Smokers with opioid use disorder may have worse drug use outcomes after varenicline than nicotine replacement

E-cigarette use among a national sample of adults receiving substance use treatment in the United States

BACKGROUND

Smoking among adults in substance use disorder (SUD) treatment programs is common with limited success in quitting. Given e-cigarettes' potential for smoking harm reduction, it is important to examine e-cigarette use among people in SUD treatment.

METHODS

We analyzed data from adults who have received SUD treatment in the past year, from the 2020-2021 National Survey on Drug Use and Health (N = 1,246). We delineated correlates of lifetime and current (past-month) use e-cigarette use.

RESULTS

Among adults receiving SUD treatment, an estimated 39.4 % (95 % CI: 34.1, 45.1) have used e-cigarettes in their lifetime and 19.5 % (95 % CI: 16.1, 23.6) of those currently vape. Among those reporting current vaping, an estimated 57.3 % (95 % CI: 44.9-68.8) currently smoke cigarettes and half (54.2 % [95 % CI: 41.1-66.7]) currently use cannabis. Compared to those who only received treatment for alcohol use disorder, those receiving treatment for drug use (aPR = 1.47, 95 % CI: 1.09-1.99) and alcohol and drug use (aPR = 1.60, 95 % CI: 1.16-2.22) had higher prevalence of lifetime e-cigarette use, and those reporting treatment for drug use only (aPR = 2.60, 95 % CI: 1.52-4.46) and alcohol and drug use (aPR = 2.82, 95 % CI: 1.63-4.87) also had higher prevalence of current e-cigarette use.

CONCLUSIONS

The prevalence of e-cigarette use was higher among those in treatment for both drug or alcohol and drugs only than those receiving treatment for only alcohol use. Smoking harm reduction interventions can potentially include e-cigarette among those receiving drug treatment. There is also a need to address challenges of dual e-cigarette and cigarette use, as well as dual e-cigarette use with cannabis.

Nicotine receptor partial agonists for smoking cessation

Background

Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist). This is an update of a Cochrane Review first published in 2007.

Objectives

To assess the effectiveness of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation.

Search methods

We searched the Cochrane Tobacco Addiction Group's Specialised Register in April 2022 for trials, using relevant terms in the title or abstract, or as keywords. The register is compiled from searches of CENTRAL, MEDLINE, Embase, and PsycINFO. 

Selection criteria

We included randomised controlled trials that compared the treatment drug with placebo, another smoking cessation drug, e‐cigarettes, or no medication. We excluded trials that did not report a minimum follow‐up period of six months from baseline.

Data collection and analysis

We followed standard Cochrane methods. Our main outcome was abstinence from smoking at longest follow‐up using the most rigorous definition of abstinence, preferring biochemically validated rates where reported. We pooled risk ratios (RRs), using the Mantel‐Haenszel fixed‐effect model. We also reported the number of people reporting serious adverse events (SAEs).

Main results

We included 75 trials of 45,049 people; 45 were new for this update. We rated 22 at low risk of bias, 18 at high risk, and 35 at unclear risk.

We found moderate‐certainty evidence (limited by heterogeneity) that cytisine helps more people to quit smoking than placebo (RR 1.30, 95% confidence interval (CI) 1.15 to 1.47; I2 = 83%; 4 studies, 4623 participants), and no evidence of a difference in the number reporting SAEs (RR 1.04, 95% CI 0.78 to 1.37; I2 = 0%; 3 studies, 3781 participants; low‐certainty evidence). SAE evidence was limited by imprecision. We found no data on neuropsychiatric or cardiac SAEs.

