Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.

TitleIdentifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.
Publication TypeJournal Article
Year of Publication2018
AuthorsLaber, Eric B., Fan Wu, Catherine Munera, Ilya Lipkovich, Salvatore Colucci, and Steve Ripa
JournalStat Med
Volume37
Issue9
Pagination1407-1418
Date Published2018 04 30
ISSN1097-0258
KeywordsAnalgesics, Opioid, Chronic Pain, Drug Dosage Calculations, Humans, Long-Term Care, Models, Statistical, Precision Medicine, Statistics as Topic, Statistics, Nonparametric
Abstract

There is growing interest and investment in precision medicine as a means to provide the best possible health care. A treatment regime formalizes precision medicine as a sequence of decision rules, one per clinical intervention period, that specify if, when and how current treatment should be adjusted in response to a patient's evolving health status. It is standard to define a regime as optimal if, when applied to a population of interest, it maximizes the mean of some desirable clinical outcome, such as efficacy. However, in many clinical settings, a high-quality treatment regime must balance multiple competing outcomes; eg, when a high dose is associated with substantial symptom reduction but a greater risk of an adverse event. We consider the problem of estimating the most efficacious treatment regime subject to constraints on the risk of adverse events. We combine nonparametric Q-learning with policy-search to estimate a high-quality yet parsimonious treatment regime. This estimator applies to both observational and randomized data, as well as settings with variable, outcome-dependent follow-up, mixed treatment types, and multiple time points. This work is motivated by and framed in the context of dosing for chronic pain; however, the proposed framework can be applied generally to estimate a treatment regime which maximizes the mean of one primary outcome subject to constraints on one or more secondary outcomes. We illustrate the proposed method using data pooled from 5 open-label flexible dosing clinical trials for chronic pain.

DOI10.1002/sim.7566
Alternate JournalStat Med
Original PublicationIdentifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.
PubMed ID29468702
PubMed Central IDPMC6293986
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 DE024984 / DE / NIDCR NIH HHS / United States
Project: