Matching study design to prescribing intention: The prevalent new-user design for studying abuse-deterrent formulations of opioids.

PURPOSE: In drug studies, research designs requiring no prior exposure to certain drug classes may restrict important populations. Since abuse-deterrent formulations (ADF) of opioids are routinely prescribed after other opioids, choice of study design, identification of appropriate comparators, and addressing confounding by "indication" are important considerations in ADF post-marketing studies. METHODS: In a retrospective cohort study using claims data (2006-2018) from a North Carolina private insurer [NC claims] and Merative MarketScan [MarketScan], we identified patients (18-64 years old) initiating ADF or non-ADF extended-release/long-acting (ER/LA) opioids. We compared patient characteristics and described opioid treatment history between treatment groups, classifying patients as traditional (no opioid claims during prior six-month washout period) or prevalent new users. RESULTS: We identified 8415 (NC claims) and 147 978 (MarketScan) ADF, and 10 114 (NC claims) and 232 028 (MarketScan) non-ADF ER/LA opioid initiators. Most had prior opioid exposure (ranging 64%-74%), and key clinical differences included higher prevalence of recent acute or chronic pain and surgery among patients initiating ADFs compared to non-ADF ER/LA initiators. Concurrent immediate-release opioid prescriptions at initiation were more common in prevalent new users than traditional new users. CONCLUSIONS: Careful consideration of the study design, comparator choice, and confounding by "indication" is crucial when examining ADF opioid use-related outcomes.

Intended and unintended consequences: Changes in opioid prescribing practices for postsurgical, acute, and chronic pain indications following two policies in North Carolina, 2012-2018 - Controlled and single-series interrupted time series analyses.

BACKGROUND: The potential misapplication of current opioid prescribing policies remains understudied and may have substantial adverse implications for patient safety. METHODS: We used autoregressive integrated moving average models to assess level and trend changes in monthly 1) prescribing rates, 2) days' supply, and 3) daily morphine milligram equivalents (MME) of incident opioid prescriptions relative to 1) a state medical board initiative to reduce high-dose and -volume opioid prescribing and 2) legislation to limit initial opioid prescriptions for acute and postsurgical pain. We examined outcomes by pain indication overall and by cancer history, using prescribing patterns for benzodiazepines to control for temporal trends. We used large private health insurance claims data to include North Carolina residents, aged 18-64, insured at any point between January 2012 and August 2018. RESULTS: After the medical board initiative, prescribing patterns for chronic pain patients did not change; conversely, acute and postsurgical pain patients experienced immediate declines in daily MME. Post-legislation prescription rates did not decline for those with acute, postsurgical, and non-cancer pain, but instead declined among cancer patients with chronic pain. Chronic pain patients experienced the largest days' supply declines post-legislation, instead of acute and postsurgical pain patients. CONCLUSIONS: We found mixed evidence on the potential impact of two opioid prescribing policies, with some observed declines in a group not intended to be impacted by the policy. This study provides evidence of the need for clearer opioid prescribing policies to ensure impacts on intended populations and avoid unintended consequences.

Public health application of predictive modeling: an example from farm vehicle crashes.

BACKGROUND: The goal of predictive modelling is to identify the likelihood of future events, such as the predictive modelling used in climate science to forecast weather patterns and significant weather occurrences. In public health, increasingly sophisticated predictive models are used to predict health events in patients and to screen high risk individuals, such as for cardiovascular disease and breast cancer. Although causal modelling is frequently used in epidemiology to identify risk factors, predictive modelling provides highly useful information for individual risk prediction and for informing courses of treatment. Such predictive knowledge is often of great utility to physicians, counsellors, health education specialists, policymakers or other professionals, who may then advice course correction or interventions to prevent adverse health outcomes from occurring. In this manuscript, we use an example dataset that documents farm vehicle crashes and conventional statistical methods to forecast the risk of an injury or death in a farm vehicle crash for a specific individual or a scenario. RESULTS: Using data from 7094 farm crashes that occurred between 2005 and 2010 in nine mid-western states, we demonstrate and discuss predictive model fitting approaches, model validation techniques using external datasets, and the calculation and interpretation of predicted probabilities. We then developed two automated risk prediction tools using readily available software packages. We discuss best practices and common limitations associated with predictive models built from observational datasets. CONCLUSIONS: Predictive analysis offers tools that could aid the decision making of policymakers, physicians, and environmental health practitioners to improve public health.

Methodologic limitations of prescription opioid safety research and recommendations for improving the evidence base.

PURPOSE: The ongoing opioid epidemic has claimed more than a quarter million Americans' lives over the past 15 years. The epidemic began with an escalation of prescription opioid deaths and has now evolved to include secondary waves of illicit heroin and fentanyl deaths, while the deaths due to prescription opioid overdoses are still increasing. In response, the Centers for Disease Control and Prevention (CDC) moved to limit opioid prescribing with the release of opioid prescribing guidelines for chronic noncancer pain in March 2016. The guidelines represent a logical and timely federal response to this growing crisis. However, CDC acknowledged that the evidence base linking opioid prescribing to opioid use disorders and overdose was grades 3 and 4. METHODS: Motivated by the need to strengthen the evidence base, this review details limitations of the opioid safety studies cited in the CDC guidelines with a focus on methodological limitations related to internal and external validity. RESULTS: Internal validity concerns were related to poor confounding control, variable misclassification, selection bias, competing risks, and potential competing interventions. External validity concerns arose from the use of limited source populations, historical data (in a fast-changing epidemic), and issues with handling of cancer and acute pain patients' data. We provide a nonexhaustive list of 7 recommendations to address these limitations in future opioid safety studies. CONCLUSION: Strengthening the opioid safety evidence base will aid any future revisions of the CDC guidelines and enhance their prevention impact.

Management of Pain in the United States-A Brief History and Implications for the Opioid Epidemic.

Pain management in the United States reflects attitudes to those in pain. Increased numbers of disabled veterans in the 1940s to 1960s led to an increased focus on pain and its treatment. The view of the person in pain has moved back and forth between a physiological construct to an individual with pain where perception may be related to social, emotional, and cultural factors. Conceptually, pain has both a medical basis and a political context, moving between, for example, objective evidence of disability due to pain and subjective concerns of malingering. In the 20th century, pain management became predominately pharmacologic. Perceptions of undertreatment led to increased use of opioids, at first for those with cancer-related pain and then later for noncancer pain without the multidimensional care that was intended. The increased use was related to exaggerated claims in the medical literature and by the pharmaceutical industry, of a lack of addiction in the setting of noncancer pain for these medications-a claim that was subsequently found to be false and deliberatively deceptive; an epidemic of opioid prescribing began in the 1990s. An alarming rise in deaths due to opioids has led to several efforts to decrease use, both in patients with noncancer conditions and in those with cancer and survivors of cancer.