We found high‐certainty evidence that varenicline helps more people to quit than placebo (RR 2.32, 95% CI 2.15 to 2.51; I2 = 60%, 41 studies, 17,395 participants), and moderate‐certainty evidence that people taking varenicline are more likely to report SAEs than those not taking it (RR 1.23, 95% CI 1.01 to 1.48; I2 = 0%; 26 studies, 14,356 participants). While point estimates suggested increased risk of cardiac SAEs (RR 1.20, 95% CI 0.79 to 1.84; I2 = 0%; 18 studies, 7151 participants; low‐certainty evidence), and decreased risk of neuropsychiatric SAEs (RR 0.89, 95% CI 0.61 to 1.29; I2 = 0%; 22 studies, 7846 participants; low‐certainty evidence), in both cases evidence was limited by imprecision, and confidence intervals were compatible with both benefit and harm.

Pooled results from studies that randomised people to receive cytisine or varenicline found no clear evidence of difference in quit rates (RR 1.00, 95% CI 0.79 to 1.26; I2 = 65%; 2 studies, 2131 participants; low‐certainty evidence) and reported SAEs (RR 0.67, 95% CI 0.44 to 1.03; I2 = 45%; 2 studies, 2017 participants; low‐certainty evidence). However, the evidence was limited by imprecision, and confidence intervals incorporated the potential for benefit from either cytisine or varenicline. We found no data on neuropsychiatric or cardiac SAEs.

We found high‐certainty evidence that varenicline helps more people to quit than bupropion (RR 1.36, 95% CI 1.25 to 1.49; I2 = 0%; 9 studies, 7560 participants), and no clear evidence of difference in rates of SAEs (RR 0.89, 95% CI 0.61 to 1.31; I2 = 0%; 5 studies, 5317 participants), neuropsychiatric SAEs (RR 1.05, 95% CI 0.16 to 7.04; I2 = 10%; 2 studies, 866 participants), or cardiac SAEs (RR 3.17, 95% CI 0.33 to 30.18; I2 = 0%; 2 studies, 866 participants). Evidence of harms was of low certainty, limited by imprecision.

We found high‐certainty evidence that varenicline helps more people to quit than a single form of nicotine replacement therapy (NRT) (RR 1.25, 95% CI 1.14 to 1.37; I2 = 28%; 11 studies, 7572 participants), and low‐certainty evidence, limited by imprecision, of fewer reported SAEs (RR 0.70, 95% CI 0.50 to 0.99; I2 = 24%; 6 studies, 6535 participants). We found no data on neuropsychiatric or cardiac SAEs.

We found no clear evidence of a difference in quit rates between varenicline and dual‐form NRT (RR 1.02, 95% CI 0.87 to 1.20; I2 = 0%; 5 studies, 2344 participants; low‐certainty evidence, downgraded because of imprecision). While pooled point estimates suggested increased risk of SAEs (RR 2.15, 95% CI 0.49 to 9.46; I2 = 0%; 4 studies, 1852 participants) and neuropsychiatric SAEs (RR 4.69, 95% CI 0.23 to 96.50; I2 not estimable as events only in 1 study; 2 studies, 764 participants), and reduced risk of cardiac SAEs (RR 0.32, 95% CI 0.01 to 7.88; I2 not estimable as events only in 1 study; 2 studies, 819 participants), in all three cases evidence was of low certainty and confidence intervals were very wide, encompassing both substantial harm and benefit.

Authors' conclusions

Cytisine and varenicline both help more people to quit smoking than placebo or no medication. Varenicline is more effective at helping people to quit smoking than bupropion, or a single form of NRT, and may be as or more effective than dual‐form NRT. People taking varenicline are probably more likely to experience SAEs than those not taking it, and while there may be increased risk of cardiac SAEs and decreased risk of neuropsychiatric SAEs, evidence was compatible with both benefit and harm. Cytisine may lead to fewer people reporting SAEs than varenicline. Based on studies that directly compared cytisine and varenicline, there may be no difference or a benefit from either medication for quitting smoking.

Future trials should test the effectiveness and safety of cytisine compared with varenicline and other pharmacotherapies, and should also test variations in dose and duration. There is limited benefit to be gained from more trials testing the effect of standard‐dose varenicline compared with placebo for smoking cessation. Further trials on varenicline should test variations in dose and duration, and compare varenicline with e‐cigarettes for smoking cessation.

Can medications like varenicline and cytisine (nicotine receptor partial agonists) help people to stop smoking and do they cause unwanted effects?

Key messages

· Varenicline can help people to stop smoking for at least 6 months. Evidence shows it works better than bupropion and using only one type of nicotine replacement therapy (e.g. only patches). Quit rates might be similar to using more than one type of nicotine replacement therapy at the same time (e.g. patches and gum together).

· Cytisine can help people to stop smoking for at least 6 months. It may work as well as varenicline, but future evidence may show that while it helps, it is not quite as helpful as varenicline.

· Future studies should test the effectiveness and safety of cytisine compared with varenicline and other stop‐smoking medications, and should also  investigate giving cytisine or varenicline at different doses and for different lengths of time.

What are 'nicotine receptor partial agonists'?

Smoking tobacco is extremely bad for people’s health. For people who smoke, quitting is the best thing they can do to improve their health. Many people find it difficult to quit smoking. Nicotine receptor partial agonists (NRPAs) are a type of medication used to help people to stop smoking. They help to reduce the withdrawal symptoms people experience when they stop smoking, like cravings and unpleasant mood changes. They also reduce the pleasure people usually experience when they smoke. The most widely‐available treatment in this drug type is varenicline. Cytisine is another, similar medication. They may cause unwanted effects such as feeling sick (nausea) and other stomach problems, difficulties sleeping, abnormal dreams, and headache. They may also lead to potentially serious unwanted effects, such as suicidal thoughts, heart problems and raised blood pressure.

What did we want to find out?

We wanted to find out if using NRPAs can help people to quit smoking, and if they cause unwanted effects. We wanted to know:

· how many people stopped smoking for at least 6 months; and

· how many people had unwanted effects.

What did we do?

We searched for studies that investigated NRPAs used to help people quit smoking. People in the studies had to be chosen at random to receive an NRPA, or another NRPA, placebo (medication like the NRPA but with no active ingredients) or no treatment. They had to be adult tobacco smokers who wanted to stop smoking.

What did we find?

We found 75 studies that compared NRPAs with:

· placebo or no medicine;

· nicotine replacement therapy, such as patches or gum;

· bupropion (another medicine to help people stop smoking);

· another NRPA;

· e‐cigarettes.

The USA hosted the most studies (28 studies). Other studies took place in a range of countries across the world, some in several countries.

Main results

People are more likely to stop smoking for at least six months using varenicline than using placebo (41 studies, 17,395 people), bupropion (9 studies, 7560 people), or just one type of nicotine replacement therapy, like patches alone (11 studies, 7572 people). They may be just as likely to quit as people using two or more kinds of nicotine replacement therapy, like patches and gum together (5 studies, 2344 people).

Cytisine probably helps more people to stop smoking than placebo (4 studies, 4623 people) and may be just as effective as varenicline (2 studies, 2131 people).

For every 100 people using varenicline to stop smoking, 21 to 25 might successfully stop, compared with only 18 of 100 people using bupropion, 18 of 100 people using a single form of nicotine‐replacement therapy, and 20 of 100 using two or more kinds of nicotine‐replacement therapy. For every 100 people using cytisine to stop smoking, 18 to 23 might successfully stop.

The most common unwanted effect of varenicline is nausea, but this is mostly at mild or moderate levels and usually clears over time. People taking varenicline likely have an increased chance of a more serious unwanted effect that could result in going to hospital, however these are still rare (2.7% to 4% of people on varenicline, compared with 2.7% of people without) and may include many that are unrelated to varenicline. People taking cytisine may also have a slightly increased chance of serious unwanted effects compared with people not taking it, but this may be less likely compared with varenicline.

What are the limitations of the evidence?

The evidence for some of our results is very reliable. We’re very confident that varenicline helps people to quit smoking better than many alternatives. We’re less sure of some other results because fewer or smaller studies provided evidence.

Several results suggest one treatment is better or less harmful than another, but the opposite could still be true.

How up to date is the evidence?

The evidence is up to date to 29 April 2022.

Nicotine receptor partial agonists for smoking cessation

BACKGROUND

Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist). This is an update of a Cochrane Review first published in 2007.

OBJECTIVES

To assess the effectiveness of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialised Register in April 2022 for trials, using relevant terms in the title or abstract, or as keywords. The register is compiled from searches of CENTRAL, MEDLINE, Embase, and PsycINFO.  SELECTION CRITERIA: We included randomised controlled trials that compared the treatment drug with placebo, another smoking cessation drug, e-cigarettes, or no medication. We excluded trials that did not report a minimum follow-up period of six months from baseline.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our main outcome was abstinence from smoking at longest follow-up using the most rigorous definition of abstinence, preferring biochemically validated rates where reported. We pooled risk ratios (RRs), using the Mantel-Haenszel fixed-effect model. We also reported the number of people reporting serious adverse events (SAEs).

MAIN RESULTS

We included 75 trials of 45,049 people; 45 were new for this update. We rated 22 at low risk of bias, 18 at high risk, and 35 at unclear risk. We found moderate-certainty evidence (limited by heterogeneity) that cytisine helps more people to quit smoking than placebo (RR 1.30, 95% confidence interval (CI) 1.15 to 1.47; I2 = 83%; 4 studies, 4623 participants), and no evidence of a difference in the number reporting SAEs (RR 1.04, 95% CI 0.78 to 1.37; I2 = 0%; 3 studies, 3781 participants; low-certainty evidence). SAE evidence was limited by imprecision. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than placebo (RR 2.32, 95% CI 2.15 to 2.51; I2 = 60%, 41 studies, 17,395 participants), and moderate-certainty evidence that people taking varenicline are more likely to report SAEs than those not taking it (RR 1.23, 95% CI 1.01 to 1.48; I2 = 0%; 26 studies, 14,356 participants). While point estimates suggested increased risk of cardiac SAEs (RR 1.20, 95% CI 0.79 to 1.84; I2 = 0%; 18 studies, 7151 participants; low-certainty evidence), and decreased risk of neuropsychiatric SAEs (RR 0.89, 95% CI 0.61 to 1.29; I2 = 0%; 22 studies, 7846 participants; low-certainty evidence), in both cases evidence was limited by imprecision, and confidence intervals were compatible with both benefit and harm. Pooled results from studies that randomised people to receive cytisine or varenicline showed that more people in the varenicline arm quit smoking (RR 0.83, 95% CI 0.66 to 1.05; I2 = 0%; 2 studies, 2131 participants; moderate-certainty evidence) and reported SAEs (RR 0.67, 95% CI 0.44 to 1.03; I2 = 45%; 2 studies, 2017 participants; low-certainty evidence). However, the evidence was limited by imprecision, and confidence intervals incorporated the potential for benefit from either cytisine or varenicline. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than bupropion (RR 1.36, 95% CI 1.25 to 1.49; I2 = 0%; 9 studies, 7560 participants), and no clear evidence of difference in rates of SAEs (RR 0.89, 95% CI 0.61 to 1.31; I2 = 0%; 5 studies, 5317 participants), neuropsychiatric SAEs (RR 1.05, 95% CI 0.16 to 7.04; I2 = 10%; 2 studies, 866 participants), or cardiac SAEs (RR 3.17, 95% CI 0.33 to 30.18; I2 = 0%; 2 studies, 866 participants). Evidence of harms was of low certainty, limited by imprecision. We found high-certainty evidence that varenicline helps more people to quit than a single form of nicotine replacement therapy (NRT) (RR 1.25, 95% CI 1.14 to 1.37; I2 = 28%; 11 studies, 7572 participants), and low-certainty evidence, limited by imprecision, of fewer reported SAEs (RR 0.70, 95% CI 0.50 to 0.99; I2 = 24%; 6 studies, 6535 participants). We found no data on neuropsychiatric or cardiac SAEs. We found no clear evidence of a difference in quit rates between varenicline and dual-form NRT (RR 1.02, 95% CI 0.87 to 1.20; I2 = 0%; 5 studies, 2344 participants; low-certainty evidence, downgraded because of imprecision). While pooled point estimates suggested increased risk of SAEs (RR 2.15, 95% CI 0.49 to 9.46; I2 = 0%; 4 studies, 1852 participants) and neuropsychiatric SAEs (RR 4.69, 95% CI 0.23 to 96.50; I2 not estimable as events only in 1 study; 2 studies, 764 participants), and reduced risk of cardiac SAEs (RR 0.32, 95% CI 0.01 to 7.88; I2 not estimable as events only in 1 study; 2 studies, 819 participants), in all three cases evidence was of low certainty and confidence intervals were very wide, encompassing both substantial harm and benefit.

AUTHORS' CONCLUSIONS

Cytisine and varenicline both help more people to quit smoking than placebo or no medication. Varenicline is more effective at helping people to quit smoking than bupropion, or a single form of NRT, and may be as or more effective than dual-form NRT. People taking varenicline are probably more likely to experience SAEs than those not taking it, and while there may be increased risk of cardiac SAEs and decreased risk of neuropsychiatric SAEs, evidence was compatible with both benefit and harm. Cytisine may lead to fewer people reporting SAEs than varenicline. Based on studies that directly compared cytisine and varenicline, there may be a benefit from varenicline for quitting smoking, however further evidence could strengthen this finding or demonstrate a benefit from cytisine. Future trials should test the effectiveness and safety of cytisine compared with varenicline and other pharmacotherapies, and should also test variations in dose and duration. There is limited benefit to be gained from more trials testing the effect of standard-dose varenicline compared with placebo for smoking cessation. Further trials on varenicline should test variations in dose and duration, and compare varenicline with e-cigarettes for smoking cessation.

A targeted approach to using e-cigarettes for harm reduction in adults

Smoking remains the leading preventable cause of death and disease in the US. While e-cigarettes (EC) are undeniably harmful when used by adolescents and nonsmokers, the perpetuation of the increasing negative perceptions of EC and widespread false belief that EC are equal or more harmful than combustible cigarettes (CC) represents a significant missed public health opportunity. EC have great potential to serve as a mechanism for smoking harm reduction among hard-to-treat populations of smokers who have failed to quit with currently available treatments. In this paper, we outline why we need to overcome the hostile EC research environment to explore the potential use of EC as a harm-reduction strategy in hard-to-treat populations.

Nicotine and opioid co-dependence: Findings from bench research to clinical trials

Concomitant use of tobacco and opioids represents a growing public health concern. In fact, the mortality rate due to smoking-related illness approaches 50% among SUD patients. Cumulative evidence demonstrates that the vulnerability to drugs of abuse is influenced by behavioral, environmental, and genetic factors. This review explores the contribution of genetics and neural mechanisms influencing nicotine and opioid reward, respiration, and antinociception, emphasizing the interaction of cholinergic and opioid receptor systems. Despite the substantial evidence demonstrating nicotine-opioid interactions within the brain and on behavior, the currently available pharmacotherapies targeting these systems have shown limited efficacy for smoking cessation on opioid-maintained smokers. Thus, further studies designed to identify novel targets modulating both nicotinic and opioid receptor systems may lead to more efficacious approaches for co-morbid nicotine dependence and opioid use disorder.

Timing of smoking cessation treatment integrated into outpatient treatment with medications for opioid use disorder: Feasibility trial

INTRODUCTION

Cigarette smoking rates among individuals with opioid use disorder (OUD) are notoriously high and may be improved by considering the timing of treatment integration for these two substances. The current study examined the feasibility of a method for assessing the timing of integrating smoking cessation pharmacotherapy within three different phases of outpatient treatment with medication for OUD (MOUD).

METHODS

Seventy-four buprenorphine-maintained smokers were enrolled in a quasi-experimental study across three MOUD treatment phases: 0-90 (Phase 1), 91-365 (Phase 2), and > 365 days of MOUD treatment (Phase 3). During a 12-week varenicline-based intervention, the study assessed outcomes daily via text messages (cigarette smoking, varenicline adherence, side effects) or monthly at in-person visits (quit motivation and carbon monoxide levels).

RESULTS

Thirty-five participants completed the study, with a lower retention rate in Phase 1 (37.5%) relative to Phases 2 (53.5%) or 3 (57.1%). A trend occurred for Phase 1 participants to report aversive side effects (e.g., abnormal dreams, gastrointestinal distress) on more study days. Among completers, adherence to text messaging and varenicline use was high and independent of MOUD treatment phase. Participants in all phases reported declines in cigarette smoking and increases in quit motivation over time; the study observed biochemically verified tobacco abstinence among only a few participants from Phases 2 or 3.

CONCLUSIONS

This feasibility study demonstrates a method to evaluate the timing of treatment integration for cigarette smoking and MOUD. Method strengths include a study schedule that coincided with the MOUD clinic schedule and use of text messaging to encourage varenicline adherence and evaluate outcomes regularly.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Investigating tobacco withdrawal in response to reduced nicotine cigarettes among smokers with opioid use disorder and other vulnerabilities

Individuals with opioid use disorder (OUD) have high prevalence of smoking and poor cessation outcomes. Data suggest that smokers with OUD may experience heightened nicotine reinforcement and more severe tobacco withdrawal compared to smokers without OUD. The Food and Drug Administration is currently considering reducing the nicotine content of cigarettes to reduce smoking prevalence and smoking-related disease. It is critical to understand the effects of reduced nicotine content cigarettes (RNCCs) on tobacco withdrawal in this subgroup. In this secondary analysis, we investigated the ability of RNCCs to attenuate acute tobacco withdrawal and craving severity in smokers with OUD versus those without substance use disorders (SUDs). Smokers maintained on methadone or buprenorphine (opioid-maintained [OM]; n = 65) versus without other SUDs (i.e., non-SUD; n = 135) completed 5 laboratory sessions wherein they smoked their usual brand (UB) or a research cigarette varying in nicotine content (0.4, 2.4, 5.2, 15.8 mg/g of tobacco) under double-blind, acute abstinence conditions. Participants completed the Minnesota Tobacco Withdrawal Scale, including a desire to smoke (craving) item, before and every 15 min for 1 hr following smoking each cigarette. Tobacco withdrawal and craving did not differ significantly by OM status in response to UB or RNCCs. In addition to the Dose × Time interaction, greater depression and cigarette dependence consistently predicted withdrawal and craving (ps < .05). Across all cigarettes, tobacco withdrawal and craving did not significantly differ by OM status, suggesting that smokers receiving opioid agonist treatment may respond favorably to RNCCs. Additional studies with larger and more diverse samples are needed to address this question more definitively. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Nicotine and Opioids: a Call for Co-treatment as the Standard of Care

The U.S. is in the midst of an opioid epidemic. At the same time, tobacco use remains the leading cause of preventable death and disability. While the shared biological underpinnings of nicotine and opioid addiction are well established, clinical implications for co-treatment of these two substance use disorders has not been emphasized in the literature, nor have researchers, clinicians, and policy makers adequately outlined pathways for incorporating co-treatment into existing clinical workflows. The current brief review characterizes the metabolic and neural mechanisms which mediate co-use of nicotine and opioids, and then outlines clinical and policy implications for concurrently addressing these two deadly epidemics. Screening, assessment, medication-assisted treatment (MAT), and tobacco-free policy are discussed. The evidence suggests that clinical care and policies that facilitate co-treatment are an expedient means of delivering healthcare to individuals that result in better health for the population while also meeting patients' substance abuse disorder recovery goals.

Quit ratios for cigarette smoking among individuals with opioid misuse and opioid use disorder in the United States

BACKGROUND

The prevalence of cigarette smoking is more than two times higher among individuals with versus without opioid misuse and/or opioid use disorders (OUD). Overall, smoking cessation has increased over time although it is unknown whether it has similarly increased for those with opioid misuse or OUD. The current study examined cigarette quit ratios from 2002 to 2018 among US individuals with and without opioid misuse or OUD.

