Literature DB >> 24700536

Personalizing medicine: a review of adaptive treatment strategies.

Michael P Wallace1, Erica E M Moodie.   

Abstract

Much of current pharmacological practice focuses on identifying the single 'best' treatment (or course of treatments) for a particular disease. Recently, however, focus has begun to shift towards a more patient-centric rather than disease-centric approach, where personal characteristics are used to identify the optimal treatment for an individual. Adaptive treatment strategies (also known as dynamic treatment regimes) are part of a rapidly expanding area of research whereby such personalized treatments can be identified. These methods can lead to improved results over standard 'one size fits all' approaches, as well as provide a route to formalizing a common practice of using ad hoc approaches when deciding or updating management plans. Here, we provide an introduction to adaptive treatment strategies, explaining their background, their purpose, and how they can be employed in practice.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Q-learning; adaptive treatment strategies; dynamic treatment regimes; personalized medicine; pharmacoepidemiology; sequential randomization

Mesh:

Year:  2014        PMID: 24700536     DOI: 10.1002/pds.3606

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  5 in total

1.  Quantile-Optimal Treatment Regimes.

Authors:  Lan Wang; Yu Zhou; Rui Song; Ben Sherwood
Journal:  J Am Stat Assoc       Date:  2018-06-08       Impact factor: 5.033

2.  Identifying optimal level-of-care placement decisions for adolescent substance use treatment.

Authors:  Denis Agniel; Daniel Almirall; Q Burkhart; Sean Grant; Sarah B Hunter; Eric R Pedersen; Rajeev Ramchand; Beth Ann Griffin
Journal:  Drug Alcohol Depend       Date:  2020-04-28       Impact factor: 4.492

3.  Using dynamic treatment regimes to understand erythropoietin-stimulating agent hyporesponsiveness.

Authors:  Ari H Pollack; Assaf P Oron; Joseph T Flynn; Raj Munshi
Journal:  Pediatr Nephrol       Date:  2018-04-04       Impact factor: 3.714

Review 4.  Sample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome.

Authors:  Nicholas J Seewald; Kelley M Kidwell; Inbal Nahum-Shani; Tianshuang Wu; James R McKay; Daniel Almirall
Journal:  Stat Methods Med Res       Date:  2019-10-01       Impact factor: 3.021

Review 5.  A scoping review of studies using observational data to optimise dynamic treatment regimens.

Authors:  Maarten J IJzerman; Julie A Simpson; Robert K Mahar; Myra B McGuinness; Bibhas Chakraborty; John B Carlin
Journal:  BMC Med Res Methodol       Date:  2021-02-22       Impact factor: 4.615

  5 in total

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