 10,801 women in 17 randomised trials. Lancet 378:1707–16.
   PubMed Web of Science ®Google Scholar
• Fine, J. P., and R. J. Gray. 1999. A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association 94 (446):496–509. doi:10.1080/01621459.1999.10474144.
   Web of Science ®Google Scholar
• Fine, J. P., H. Jiang, and R. J. Chappell. 2001. On semi-competing risks data. Biometrika 88 (4):907–19. doi:10.1093/biomet/88.4.907.
   Web of Science ®Google Scholar
• Hsieh, J. J., and Y. T. Huang. 2012. Regression analysis based on conditional likelihood approach under semi-competing risks data. Lifetime Data Analysis 18 (3):302–20. doi:10.1007/s10985-012-9219-3.
   PubMed Web of Science ®Google Scholar
• Leconte, E., S. Poiraud-Casanova, and C. Thomas-Agnan. 2002. Smooth conditional distribution function and quantiles under random censorship. Lifetime Data Analysis 8 (3):229–46. doi:10.1023/A:1015897720112.
   PubMed Web of Science ®Google Scholar
• Lee, K. H., S. Haneuse, D. Schrag, and F. Dominici. 2015. Bayesian semi-parametric analysis of semi-competing risks data: Investigating hospital readmission after a pancreatic cancer diagnosis. Journal of the Royal Statistical Society. Series C, Applied Statistics 64 (2):253–73. doi:10.1111/rssc.12078.
   PubMed Web of Science ®Google Scholar
• National Comprehensive Cancer Network (NCCN). 2011. Clinical practice guidelines in oncology: Breast cancer (Version 2). Fort Washington, PA: National Comprehensive Cancer Network.
   Google Scholar
• Peng, L., and J. P. Fine. 2005. Regression analysis of semi-competing risks data. Technical Report 1097, Department of Statistics, University of Wisconsin, Madison.
   Google Scholar
• Peng, L., and J. P. Fine. 2007. Regression modeling of semicompeting risks data. Biometrics 63 (1):96–108. doi:10.1111/j.1541-0420.2006.00621.x.
   PubMed Web of Science ®Google Scholar
• Punglia, R. S., A. M. Saito, B. A. Neville, C. C. Earle, and J. C. Weeks. 2010. Impact of interval from breast conserving surgery to radiotherapy on local recurrence in older women with breast cancer: Retrospective cohort analysis. BMJ (Clinical Research ed.) 340:c845. doi:10.1136/bmj.c845.
   PubMed Web of Science ®Google Scholar
• Scheike, T. H., and M.-J. Zhang. 2008. Flexible competing risks regression modeling and goodness-of-fit. Lifetime Data Analysis 14 (4):464–83. doi:10.1007/s10985-008-9094-0.
   PubMed Web of Science ®Google Scholar
• Shih, J. H., and T. A. Louis. 1995. Inferences on the association parameters in copula models for bivariate survival data. Biometrics 51 (4):1384–99. doi:10.2307/2533269.
   PubMed Web of Science ®Google Scholar
• Smith, B. D., C. P. Gross, G. L. Smith, D. H. Galusha, J. E. Bekelman, and B. G. Haffty. 2006. Effectiveness of radiation therapy for older women with early breast cancer. JNCI: Journal of the National Cancer Institute 98 (10):681–90. doi:10.1093/jnci/djj186.
   PubMedGoogle Scholar
• Wang, H. J., and L. Wang. 2014. Quantile regression analysis of length-biased survival data. Statistics 3 (1):31–47. doi:10.1002/sta4.42.
   Google Scholar
• Xu, J., J. D. Kalbfleisch, and B. Tai. 2010. Statistical analysis of illness-death processes and semicompeting risks data. Biometrics 66 (3):716–25. doi:10.1111/j.1541-0420.2009.01340.x.
   PubMed Web of Science ®Google Scholar
• Zhou, R., H. Zhu, M. Bondy, and J. Ning. 2016. Semiparametric model for semi-competing risks data with application to breast cancer study. Lifetime Data Analysis 22 (3):456–71. doi:10.1007/s10985-015-9344-x.
   PubMed Web of Science ®Google Scholar
• Zhou, R., H. Zhu, M. Bondy, and J. Ning. 2017. Analyzing semi-competing risks data with missing cause of informative terminal event. Statistics in Medicine 36 (5):738–53. doi:10.1002/sim.7161.
   PubMed Web of Science ®Google Scholar