Estimating the optimal dynamic antipsychotic treatment regime: Evidence from the sequential multiple assignment randomized CATIE Schizophrenia Study

By Susan M. Shortreed, Erica E. Moodie. 2012

48 citations recorded by the source corpus.

Summary. Treatment of schizophrenia is notoriously difficult and typically requires personalized adaption of treatment because of lack of efficacy of treatment, poor adherence or intolerable side effects. The Clinical Antipsychotic Trials in Intervention Effectiveness schizophrenia study is a sequential multiple‐assignment randomized trial comparing the typical antipsychotic medication perphenazine with several newer atypical antipsychotics. The paper describes the marginal structural modelling method for estimating optimal dynamic treatment regimes and applies the approach to this schizophrenia study. Missing data and valid estimation of confidence intervals are also addressed.

Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation (2018, methodology): “…of dealing with delayed reward and inferring optimal policy based on non-optimal prescription behaviors, a set of reinforcement learning methods have been adapted to generate optimal DTR for life-threatening diseases, such as schizophrenia, non-small cell lung cancer, and sepsis [25, 31, 42].”
Adaptive Interventions in Child and Adolescent Mental Health (2016, background): “…regimens” (Chakraborty & Moodie, 2013; Laber, Lizotte, Qian, Pelham, & Murphy, 2014; Lavori & Dawson, 2004; Murphy, 2003; Murphy & Almirall, 2009; Shortreed & Moodie, 2012), “treatment policies” (Lunceford, Davidian, & Tsiatis, 2002; Wahed & Tsiatis, 2004), or “multistage” or “multicourse…”
Precision Medicine. (2019, background): “…regimes that occur more generally in statistical modeling and thus we will not discuss them here; e.g., missing data (Shortreed et al 2011; Shortreed and Moodie 2012; Shortreed et al 2014; Kosorok and Moodie 2016); measurement error (Shani et al 2013), and model-building (Biernot and…”
Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules (2017, methodology): “We selected tailoring covariates based on clinical expertise and prior analyses (Shortreed and Moodie, 2012; Shortreed et al., 2014).”