On optimal treatment regimes selection for mean survival time

Statistics in Medicine

Volumn 34, Issue 7, 2015, Pages 1169-1184

  Geng, Yuan ^a   Zhang, Hao Helen ^b   Lu, Wenbin ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b University of Arizona   (United States)

Author keywords

adaptive LASSO; censored regression; mean survival time; optimal treatment regime; variable selection

Indexed keywords

ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; DECISION MAKING; EMPIRICAL RESEARCH; EVALUATION STUDY; FEMALE; HUMAN; KAPLAN MEIER METHOD; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR; MAJOR CLINICAL STUDY; MALE; MEDIAN SURVIVAL TIME; MEDICAL PROCEDURES; OPTIMAL TREATMENT REGIME; OUTCOME ASSESSMENT; PERCENTAGE OF MAKING CORRECT DECISION; POTENTIAL SURVIVAL TIME; PROPENSITY SCORE; RESTRICTED MEAN SURVIVAL TIME; SENSITIVITY ANALYSIS; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS; SURVIVAL RATE; SURVIVAL TIME; TREATMENT INDICATION; TREATMENT RESPONSE; VARIABLE SELECTION; ACQUIRED IMMUNODEFICIENCY SYNDROME; BIOSTATISTICS; CLINICAL TRIAL (TOPIC); COMPUTER SIMULATION; MORTALITY; NONPARAMETRIC TEST; PERSONALIZED MEDICINE; PROCEDURES; REGRESSION ANALYSIS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT;

ACQUIRED IMMUNODEFICIENCY SYNDROME; ANTI-HIV AGENTS; BIOSTATISTICS; CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; HUMANS; KAPLAN-MEIER ESTIMATE; LEAST-SQUARES ANALYSIS; MODELS, STATISTICAL; PRECISION MEDICINE; REGRESSION ANALYSIS; STATISTICS, NONPARAMETRIC; SURVIVAL RATE;

EID: 84919968650     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6397     Document Type: Article

References (31)

1. Watkins CJCH. Learning from delayed rewards. PhD Thesis, King's College, Cambridge, UK, 1989.
2. Watkins CJCH, Dayan P. Q-learning. Machine Learning 1992; 8:279–292.
3. Blatt D, Murphy SA, Zhu J. A-learning for approximate planning. Technical Report 04–63, The Methodology Center, The Pennsylvania State University, University Park, PA, 2004.
4. Murphy SA. Optimal dynamic treatment regimes. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2003; 65:331–355.
5. Robins JM. Optimal structural nested models for optimal sequential decisions. Proceedings of the Second Seattle Symposium on Biostatistics. Springer, 2004.
6. Zhang B, Tsiatis AA, Laber EB, Davidian M. A robust method for estimating optimal treatment regimes. Biometrics 2012; 68:1010–1018.
7. Zhao Y, Zeng D, Rush AJ, Kosorok MR. Estimating individualized treatment rules using outcome weighted learning. Journal of the American Statistical Association 2012; 107:1106–1118.
8. Zhang B, Tsiatis AA, Davidian M, Zhang M, Laber E. Estimating optimal treatment regimes from a classification perspective. Stat 2012; 1:103–114.
9. Hammer SM, Katzenstein DA, Hughes MD, Gundacker H, Schooley RT, Haubrich RH, Henry WK, Lederman MM, Phair JP, Niu M, Hirsch MS, Merigan TC. A trial comparing nucleoside monotherapy with combination therapy in HIV-infected adults with CD4 cell counts from 200 to 500 per cubic millimeter. New England Journal of Medicine 1996; 335:1081–1090.
10. Tibshirani R. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society (Series B) 1996; 58:267–288.
11. Fan J, Li R. Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association 2001; 96:1348–1360.
12. Zou H. The adaptive lasso and its oracle properties. Journal of the American Statistical Association 2006; 101:1418–1429.
13. Gunter L, Zhu J, Murphy SA. Variable selection for qualitative interactions. Statistical Methodology 2011; 8:42–55.
14. Qian M, Murphy SA. Performance guarantees for individualized treatment rules. Annals of Statistics 2011; 39:1180–1210.
15. Lu W, Zhang HH, Zeng D. Variable selection for optimal treatment decision. Statistical Methods in Medical Research 2013; 22:493–504.
16. Rubin DB. Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology 1974; 66:688–701.
17. Cheng SC, Wei LJ, Ying Z. Analysis of transformation models with censored data. Biometrika 1995; 82:835–845.
18. Cheng SC, Wei LJ, Ying Z. Predicting survival probabilities with semiparametric transformation models. Journal of the American Statistical Association 1997; 92:227–235.
19. Fan J, Gijbels I. Censored regression: local linear approximations and their applications. Journal of the American Statistical Association 1994; 89:560–570.
20. Fine JP, Ying Z, Wei LG. On the linear transformation model for censored data. Biometrika 1998; 85:980–986.
21. Koul H, Susarla V, Ryzin JV. Regression analysis with randomly right-censored data. The Annals of Statistics 1981; 9:1276–1288.
22. Zhang HH, Lu W. Adaptive lasso for Cox's proportional hazards model. Biometrika 2007; 94:691–703.
23. Zhang CH. Nearly unbiased variable selection under minimax concave penalty. Annals of Statistics 2010; 38:894–942.
24. Efron B, Hastie T, Johnstone I, Tibshirani R. Least angle regression. Annals of Statistics 2004; 32:407–499.
25. Andersen P, Hansen M, Klein J. Regression analysis of restricted mean survival time based on pseudo-observations. Lifetime Data Analysis 2004; 10:335–350.
26. Zhao H, Tsiatis AA. A consistent estimator for the distribution of quality adjusted survival time. Biometrika 1997; 84:339–348.
27. Zhao H, Tsiatis AA. Efficient estimation of the distribution of quality-adjusted survival time. Biometrics 1997; 55:1101–1107.
28. Tsiatis AA, Davidian M, Zhang M, Lu X. Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: a principled yet flexible approach. Statistics in Medicine 2008; 27:4658–4677.
29. Zhang M, Tsiatis AA, Davidian M. Improving efficiency of inferences in randomized clinical trials using auxiliary covariates. Biometrics 2008; 64:707–715.
30. Huang J, Ma S, Xie H, Zhang CH. A group bridge approach for variable selection. Biometrika 2009; 96:339–355.
31. Zhou N, Zhu J. Group variable selection via a hierarchical lasso and its oracle property. Statistics and Its Interface 2010; 3:557–574.