Author information
1 Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. Christopher.Rentsch@lshtm.ac.uk.
2 Veterans Aging Cohort Study Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA. Christopher.Rentsch@lshtm.ac.uk.
3 Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA.
4 Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06515, USA.
5 Veterans Aging Cohort Study Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA.
6 Department of Epidemiology, Brown School of Public Health, Providence, RI, 02903, USA.
7 Department of Psychiatry, Yale School of Medicine and VA Connecticut Healthcare System, West Haven, CT, 06516, USA.
8 Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, NJ, 08901, USA.
9 Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, 06515, USA.
10 Pain Research, Informatics, Multi-morbidities and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA.
11 VA COIN Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City VA Health Care System, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA.
12 School of Nursing, University of Louisville, Louisville, KY, 40202, USA.
13 Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
14 Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.
15 Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, 06515, USA.
16 Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Abstract
A better understanding of predisposition to transition to high-dose, long-term opioid therapy after initial opioid receipt could facilitate efforts to prevent opioid use disorder (OUD). We extracted data on 69,268 patients in the Veterans Aging Cohort Study who received any opioid prescription between 1998 and 2015. Using latent growth mixture modelling, we identified four distinguishable dose trajectories: low (53%), moderate (29%), escalating (13%), and rapidly escalating (5%). Compared to low dose trajectory, those in the rapidly escalating dose trajectory were proportionately more European-American (59% rapidly escalating vs. 38% low); had a higher prevalence of HIV (31% vs. 29%) and hepatitis C (18% vs. 12%); and during follow-up, had a higher incidence of OUD diagnoses (13% vs. 3%); were hospitalised more often [18.1/100 person-years (PYs) vs. 12.5/100 PY]; and had higher all-cause mortality (4.7/100 PY vs. 1.8/100 PY, all p < 0.0001). These measures can potentially be used in future prevention research, including genetic discovery.