In medical research, a dynamic treatment regime (DTR), adaptive intervention, or adaptive treatment strategy is a set of rules for choosing effective treatments for individual patients. Historically, medical research and the practice of medicine tended to rely on an acute care model for the treatment of all medical problems, including chronic illness. Treatment choices made for a particular patient under a dynamic regime are based on that individual's characteristics and history, with the goal of optimizing his or her long-term clinical outcome. A dynamic treatment regime is analogous to a policy in the field of reinforcement learning, and analogous to a controller in control theory. While most work on dynamic treatment regimes has been done in the context of medicine, the same ideas apply to time-varying policies in other fields, such as education, marketing, and economics.
^Wagner E. H.; Austin B. T.; Davis C.; Hindmarsh M.; Schaefer J.; Bonomi A. (2001). "Improving Chronic Illness Care: Translating Evidence Into Action". Health Affairs. 20 (6): 64–78. doi:10.1377/hlthaff.20.6.64. PMID11816692.
Diaz, Francisco J.; Cogollo, Myladis R.; Spina, Edoardo; Santoro, Vincenza; Rendon, Diego M.; Leon, jose de (2012), "Drug Dosage Individualization Based on a Random-Effects Linear Model", Journal of Biopharmaceutical Statistics, 22:3: 463–484, doi:10.1080/10543406.2010.547264, PMID22416835
Diaz, Francisco J.; Yeh, Hung-Weh; Leon, Jose de (2012), "Role of Statistical Random-Effects Linear Models in Personalized Medicine", Current Pharmacogenomics and Personalized Medicine, 10 (1): 22–32, doi:10.2174/1875692111201010022 (inactive 2015-01-12), PMC3580802, PMID23467392
Banerjee, A.; Tsiatis, A. A. (2006), "Adaptive two-stage designs in phase II clinical trials", Statistics in Medicine, 25 (19): 3382–3395, doi:10.1002/sim.2501, PMID16479547
Collins, L. M.; Murphy, S. A.; Nair, V.; Strecher, V. (2005), "A strategy for optimizing and evaluating behavioral interventions", Annals of Behavioral Medicine, 30: 65–73, doi:10.1207/s15324796abm3001_8 (inactive 2015-01-12)
Guo, X.; Tsiatis, A. A. (2005), "Estimation of survival distributions in two-stage randomization designs with censored data", International Journal of Biostatistics, 1 (1), doi:10.2202/1557-4679.1000
Hernán, Miguel A.; Lanoy, Emilie; Costagliola, Dominique; Robins, James M. (2006), "Comparison of Dynamic Treatment Regimes via Inverse Probability Weighting", Basic & Clinical Pharmacology & Toxicology, 98 (3): 237–242, doi:10.1111/j.1742-7843.2006.pto_329.x
Lokhnygina, Y; Tsiatis, A. A. (2008), "Optimal two-stage group sequential designs", Journal of Statistical Planning and Inference, 138 (2): 489–499, doi:10.1016/j.jspi.2007.06.011
Lunceford, J. K.; Davidian, M.; Tsiatis, A. A. (2002), "Estimation of survival distributions of treatment policies in two-stage randomization designs in clinical trials", Biometrics, 58 (1): 48–57, doi:10.1111/j.0006-341x.2002.00048.x, PMID11890326
Robins, James M. (2004), "Optimal structural nested models for optimal sequential decisions", in Lin, D. Y.; Heagerty, P. J., Proceedings of the Second Seattle Symposium on Biostatistics, Springer, New York, pp. 189–326
Robins, James M. (1986), "A new approach to causal inference in mortality studies with sustained exposure periods-application to control of the healthy worker survivor effect", Computers and Mathematics with Applications, 14: 1393–1512
Robins, James M. (1987), "Addendum to 'A new approach to causal inference in mortality studies with sustained exposure periods-application to control of the healthy worker survivor effect'", Computers and Mathematics with Applications, 14 (9–12): 923–945, doi:10.1016/0898-1221(87)90238-0
Wagner, E. H.; Austin, B. T.; Davis, C.; Hindmarsh, M.; Schaefer, J.; Bonomi, A. (2001), "Improving Chronic Illness Care: Translating Evidence Into Action", Health Affairs, 20 (6): 64–78, doi:10.1377/hlthaff.20.6.64, PMID11816692
Wahed, A.. S.; Tsiatis, A. A. (2004), "Optimal estimator for the survival distribution and related quantities for treatment policies in two-stage randomization designs in clinical trials", Biometrics, 60 (1): 124–133, doi:10.1111/j.0006-341X.2004.00160.x, PMID15032782
Watkins, C. J. C. H. (1989), "Learning from Delayed Rewards", PhD thesis, Cambridge University, Cambridge, England