Censored quantile regression for residual lifetimes
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We propose a regression method that studies covariate effects on the conditional quantiles of residual lifetimes at a certain followup time point. This can be particularly useful in cancer studies, where more patients survive cancers initially and a patient’s residual life expectancy is used to compare the efficacy of secondary or adjuvant therapies. The new method provides a consistent estimator that often exhibits smaller standard error in real and simulated examples, compared to the existing method of Jung et al. (2009). It also provides a simple empirical likelihood inference method that does not require estimating the covariance matrix of the estimator or resampling. We apply the new method to a breast cancer study (NSABP Protocol B-04, Fisher et al. (2002)) and estimate median residual lifetimes at various followup time points, adjusting for important prognostic factors.
KeywordsCancer Empirical likelihood Quantile regression Residual lifetime regression Survival analysis Wilks’ theorem
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- Coombes RC, Hall E, Gibson LJ, Paridaens R, Jassem J, Delozier T, Jones S, Alvarez I, Bertelli G, Ortmann O, Coates AS, Bajetta E, Dodwell D, Coleman RE, Fallowfield LJ, Mickiewicz E, Andersen J, Lønning PE, Cocconi G, Stewart A, Stuart N, Snowdon CF, Carpentieri M, Massimini G, Bliss JM, fortheIntergroup Exemestane Study (2004) A randomized trial of exemestane after two to three years of tamoxifen therapy in postmenopausal women with primary breast cancer. N Engl J Med 350(11): 1081–1092CrossRefGoogle Scholar
- Goss PE, Ingle JN, Martino S, Robert NJ, Muss HB, Piccart MJ, Castiglione M, Tu D, Shepherd LE, Pritchard KI, Livingston RB, Davidson NE, Norton L, Perez EA, Abrams JS, Therasse P, Palmer MJ, Pater JL (2003) A randomized trial of letrozole in postmenopausal women after five years of tamoxifen therapy for early-stage breast cancer. N Engl J Med 349(19): 1793–1802CrossRefGoogle Scholar
- Koenker R (2005) Quantile Regression Cambridge University PressGoogle Scholar
- R Development Core Team (2008) R: A language and environment for statistical computing. R Foundation for Statistical Computing, http://www.R-project.org
- Rotnitzky A, Robins JM (2005) Inverse probability weighted estimation in survival analysis 2nd edn. WileyGoogle Scholar
- Zhou M (2011) A wilks thorem for teh censored empirical liklihood of means. Unpublished Manuscript: http://www.ms.uky.edu/~mai/research/Note3.pdf
- Zhou M, Kim M, Bathke A (2011) Empirical likelihood analysis for the heteroscedastic accelerated failure time model. Statistica Sinica (in press)Google Scholar