Acute pain pathways: protocol for a prospective cohort study.

INTRODUCTION: Opioid analgesics are often used to treat moderate-to-severe acute non-cancer pain; however, there is little high-quality evidence to guide clinician prescribing. An essential element to developing evidence-based guidelines is a better understanding of pain management and pain control among individuals experiencing acute pain for various common diagnoses. METHODS AND ANALYSIS: This multicentre prospective observational study will recruit 1550 opioid-naïve participants with acute pain seen in diverse clinical settings including primary/urgent care, emergency departments and dental clinics. Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. Participants will be enrolled to represent diverse races and ethnicities and pain conditions, as well as geographical diversity. Data analysis will focus on assessing patients' patterns of pain and opioid analgesic use, along with other pain treatments; associations between patient and condition characteristics and patient-centred outcomes including resolution of pain, satisfaction with care and long-term use of opioid analgesics; and descriptive analyses of patient management of leftover opioids. ETHICS AND DISSEMINATION: This study has received approval from IRBs at each site. Results will be made available to participants, funders, the research community and the public. TRIAL REGISTRATION NUMBER: NCT04509115.

Considerations in the Assessment of Clinical Benefit with a Focus on Pain: a Regulatory Perspective.

In the USA, the regulatory standard for demonstration of efficacy of a drug is evidence of clinical benefit from adequate and well-controlled clinical trials. Understanding the natural history of disease and how treatment is expected to alter its course, and gathering input from relevant stakeholders, such as patients, caregivers, and clinicians, is essential to understand the best way to measure clinical benefit in a clinical trial. Though pain intensity has been the primary outcome measure in clinical trials for pain, an array of measures assessing clinical outcomes from multiple perspectives can allow for more comprehensive interpretation of how a treatment affects patients' lives. Careful consideration should be given to how pain affects the feeling and functioning of each distinct patient population and which outcome assessment, or combination of outcome assessments, may be necessary to provide a more comprehensive view of the patient experience. The early stages of medical product development are an important opportunity to engage with regulatory agencies to discuss potential approaches to clinical trial design and outcome measurement strategies.

Characteristics Associated With U.S. Outpatient Opioid Analgesic Prescribing and Gabapentinoid Co-Prescribing.

INTRODUCTION: A considerable burden of prescription and illicit opioid-related mortality and morbidity in the U.S. is attributable to potentially unnecessary or excessive opioid prescribing, and co-prescribing gabapentinoids may increase risk of harm. Data are needed regarding physician and patient characteristics associated with opioid analgesic and opioid analgesic-gabapentinoid co-prescriptions to elucidate targets for reducing preventable harm. METHODS: Multiple logistic regression was utilized to examine patient and physician predictors of opioid analgesic prescriptions and opioid analgesic-gabapentinoid co-prescriptions in adult noncancer patients using the National Ambulatory Medical Care Survey 2015 public use data set. Potential predictors were selected based on literature review, clinical relevance, and random forest machine learning algorithms. RESULTS: Among the 11.8% (95% CI=9.8%, 13.9%) of medical encounters with an opioid prescription, 16.2% (95% CI=12.6%, 19.8%) had a gabapentinoid co-prescription. Among all gabapentinoid encounters, 40.7% (95% CI=32.6%, 48.7%) had an opioid co-prescription. Predictors of opioid prescription included arthritis (OR=1.87, 95% CI=1.30, 2.69). Predictors of new opioid prescription included physician status as an independent contractor (OR=3.67, 95% CI=1.38, 9.81) or part owner of the practice (OR=3.34, 95% CI=1.74, 6.42). Predictors of opioid-gabapentinoid co-prescription included patient age (peaking at age 55-64 years; OR=35.67, 95% CI=4.32, 294.43). CONCLUSIONS: Predictors of opioid analgesic prescriptions with and without gabapentinoid co-prescriptions were identified. These predictors can help inform and reinforce (e.g., educational) interventions seeking to reduce preventable harm, help identify populations for elucidating opioid-gabapentinoid risk-benefit profiles, and provide a baseline for evaluating subsequent public health measures.