METHODS

Data came from the National Survey on Drug Use and Health, a yearly cross-sectional survey of US civilians 12 years or older. Annual quit ratios (i.e., proportion of former smokers among lifetime-smokers) were estimated from 2002 to 2018. Logistic regression tested time trends in quit ratios by opioid misuse/OUD.

RESULTS

Past-month smoking prevalence was much higher for persons with versus without opioid misuse (64.6 % versus 25.7 %) and OUD (73.3 % versus 26.0 %). In 2018, quit ratios for individuals with opioid misuse (18.0 %) or OUD (10.0 %) were less than half of those without opioid misuse (48.3 %) or OUD (48.1 %). After adjusting for background characteristics, the quit ratio did not change over time among individuals with opioid misuse or OUD in contrast to an increase in quit ratios for those without opioid misuse or OUD. For those without opioid misuse or OUD, males had higher quit ratios than females.

CONCLUSIONS

Cigarette quit ratios remain dramatically lower among those with opioid misuse or OUD. Public health and clinical attention are needed to increase cessation and reduce smoking consequences for individuals with opioid misuse and OUD.

Achieving Smoking Cessation Among Persons with Opioid Use Disorder

While prevalence of tobacco use in the US general population is declining, prevalence among those with opioid use disorder (OUD) remains high and results in excessive tobacco-related disease and premature mortality. Among smokers with OUD, tobacco cessation rates are negligible without treatment. However, both low-intensity behavioral interventions and more intensive motivational interventions yield negligible cessation rates. While contingency management has potent short-term cessation effects, effects are not maintained at post-intervention follow-up. Evidence-based smoking cessation pharmacotherapies, such as nicotine replacement therapy, bupropion, and varenicline, result in very modest cessation rates among smokers with OUD. Intensification of pharmacotherapy, such as high-dose and combination nicotine replacement therapy or extended medication treatment, has failed to improve cessation outcomes compared with standard treatment regimens. Targeting the unique challenges faced by smokers with OUD, including nicotine-opioid interactions and poor medication adherence, has potential to improve cessation outcomes, but further research is needed to optimize intervention efficacy among smokers with OUD.

Psycho-Social Correlates of Opioid Use Disorder among the US Adult Population: Evidence from the National Survey on Drug Use and Health, 2015-2018

The United States (US) has experienced an opioid epidemic over the last two decades. Drug overdose deaths increased by 21% from 2015 to 2016, with two-thirds of these deaths attributed to opioid use disorder (OUD). This study assessed the psycho-social correlates associated with OUD over 2015-2018 in the US. Methods: This study used data collected from 171,766 (weighted = 245,838,163) eligible non-institutionalized US adults in the pooled National Survey on Drug Use and Health from 2015-2018. Survey-weighted descriptive, bivariate, and multivariable analyses were performed to assess the psycho-social correlates of OUD. Results: About 0.85% of the respondents reported having OUD in the past year. About one-quarter (26.3%), one-sixth (14.8%), and half (47.3%) of the respondents with OUD reported alcohol, marijuana, and nicotine dependence, respectively. One-sixth (16.7%) had a criminal justice involvement history, and almost one-third (30.8%) experienced a major depressive episode (MDE) in the past year. In multivariable analysis, ≤64 years, White race, male gender, lower educational attainment, unemployment, large metro area residence, history of alcohol, marijuana, nicotine use disorder, history of criminal justice involvement, and MDE in previous year were associated with higher odds of OUD. In contrast, being married, non-Hispanic African American, non-Hispanic Other, and Hispanic ethnicity, good physical health, private health insurance, and higher risk perception about addictive substance use were associated with lower odds of OUD. Conclusions: OUD is more prevalent among certain sociodemographic groups in the US. Targeted interventions focusing on young, White, unmarried, male, and uninsured/Medicaid/Medicare populations should be implemented to reduce the OUD.