title: Dynamic treatment regimes for managing chronic health conditions: a statistical perspective.
abstract: Dynamic treatment regimes are an emerging and important methodological area in health research, particularly in the management of chronic health conditions. This paradigm encompasses the ideological shift in research from the acute care model to the chronic care model. It allows individualization of treatment (type, dosage, timing) at each stage of intervention. Constructing evidence-based dynamic treatment regimes requires implementation of cutting-edge design and analysis tools. Here I briefly discuss some of these modern tools, namely the sequential multiple assignment randomized trial (SMART) design and a regression-based analysis approach called Q-learning.
authors.affiliation: Department of Biostatistics, Columbia University, New York, NY 10032, USA. bc2425@columbia.edu
authors.forename: Bibhas
authors.initials: B
authors.lastname: Chakraborty
mesh_terms: D000437:Alcoholism / Q000628:therapy; D002908:Chronic Disease / Q000628:therapy*; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D019317:Evidence-Based Medicine / Q000706:statistics & numerical data*; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012107:Research Design