We asked three leading researchers in the area of dynamic treatment regimes to share their stories on how they became interested in this topic and their perspectives on the most important opportunities and challenges for the future.
ArmstrongAJGarrett-MayerELEisenbergerM. Response: Re: Adaptive therapy for androgen independent prostate cancer: a randomized selection trial of four regimens. JNCI2008; 100: 682–683.
2.
ThallPFLogothetisCPagliaroLC, et al.Adaptive therapy for androgen-independent prostate cancer: a randomized selection trial of four regimens. J Natl Cancer Inst2007; 99: 1613–1622.
3.
ZhaoYFKosorokMRZengD. Reinforcement learning design for cancer clinical trials. Stat Med2009; 28: 3294–3315.
4.
ZhaoYFZengDSocinskiMA, et al.Reinforcement learning strategies for clinical trials in non-small cell lung cancer. Biometrics2011; 67: 1422–1433.
5.
RobinsJMHernanMABrumbackB. Marginal. Structural models and causal inference in epidemiology. Epidemiology2000; 11: 550–560.
6.
Lee JH, Thall PF, Ji Y, et al. Bayesian dose-finding in two treatment cycles based on the joint utility of efficacy and toxicity. J Am Statist Assoc 2015; 110: 711–722.
