Opioid drugs (such as codeine and tramadol) for chronic pain have increased considerably in the US, UK and Europe. Pain due to musculoskeletal (MSK) conditions is one of the common reasons for prescribing opioids. MSK patients may be particularly susceptible to opioid-related harms due to older age, other existing health-conditions and drug-interactions. However, there are limited alternative options for painkillers. Therefore, depriving everyone of opioids is not a solution. Recognising risk-factors and patient subgroups where harms outweigh the benefits is imperative for informed decision-making and safe prescribing. We will focus on people with MSK conditions starting opioids for the first-time to address (i) the current national trends of opioid prescribing in the UK over the last 14 years (ii) how many people/year get admitted to hospital for opioid-related harms, develop opioid-dependence, or die because of the drug? (iii) what risk factors in individual patients predispose to opioid-dependence and deaths?(iv) can we predict individual risk before prescribing an opioid and what subgroups of people should not be prescribed an opioid due to a high risk of death? A better understanding of individual risk of opioid-related harms before starting opioids, would enable patients to make more informed decisions. By determining patient subgroups most vulnerable to opioid-related harms we can develop targeted interventions for safer future clinical care, whilst avoiding depriving the entire population of this class of painkillers that may be safe and effective for some.
Rising opioid use has been associated with an alarming rise in opioid-related harms, dependence and mortality in North America. However, fewer data are available in Europe. RMDs are one of the most common indications for prescribing opioids. These patients may already be at high-risk of opioid-related morbidity/mortality due to multimorbidity, immunosuppression and polypharmacy.
Aims: In new opioid users with the following RMDs: rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis, systemic lupus erythematosus, osteoarthritis and fibromyalgia to:
(i) Characterise national UK opioid prescribing trends between 2006-2021
(ii) Evaluate trends in hospital admissions associated with opioid-related prescriptions, dependence and mortality
(iii) Identify individual, prescribing, demographic and contextual risk factors that predispose to opioid-dependence and mortality
(iv) Predict opioid-related mortality risk to enable a stratified approach to prescribing in clinical care
Methods: A retrospective observational study will be performed using 2006-2021 data using linked CPRD data. A combination of traditional (e.g. survival analysis/multi-state models) and machine learning methods will be used to address the outlined objectives.
Expected outputs: Prediction of individual risk of opioid-related harms would allow future development of targeted interventions, guiding clinicians towards more careful prescribing in those at high-risk while avoiding depriving the entire population of this class of analgesics.
Opioid prescriptions per year; Opioid-related hospitalisations; opioid dependence; cause specific and all cause mortality
Meghna Jani - Chief Investigator - University of Manchester
Meghna Jani - Corresponding Applicant - University of Manchester
Belay Yimer - Collaborator - University of Manchester
Carlos Raul Ramirez Medina - Collaborator - University of Manchester
David Jenkins - Collaborator - University of Manchester
Jose Benitez-Aurioles - Collaborator - University of Manchester
Joyce (Yun-Ting) Huang - Collaborator - University of Manchester
Mark Lunt - Collaborator - University of Manchester
Max Lyon - Collaborator - University of Manchester
Niels Peek - Collaborator - University of Manchester
Ramiro Bravo - Collaborator - University of Manchester
Wanqi Zhao - Collaborator - University of Manchester
William Dixon - Collaborator - University of Manchester
Dhanwanti Dhanwanti - Collaborator - University of Manchester
Jose Benitez-Aurioles - Collaborator - University of Manchester
Joyce (Yun-Ting) Huang - Collaborator - University of Manchester
Lotta Castren - Collaborator - University of Manchester
Lucy Bull - Collaborator - University of Manchester
Ramiro Bravo - Collaborator - University of Manchester
Ruth Costello - Collaborator - University of Manchester
HES Accident and Emergency;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation