Adherence to varenicline in the COMPASS smoking cessation intervention trial

Optimizing behavioral and pharmacological smoking cessation interventions among people with HIV

BACKGROUND

People with HIV/AIDS (PWH) smoke at nearly three times the rate of the general population. Interventions to promote sustained quitting among PWH are urgently needed.

METHODS

Our study used a randomized factorial design to evaluate the effects of varenicline, compared with placebo, and behavioral cessation therapy, positively smoke free (PSF), compared with standard of care (SOC) among PWH who smoke. The study was designed with power to detect a small effect (Cohen's h of 0.28-0.36) with 240 participants. The primary outcome was the 7-day point prevalence abstinence (PPA) confirmed by exhaled carbon monoxide (ECO) less than 10 ppm for both main effects at 36 weeks. The study was conducted from June 2016 to November 2020. During the study's last year, recruitment was halted because of COVID-19.

RESULTS

The study randomized 184 participants with power to detect a medium effect (Cohen's h of 0.41). Participants were mostly African American (89.7%), men (62.8%) who smoked mentholated cigarettes (96.7%). Nearly all received antiretroviral medication (96.2%). Quit rates for the entire sample were 7.5% at 36 weeks. Compared with those who received placebo, neither those who received varenicline [36 weeks; OR (95% CI), 1.31 (0.33-5.22), P  = 0.70] nor PSF [36 weeks; OR (95% CI), 0.26 (0.03-2.44), P  = 0.24) were more likely to quit smoking.

CONCLUSION

Among an urban living, primarily African American sample of PWH who smoke neither varenicline nor PSF was found to be efficacious at 36 weeks. Our study was not powered to detect small effects sizes. Larger trials are needed to establish tobacco treatment standards for PWH who smoke.

Identifying determinants of varenicline adherence using the Theoretical Domains framework: a rapid review

BACKGROUND

Adhering to varenicline has been shown to significantly improve the chances of successfully quitting smoking, with studies indicating a twofold increase in 6-month quit rates. However, despite its potential benefits, many individuals struggle with maintaining good adherence to varenicline; thus there is a need to develop scalable strategies to help people adhere. As a first step to inform the development of an intervention to improve adherence to varenicline, we conducted a rapid literature review to identify: 1) modifiable barriers and facilitators to varenicline adherence, and 2) behaviour change techniques associated with increased adherence to varenicline.

METHODS

We searched MEDLINE, Embase, APA PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials for relevant studies published between 2006 and 2022. Search terms included "varenicline," "smoking cessation," and "adherence," and their respective subject headings and synonyms. We screened and included studies reporting modifiable determinants of adherence to varenicline and then assessed quality, extracted modifiable determinants and mapped them to the Theoretical Domains Framework version 2 and the Behaviour Change Technique Taxonomy version 1.

RESULTS

A total of 1,221 titles were identified through the database searches; 61 met the eligibility criteria. Most of the studies were randomized controlled trials and predominantly focused on barriers to varenicline. Only nine studies explicitly mentioned behaviour change techniques used to help varenicline adherence. Eight domains were identified as barriers to varenicline adherence (behavioural regulation, memory, goals, intentions, beliefs about capabilities, beliefs about consequences, optimism/pessimism, and environmental context) and five as facilitators (knowledge, behavioural regulation, beliefs about capabilities, social influences, and environmental context).

CONCLUSIONS

This study identifies barriers and facilitators that should be addressed when developing a complex adherence intervention tailored to patients' needs based on modifiable determinants of medication adherence, some of which are under- used by existing adherence interventions. The findings from this review will inform the design of a theory-based healthbot planned to improve varenicline adherence in people undergoing smoking cessation treatment.

SYSTEMATIC REVIEW REGISTRATION

This study was registered with PROSPERO (# CRD42022321838).

AI Conversational Agent to Improve Varenicline Adherence: Protocol for a Mixed Methods Feasibility Study

BACKGROUND

Varenicline is a pharmacological intervention for tobacco dependence that is safe and effective in facilitating smoking cessation. Enhanced adherence to varenicline augments the probability of prolonged smoking abstinence. However, research has shown that one-third of people who use varenicline are nonadherent by the second week. There is evidence showing that behavioral support helps with medication adherence. We have designed an artificial intelligence (AI) conversational agent or health bot, called "ChatV," based on evidence of what works as well as what varenicline is, that can provide these supports. ChatV is an evidence-based, patient- and health care provider-informed health bot to improve adherence to varenicline. ChatV has been programmed to provide medication reminders, answer questions about varenicline and smoking cessation, and track medication intake and the number of cigarettes.

OBJECTIVE

This study aims to explore the feasibility of the ChatV health bot, to examine if it is used as intended, and to determine the appropriateness of proceeding with a randomized controlled trial.

METHODS

We will conduct a mixed methods feasibility study where we will pilot-test ChatV with 40 participants. Participants will be provided with a standard 12-week varenicline regimen and access to ChatV. Passive data collection will include adoption measures (how often participants use the chatbot, what features they used, when did they use it, etc). In addition, participants will complete questionnaires (at 1, 4, 8, and 12 weeks) assessing self-reported smoking status and varenicline adherence, as well as questions regarding the acceptability, appropriateness, and usability of the chatbot, and participate in an interview assessing acceptability, appropriateness, fidelity, and adoption. We will use "stop, amend, and go" progression criteria for pilot studies to decide if a randomized controlled trial is a reasonable next step and what modifications are required. A health equity lens will be adopted during participant recruitment and data analysis to understand and address the differences in uptake and use of this digital health solution among diverse sociodemographic groups. The taxonomy of implementation outcomes will be used to assess feasibility, that is, acceptability, appropriateness, fidelity, adoption, and usability. In addition, medication adherence and smoking cessation will be measured to assess the preliminary treatment effect. Interview data will be analyzed using the framework analysis method.

RESULTS

Participant enrollment for the study will begin in January 2024.

CONCLUSIONS

By using predetermined progression criteria, the results of this preliminary study will inform the determination of whether to advance toward a larger randomized controlled trial to test the effectiveness of the health bot. Additionally, this study will explore the acceptability, appropriateness, fidelity, adoption, and usability of the health bot. These insights will be instrumental in refining the intervention and the health bot.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05997901; https://classic.clinicaltrials.gov/ct2/show/NCT05997901.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/53556.

Pairwise comparisons of three medication adherence outcomes in adolescents who use alcohol

BACKGROUND

Accurate assessment of medication adherence is important for understanding pharmacotherapy outcomes across all phases of adolescent substance use disorder (SUD) clinical trials. The objective of this study was to describe and assess the pairwise concordance between three commonly used non-biological medication adherence assessment methods in adolescents who use alcohol to inform the selection of medication adherence measures for use in future youth SUD trials.

METHODS

Participants (N = 32, 17-19-years-old) took N-acetylcysteine and placebo, in a randomized cross-over design, for 10 days each. Medication adherence was assessed (20 days total) via pill count, medication videos submitted twice daily, and the Medication Event Monitoring System (MEMS®). Lin's Concordance Correlation Coefficient (CCC) assessed concordance and Bland-Altman plots are reported. Linear mixed-effects models with main effects of medication, treatment block (first medication, second medication), and sequence were also run.

RESULTS

Medication videos yielded the lowest (64%) and pill count yielded the highest (89%) adherence estimates. CCC values indicated poor correspondence, except between pill count and MEMS. The Bland-Altman plots showed good pairwise agreement between all methods. Linear mixed-effects models indicated a difference between the first and second cross-over medication, with adherence estimates being lower for the second medication, regardless of whether it was N-acetylcysteine or placebo.

CONCLUSIONS

The study yielded important and practical information. First, incorporating more than one method of adherence assessment may capture estimated floor and ceiling adherence in the absence of a biological marker. This is particularly relevant for remote or hybrid studies where bio-marker collection is challenging. Selection of the assessment methods will depend on study goals. Second, the continuation of medication adherence research can benefit each phase of clinical trials and inform rigorous pharmacotherapy evaluation.

Treatment adherence in a smoking cessation clinical trial for individuals with current or past major depressive disorder: Predictors and association with cessation

INTRODUCTION

Individuals with major depressive disorder (MDD) exhibit high rates of tobacco use and lower responsiveness to tobacco cessation treatments. Treatment adherence is a strong predictor of treatment outcomes in the general population but has not been evaluated in this under-served community of smokers with MDD.

METHODS

We used data from a randomized clinical trial on smoking cessation treatment among 300 smokers with MDD to examine the rate of adherence (medication and counseling), the association of adherence with cessation outcomes, and factors associated with adherence, including demographic and smoking characteristics, psychiatric characteristics, smoking cessation processes (e.g., withdrawal, reinforcers), and treatment-related side effects (e.g., nausea).

RESULTS

Overall, 43.7% of participants were adherent with medication and 63.0% were adherent with counseling. Medication adherence was significantly associated with cessation, with 32.1% of adherent vs. 13.0% of non-adherent participants quitting smoking at EOT. Counseling adherence was also significantly associated with cessation, with 32.3% of adherent vs. 2.7% of non-adherent participants quitting smoking. Multivariate regression models showed that medication adherence was associated with higher engagement in complementary reinforcers and higher baseline smoking reward, while counseling adherence was associated with identifying as female, lower alcohol use and nicotine dependence, higher baseline smoking reward, and higher engagement in substitute and complementary reinforcers within the first weeks of medication use.

CONCLUSIONS

As with the general population of smokers, non-adherence to treatment in smokers experiencing depression is widespread and a significant barrier to cessation. Interventions that target reinforcers may improve rates of treatment adherence.

Repetitive transcranial magnetic stimulation for smoking cessation: Next steps for translation and implementation into clinical practice

Tobacco smoking is a significant determinant of preventable morbidity and mortality worldwide. It is now possible to modulate the activity of the neurocircuitry associated with nicotine dependence using repetitive Transcranial Magnetic Stimulation (rTMS), a non-invasive neurostimulation approach, which has recently demonstrated efficacy in clinical trials and received regulatory approval in the US and Canada. However there remains a paucity of replication studies and real-world patient effectiveness data as access to this intervention is extremely limited. There are a number of unique challenges related to the delivery of rTMS that need to be addressed prior to widespread adoption and implementation of this treatment modality for smoking cessation. In this paper, we review the accessibility, scientific, technological, economical, and social challenges that remain before this treatment can be translated into clinical practice. By addressing these remaining barriers and scientific challenges with rTMS for smoking cessation and delineating implementation strategies, we can greatly reduce the burden of tobacco-related disease worldwide.

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.

Medication Adherence in Tobacco Cessation Clinical Trials

Adherence is a critical mediator of treatment outcome across health conditions and low rates of adherence undermine success in smoking cessation treatment. This narrative review provides an overview of different techniques that can be used to measure adherence to smoking cessation treatments and outlines strategies to address treatment adherence. Techniques to measure adherence include conducting pill counts, collecting self-reports of adherence, directly observed therapy, biochemical verification methods, and electronic data collection via medication events monitoring systems. Techniques examined for increasing tobacco cessation treatment adherence include counseling, automated adherence calls, feedback from electronic monitors, contingency management and directly observed therapy. Adherence monitoring and optimization should be a standard component of smoking cessation treatment research.

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.

Factors associated with quitting among smoking cessation medication-assisted smokers and ex-smokers: A cross-sectional study in Australia

Effective smoking cessation medications (SCM) are available and are recommended for the treatment of tobacco smoking. In this study, we evaluated rate and factors associated with successful quitting among individuals who supported their quit attempt using SCMs in Australia. An observational online cross-sectional survey was conducted using a convenience sample of smokers and ex-smokers in Australia. A self-administered questionnaire was used to evaluate socio-demographic, psychological, smoking, and medication use characteristics. The Fagerstrom Test for Nicotine Dependence scale was used to assess the level of nicotine addiction. Logistic regression used to identify factors associated with smoking cessation. Of the 201 respondents, 33.3% had successfully quit smoking. Nicotine replacement therapy (NRT), varenicline, and bupropion were used by 71.6%, 19.9%, and 8.5% respectively. The rate of quitting was 30.6%, 47.5%, and 23.5% for participants who used NRT, varenicline, and bupropion, respectively. Six in ten (59.6%) of the participants who were adherent to SCMs reported continuous abstinence. Whereas 22.9% reported quitting among participants who were nonadherent to SCMs. Adherence to SCMs was significantly associated with increased rate of quitting (AOR = 2.67, 95% CI of 1.17-6.10). Additionally, having smoke-free home was associated with successful smoking cessation (AOR = 2.34, 95% CI of 1.13-4.90). In conclusion, one in three participants self-reported that they successfully quit smoking. Adherence to SCMs and smoke-free home were strongly associated with quitting. Smoking cessation programs and future studies are recommended to incorporate medication adherence as a core component. Home-targeted and family-inclusive interventions are recommended to manage smoke-free homes and enhance success of quitting attempts.

Cocreation of a conversational agent to help patients adhere to their varenicline treatment: A study protocol

Objective

Varenicline is the most efficacious approved smoking cessation medication, making it one of the most cost-effective clinical interventions for reducing tobacco-related morbidity and mortality. Adhering to varenicline is strongly associated with smoking cessation. Healthbots have the potential to help people adhere to their medications by scaling up evidence-based behavioral interventions. In this protocol, we outline how we will follow the UK's Medical Research Council's guidance to codesign a theory-informed, evidence-based, and patient-centered healthbot to help people adhere to varenicline.

Methods

The study will utilize the Discover, Design and Build, and Test framework and will include three phases: (a) a rapid review and interviews with 20 patients and 20 healthcare providers to understand barriers and facilitators to varenicline adherence (Discover phase); (b) Wizard of Oz test to design the healthbot and get a sense of the questions that chatbot has to be able to answer (Design phase); and (c) building, training, and beta-testing the healthbot (Building and Testing phases) where the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework will be used to develop the healthbot using the simplest sensible solution, and 20 participants will beta test the healthbot. We will use the Capability, Opportunity, Motivation-Behavior (COM-B) model of behavior change and its associated framework, the Theoretical Domains Framework, to organize the findings.

Conclusions

The present approach will enable us to systematically identify the most appropriate features for the healthbot based on a well-established behavioral theory, the latest scientific evidence, and end users' and healthcare providers' knowledge.

Assessment of patient perception of treatment assignment and patient-reported outcomes in a cannabis use disorder trial

Background: Blinding is a cornerstone of trial methodology. Prior work indicates participant-perceived assignment may be associated with trial outcomes. Less is known about how perception changes over time and if this is associated with outcomes.Objectives: To evaluate if participants change their perception of assignment over time in a blinded trial, and if perception is associated with different types of patient-reported outcomes (PROs).Methods: This was a secondary analysis of data from the Achieving Cannabis Cessation-Evaluating N-Acetylcysteine Treatment (ACCENT) trial, which evaluated the efficacy of N-acetylcysteine (NAC) relative to placebo for treating cannabis use disorder. Participants (N = 234; 164 men, 70 women) were asked at weeks 5 and 9 what treatment (placebo or NAC) they believed they were receiving. We included PROs proximal (cannabis-associated problems, craving) and distal (anxiety) to the intervention. Analysis was by multiple linear regression and mixed models.Results: Approximately 20% of participants in both arms changed their perception over time. Relative to participants who consistently perceived assignment to placebo, participants who consistently perceived assignment to NAC did not always have comparatively better average scores (coefficient -3.3 [95% CI: -7.0, 0.5]). In some analyses, participants who switched to guessing NAC from placebo had comparatively better average scores (coefficient -3.0 [95% CI: -9.3, 3.4]), but this was inconsistent across outcomes or strata defined by actual assignment or guess accuracy.Conclusion: The study suggests that the proportion of individuals who switch their perception over time is modest. However, this group may influence the estimates of intervention effects on some PROs.

Characterising the use of varenicline: an analysis of the Australian dispensing claims data

BACKGROUND AND AIMS

In Australia, patterns of use of smoking cessation medications and factors associated with their dispensing are currently not known. This study aimed to measure the demographic and clinical factors associated with varenicline dispensing compared with nicotine replacement therapy (NRT) and bupropion among first-time users of Pharmaceutical Benefits Scheme (PBS) subsidised smoking cessation medicines in Australia and to characterise those who discontinued varenicline treatment prematurely.

DESIGN

Retrospective, population-based study. Logistic regression was used to identify factors associated with varenicline dispensing compared with NRT and bupropion. Sensitivity analyses estimated the proportion of individuals who completed the recommended 12 weeks of varenicline treatment.

SETTING AND PARTICIPANTS

First-time users of PBS subsidised smoking cessation medicines in Australia. Individuals first dispensed a smoking cessation medicine between 2011 and 2019 were identified from a 10% random sample of the national dispensing claims data.

MEASUREMENTS

The outcome for the regression analysis was the dispensing of varenicline compared with NRT and bupropion. The dispensing of a smoking cessation medicine was identified using the World Health Organization Anatomical Therapeutic Chemical Classification System and PBS item codes. Independent variables included demographic and clinical characteristics such as sex, age, concessional status, year of treatment initiation and comorbidities identified using the Rx-Risk index. The proportion of people who discontinued varenicline treatment after the initiation pack was determined using prescription refill data.

FINDINGS

A total of 94 532 people had their first PBS subsidised smoking cessation medicine. Of these, 62 367 (66.0%) were dispensed varenicline, 29 949 (31.7%) NRT and 2216 (2.3%) bupropion. The odds of varenicline dispensing were higher in males (OR, 1.18; 95% CI, 1.14-1.21), but lower in older adults (0.86 [0.82-0.90] in above 30 years to 0.49 [0.47-0.52] in 61 years and above), among concession beneficiaries (0.44; 0.43-0.46), and those with congestive heart failure (0.60; 0.53-0.68), depression (0.61; 0.54-0.69), anxiety (0.70; 0.66-0.73), psychotic illness (0.39; 0.37-0.42), and chronic obstructive pulmonary disease (0.87; 0.82-0.92). The majority (37 670; 60.4%) of those dispensed varenicline discontinued treatment after the initiation pack. Anxiety and psychotic illnesses were significantly more prevalent in those who discontinued treatment. Only 2804 (4.5%) of those dispensed varenicline completed 12 weeks of treatment.

CONCLUSION

Individuals dispensed varenicline in Australia appear to be healthier compared with those who are dispensed nicotine replacement therapy or bupropion.

Experiences of hospitalized smokers initiated on varenicline as part of a pragmatic smoking cessation trial

Varenicline is an effective monotherapy for smoking cessation, but adherence is often suboptimal. This qualitative study explored the experiences of varenicline treatment among participants enrolled in a randomized controlled trial, who self-reported being adherent or nonadherent to varenicline treatment (n = 15). Individual interviews were conducted using a semi-structured interview guide. Data were analyzed using thematic framework approach. An environment of forced abstinence played a key role in motivating quit attempts. The main barriers to varenicline adherence were medicine-related side effects, relapse to smoking, and a belief that the medication was not working if abstinence was not achieved by the target quit date. Participants adherent to treatment adopted a reduce-to-quit approach and noticed a gradual reduction in cigarette cravings. When asked about their preferences for support while on varenicline treatment, participants expressed the need for proactive follow-up by health professionals and more active behavioral support to assist them in adhering to treatment. Prescribers should encourage varenicline users to persist with treatment, even if abstinence is not achieved by the target quit date. Further research is needed to explore the awareness and acceptability of the reduce-to-quit method among prescribers and patients and its impact on varenicline adherence and in term long-term abstinence.

Addressing smoking in sheltered homelessness with intensive smoking treatment (ASSIST project): A pilot feasibility study of varenicline, combination nicotine replacement therapy and motivational interviewing

BACKGROUND

This pilot study aimed to test the feasibility of providing varenicline in combination with nicotine replacement therapy (NRT) and motivational interviewing (MI) to adult male smokers attending a clinic in a hostel for homeless people.

METHODS

A single group pre- and post-treatment (12 weeks following intervention commencement) design with embedded process evaluation (at weekly counselling and fortnightly safety check-ins). Participants were 20 male smokers attending a health clinic within a homelessness service in Sydney, Australia, between December 2019 and March 2020. Participants set a target quit date 7-days post intervention commencement. Adverse events, self-reported abstinence, cigarettes per day, treatment adherence and acceptability of the study interventions were assessed 12 weeks post intervention commencement. Abstinence was biochemically verified. Results are complete cases.

RESULTS

Retention was 65% at 12-weeks post-intervention commencement (n = 13). No related adverse events were reported. Three participants (15%) reported continuous abstinence. Two participants self-reported 30-day point prevalence abstinence (10%), confirmed by CO level. Participants who did not quit smoking (n = 10), reported a significant reduction in the number of cigarettes smoked per day (19.4 vs 4.7, p < .01). Cravings, withdrawal symptoms, and psychological distress significantly decreased from baseline to 12-week follow-up (all < 0.01). Adherence to the pharmacological interventions was good, most used combination NRT and varenicline. Adherence to the counselling sessions was low, attending three of 12 sessions. Both NRT and MI were rated as highly acceptable. Some participants expressed concerns about the safety of varenicline.

CONCLUSIONS

The intervention was feasible and acceptable and associated with short-term smoking cessation and significant reductions in the number of cigarettes smoked-per-day.

Predictors of Adherence to Smoking Cessation Medications among Current and Ex-Smokers in Australia: Findings from a National Cross-Sectional Survey

Background: Adherence to smoking cessation medications (SCMs) improve the rate of successful quitting. This study aimed to evaluate the level of adherence to SCMs and associated factors among smokers and ex-smokers in Australia. Method: A cross-sectional study using an online survey was conducted in Australia. Descriptive statistics were used to present the overall characteristics of participants. Cross-tabulation with Pearson’s chi-square test was performed to evaluate the possible associations between factors. To explore barriers and facilitators of adherence to SCMs, logistic regressions were conducted. Results: Among 201 participants, 57 (28.4%) were found to be adherent to SCMs. The odds of being adherent were found to be higher among participants with good social support (AOR = 3.28, 95% CI of 2.30–6.27). Participants who did not experience anxiety symptoms had higher odds of being adherent to SCMs as compared to smokers who had anxiety symptoms (AOR = 4.41, 95% CI of 3.64–14.68). Having previous experience of using SCMs improved adherence four-fold (AOR = 3.87, 95% CI of 1.11–13.44). Level of nicotine dependence showed a direct association with adherence (AOR = 3.53, 95% CI of 1.40–8.95). Not relapsing while on the medications improved adherence (AOR = 2.88, 95% CI of 1.21–6.88). Conclusion: In a study of smokers and ex-smokers in Australia, the self-reported level of adherence to SCMs was found to be low. Adherence was associated with social, psychological, and medication-related factors. Smoking cessation interventions are recommended to include strategies that can address medication adherence.

Design and methods of a randomized trial testing the novel Wellness Intervention for Smokers Living with HIV (WISH)

Smoking rates are disproportionately high among people living with HIV. Smokers living with HIV (SLWH) are also largely unaware of the HIV-specific deleterious effects of smoking and often lack motivation and confidence in their ability to quit tobacco. To address these issues, we developed the Wellness Intervention for Smokers Living with HIV (WISH). WISH is grounded in the Information-Motivation-Behavioral Skills (IMB) Model and is designed for all SLWH, regardless of their initial motivation to quit. It follows evidence-based, best practice guidelines for nicotine dependence treatment, but is innovative in its use of a comprehensive wellness approach that addresses smoking within the context of HIV self-management including treatment adherence and engagement, stress management, substance use, and other personally relevant health behavior goals. The described randomized trial will enroll SLWH who are receiving care at Veterans Affairs (VA) medical centers and compare WISH's impact on smoking behavior to standard care services offered through the National VA Quitline and SmokefreeVET texting program. It will also assess intervention impact on markers of immune status and mortality risk. If effective, WISH could be disseminated to Veterans nationwide and could serve as a model for designing quitline interventions for other smokers who are ambivalent about quitting. The current paper outlines the rationale and methodology of the WISH trial, one of a series of studies recently funded by the National Cancer Institute to advance understanding of how to better promote smoking cessation among SLWH.

The estimand framework and its application in substance use disorder clinical trials: a case study

Relapse rates among individuals with substance use disorder (SUD) remain high and new treatment approaches are needed, which require evaluation in randomized controlled trials (RCTs). Measurement and interpretation challenges for SUD RCT data are often ignored or presented only in statistical analysis plans. Since different analytic approaches may result in different estimates and thus interpretations of the treatment effect, it is important to present this clearly throughout the trial. Inconsistencies between study analyses and objectives present further challenges for interpretation and cross-study comparisons. The recent International Council for Harmonization (ICH) addendum provides standardized language and a common framework for aligning trial objectives, design, conduct, and analysis. The framework focuses on estimands, which describe the treatment effect and link the trial objective with the scientific question and the analytic approach. The use of estimands offers SUD researchers and clinicians the opportunity to explicitly address events that affect measurement and interpretation at the outset of the trial. Furthermore, the use of standard terminology can lead to clearer interpretations of SUD trials and the treatments evaluated in SUD trials. Resources for understanding and applying estimands are needed to optimize the use of this new, helpful framework. This Perspective provides this resource for SUD researchers. Specifically, it highlights the relevance of estimands for SUD trials. Furthermore, it demonstrates how estimands can be used to develop clinically relevant analyses to address challenges in SUD trials. It also shows how a standardized framework can be employed to improve the interpretation and presentation of SUD study findings.

Adherence and Efficacy of Smoking Cessation Treatment Among Patients with COPD in China

Background

Smoking cessation is a key intervention for all smokers with chronic obstructive pulmonary disease (COPD). Poor treatment adherence is a challenge in clinical practice that might contribute to the lower efficacy of medication (eg, oral drug). However, it is unclear what factors will influence adherence among smokers with COPD.

Methods

This study was based on an open-label randomized controlled trial (RCT) of varenicline and bupropion for smoking cessation among patients with COPD in China. The medication was given for 12 weeks, and visits and assessments were conducted at weeks 0, 1, 2, 4, 6, 9, 12, and 24. We assessed whether the adherence to smoking cessation treatment affects the smoking cessation efficacy and evaluated predictors of adherence.

Results

A total of 136 participants were recruited from February 2019 to June 2020, and analyzed using the intention-to-treat (ITT) method. In this study, 48.5% (66/136) of the total participants had good adherence to smoking cessation, and good adherence significantly improved the efficacy of smoking cessation (OR=9.60, 95% CI 4.02–22.96, P < 0.001). After adjusting for age, gender, nationality, education, and marital status, we found older age, higher education level, having more previous quitting attempts, stronger self-efficacy and preparation in quitting smoking, recognizing hazards of smoking, longer duration of COPD, and higher St. George’s Respiratory Questionnaire (SGRQ) scores were relevant to good adherence (P < 0.05).

Conclusion

To our best knowledge, this is the first study to evaluate adherence to smoking cessation treatment among patients with COPD in China. Our study found that good adherence to smoking cessation treatment significantly improved the smoking cessation efficacy, and predictors of adherence were evaluated. We call on the medical community to pay attention to the adherence to smoking cessation among patients with COPD.

Effect of varenicline directly observed therapy versus varenicline self-administered therapy on varenicline adherence and smoking cessation in methadone-maintained smokers: a randomized controlled trial

BACKGROUND AND AIMS

Level of adherence to tobacco cessation medication regimens is believed to be causally related to medication effectiveness. This study aimed to evaluate the efficacy of varenicline directly observed therapy (DOT) on varenicline adherence and smoking cessation rates among smokers with opioid use disorder (OUD) receiving methadone treatment.

DESIGN

Multicenter, parallel-group two-arm randomized controlled trial.

SETTING

Urban opioid treatment program (OTP) in the Bronx, New York, USA.

PARTICIPANTS

Daily smokers of ≥ 5 cigarettes/day, interested in quitting (ladder of change score 6-8), in methadone treatment for ≥ 3 months, attending OTP ≥ 3 days/week. Participants' mean age was 49 years, 56% were male, 44% Latino, 30% Black, and they smoked a median of 10 cigarettes/day.

INTERVENTIONS

Individual, block, random assignment to 12 weeks of varenicline, either directly observed with methadone (DOT, n = 50) or via unsupervised self-administered treatment (SAT, n = 50).

MEASUREMENTS

The primary outcome was adherence measured by pill count. The secondary outcome was 7-day point prevalence tobacco abstinence verified by expired carbon monoxide (CO) < 8 parts per million.

FINDINGS

Retention at 24 weeks was 92%. Mean adherence was 78.5% [95% confidence interval (CI) = 71.8-85.2%] in the DOT group versus 61.8% in the SAT group (95% CI = 55.0-68.6%); differences were driven by DOT effects in the first 6 weeks. CO-verified abstinence did not differ between groups during the intervention (P = 0.26), but was higher in the DOT than the SAT group at intervention end (DOT = 18% versus SAT = 10%, difference = 8%, 95% CI = -13, 28); this difference was not significant (P = 0.39) and was not sustained at 24-week follow-up.

CONCLUSIONS

Among daily smokers attending opioid treatment programs, opioid treatment program-based varenicline directly observed therapy was associated with early increases in varenicline adherence compared with self-administered treatment, but findings were inconclusive as to whether directly observed therapy was associated with a difference in tobacco abstinence.

Reciprocal influences of tobacco use on illicit opioid and alcohol use during the first six-months of specialist addiction treatment

BACKGROUND

This is the first national study of lagged reciprocal associations between tobacco smoking frequency and change in illicit opioid or alcohol use frequency within six-months of treatment.

METHODS

All adults admitted to publicly-funded specialist addiction treatment in England in 2018/19 and enrolled for at least six months for either opioid use disorder (OUD; n = 22,046; 82.4 % of those eligible) or alcohol use disorder (AUD; n = 15,251; 78.8 % of those eligible). Two cross-lagged panel models estimated, separately for OUD and AUD patients, the relationships between smoking at admission and change in main drug over six months, and between main drug use at admission and change in smoking over six months.

RESULTS

Within the OUD cohort, illicit opioid use frequency reduced from 17.7 days to 8.0 days and smoking tobacco remained at 18.8 days. After controlling for available covariates, higher smoking frequency at admission was associated with a relative increase in illicit opioid use at six-months (0.02 days [95 % CI 0.00-0.03]). Within the AUD cohort, alcohol use frequency reduced from 21.2 days to 14.4 days while smoking tobacco reduced from 12.6 days to 11.5 days. Higher smoking frequency at admission was associated with a relative increase in alcohol use at six-months (0.03 days [95 % CI 0.02-0.04]) and higher alcohol use frequency at admission was associated with a relative increase in smoking at six-months (0.04 [95 % CI 0.02-0.06]), controlling for available covariates.

CONCLUSIONS

Higher smoking frequency at admission is associated with higher illicit opioid and alcohol use frequency after six-months of specialist addiction treatment.

Barriers and Facilitators of Adherence to Nicotine Replacement Therapy: A Systematic Review and Analysis Using the Capability, Opportunity, Motivation, and Behaviour (COM-B) Model

BACKGROUND

Poor adherence to nicotine replacement therapy (NRT) is associated with low rates of smoking cessation. Hence, this study aims to identify and map patient-related factors associated with adherence to NRT using the capability, opportunity, motivation, and behaviour (COM-B) model.

METHODS

A systematic review was conducted by searching five databases (MEDLINE, Scopus, EMBASE, CINAHL, and PsycINFO) and grey literature on 30 August 2020. Data were extracted, thematically analysed, and mapped to the COM-B model. The Joanna Briggs Institute (JBI) critical appraisal tool was utilised to assess the quality of studies.

RESULTS

A total of 2929 citations were screened, and 26 articles with a total of 13,429 participants included. Thirty-one factors were identified and mapped to COM-B model: psychological capability (forgetfulness, education), physical capability (level of nicotine dependence, withdrawal symptoms), reflective motivation (perception about NRT and quitting), automatic motivation (alcohol use, stress, depression), physical opportunity (cost), and social opportunity (social support). The most prominent element associated with adherence was reflective motivation followed by physical capability and automatic motivation.

CONCLUSIONS

Multiple personal, social, and environmental factors affect NRT adherence. Hence, it is recommended to implement a multifaceted behavioural intervention incorporating factors categorised under the COM-B model, which is the hub of the behaviour change wheel (BCW) to improve adherence and quitting.

Electronically Monitored Nicotine Gum Use Before and After Smoking Lapses: Relationship With Lapse and Relapse

INTRODUCTION

Greater use of nicotine replacement therapy (NRT) is related to smoking cessation success, but the causal direction is unclear. This study characterized the relationship between NRT use and smoking lapse and relapse.

METHODS

Participants (N = 416 smokers; 57% female, 85% White) were recruited from primary care for a smoking cessation factorial experiment and analyzed if abstaining ≥1 day in the first 2 weeks post-target quit day (TQD). Participants were randomized to counseling and 8 versus 26 weeks of nicotine patch plus nicotine gum post-TQD. Participants carried electronic dispensers that timestamped each gum use. Participants who lapsed (smoked after abstaining) within 6 weeks post-TQD were matched with nonlapsers (n = 146 pairs) on multiple variables. We compared lapsers' versus matched nonlapsers' gum use in the 5 days before and after the lapsers' first lapse.

RESULTS

By week 6 post-TQD, 63% of participants lapsed. Compared with nonlapsers, lapsers used less gum 1 and 2 days pre-"lapse" and on the 5 days post-lapse. Lapsers used less gum during the 5 days post-lapse than the 5 days pre-lapse. Univariate survival analyses with lapsers showed greater gum use during both pre- and post-lapse periods predicted longer latency to relapse in the first 6 weeks.

CONCLUSIONS

In a smoking cessation attempt using nicotine patch plus gum, lapsers versus matched nonlapsers used less gum immediately preceding and following their first lapse. Lower mean gum use before and after lapses predicted a more rapid escalation to relapse. Decreased nicotine gum use both precedes and follows returns to smoking during cessation attempts.

IMPLICATIONS

This research examined electronically monitored nicotine gum use collected in real time and found that among smokers engaged in a quit attempt, lapsers (vs. matched nonlapsers) tended to decrease their gum use 1-2 days prior to lapsing and to further decrease their gum use from pre- to post-lapse. Decreased gum use pre-lapse may signal heightened lapse risk in 1-2 days, with lower level of gum use predicting a more precipitous course of relapse. These results encourage further exploration of objective measures of smoking medication use patterns to examine their signaling properties and to inform understanding of cessation failure.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT01120704.

Quitting Failure and Success With and Without Using Medication: Latent Classes of Abstinence and Adherence to Nicotine Monotherapy, Combination Therapy, and Varenicline

INTRODUCTION

Nonadherence to pharmacotherapies complicates studies of comparative pharmacotherapy effectiveness. Modeling adherence and abstinence simultaneously may facilitate analysis of both treatment acceptability and effectiveness.

METHODS

Secondary analyses of a three-arm randomized comparative trial of nicotine patch, varenicline, and combination nicotine patch and lozenge among adult daily smokers (N = 1086) were conducted. Adherence rates collected via interactive voice response systems during the first 27 days of quitting were compared across treatment conditions. Repeated measures latent class analyses of adherence and abstinence in 3-day parcels through 27 days of a quit attempt were conducted with treatment, demographic, and smoking history covariates.

RESULTS

Adherence varied across treatments and was lowest for nicotine lozenge use in combination nicotine replacement therapy (NRT). Five latent classes that differed significantly in 6-month abstinence rates were retained, including three subgroups of adherent participants varying in treatment response and two nonadherent groups varying in abstinence probabilities. Nonadherence was more likely among those receiving varenicline and combination NRT, relative to patch monotherapy. Varenicline and combination NRT did not promote abstinence among adherent latent classes but did promote abstinence among those partially adherent, relative to patch alone. Combination therapy attenuated increased risk of treatment disengagement with more years smoking. Minority smokers, those high in dependence, and those with shorter past abstinence were at increased risk for low-adherence and low-abstinence latent classes.

CONCLUSIONS

Varenicline and combination nicotine patch and lozenge are less likely to be used as directed and may not increase first-month abstinence better than patch alone when taken adherently.

IMPLICATIONS

This secondary analysis of adherence and abstinence in a comparative effectiveness trial shows that adherence is highest for the nicotine patch, next highest for varenicline, and lowest for combination nicotine patch and lozenge therapy due to low lozenge use. Distinct latent classes were found that varied in both first-month abstinence and adherence. Varenicline and combination NRT may not enhance abstinence over patch alone among smokers who take medication adherently. Adherent use of medication especially benefits those who are low in dependence and have positive quitting histories; it is less beneficial to at-risk smokers and members of racial minorities.

Predictors of Varenicline Adherence Among Cancer Patients Treated for Tobacco Dependence and its Association With Smoking Cessation

INTRODUCTION

The degree to which smokers adhere to pharmacotherapy predicts treatment success. The development of interventions to increase adherence requires identification of predictors of treatment adherence, particularly among specific clinical populations.

METHODS

Using data from a 12-week open-label phase of a clinical trial of varenicline for tobacco dependence among cancer patients (N = 207), we examined: (1) the relationship between self-reported varenicline adherence and verified smoking cessation and (2) demographic and disease-related variables, and early changes in cognition, affect, withdrawal, the reinforcing effects of smoking, and medication side effects, as correlates of varenicline adherence.

RESULTS

At the end of 12 weeks, 35% of the sample had quit smoking and 52% reported taking ≥80% of varenicline. Varenicline adherence was associated with cessation (p < .001): 58% of participants who were adherent had quit smoking versus 11% of those who were not. Participants who experienced early reductions in depressed mood and satisfaction from smoking and experienced an increase in the toxic effects of smoking, showed greater varenicline adherence (p < .05); the relationship between greater adherence and improved cognition, reduced craving, and reduced sleep problems and vomiting approached significance (p < .10).

CONCLUSIONS

Among cancer patients treated for tobacco dependence with varenicline, adherence is associated with smoking cessation. Initial changes in depressed mood and the reinforcing effects of smoking are predictive of adherence.

IMPLICATIONS

The benefits of varenicline for treating tobacco dependence among cancer patients may depend upon boosting adherence by addressing early signs of depression and reducing the reinforcing dimensions of cigarettes.

Correlates of varenicline adherence among smokers with HIV and its association with smoking cessation

INTRODUCTION

With medical advances, the life expectancy of people living with HIV/AIDS (PLWHA) has improved; however, tobacco use remains a prominent risk for mortality. Although studies have examined the efficacy of varenicline for treating smoking among PLWHA, the relationship between varenicline adherence and cessation and correlates of varenicline adherence remain under-studied.

METHODS

We conducted secondary analyses from a randomized placebo-controlled trial of varenicline for smoking among PLWHA, using data from participants who received varenicline (N = 89). The relationship between varenicline adherence (based on pill count) and end-of-treatment smoking cessation was assessed, as were correlates of varenicline adherence.

RESULTS

Those who were abstinent took an average of 137.1 pills (SD = 39.3), or 83% of pills prescribed, vs. 105.3 pills (SD = 64.1), or 64%, for those who were smoking (OR = 1.01, 95% CI: 1.001-1.021, p = 0.03); 52/89 (58%) participants were adherent based on taking ≥80% of pills. The quit rate for adherent participants was 35% (18/52) vs. 19% (7/37) for non-adherent participants. Adherent participants were older, smoked fewer cigarettes each day, started smoking at an older age, and had lower baseline creatinine vs. non-adherent participants (p < 0.05). There was a significant time-by-group interaction effect for anxiety (F[1,72] = 6.24, p = 0.02), depression (F[1,72] = 4.2, p = 0.04), and insomnia (F[1,72] = 7.73, p = 0.007), indicating that adherent participants had less depression, anxiety, and insomnia during the initial weeks of treatment, vs. non-adherent participants.

CONCLUSIONS

Our findings underscore the importance of varenicline adherence for determining cessation and highlight the role of early changes in anxiety, depression, and insomnia determining varenicline adherence.

Impact of early nausea on varenicline adherence and smoking cessation

BACKGROUND AND AIMS

Varenicline effectiveness may be related to the level of adherence, which might be reduced by adverse effects such as nausea. The aim of the study was to test a possible effect of nausea on smoking cessation outcomes mediated by adherence.

DESIGN

Mediation path analysis.

SETTING

Multiple sites within Canada and the United States.

PARTICIPANTS

Treatment-seeking smokers receiving varenicline from two smoking cessation clinical trials: Quit2Live (NCT01836276; n = 449) and Pharmacogenetics of Nicotine Addiction Treatment (PNAT) (NCT01314001; n = 421).

MEASUREMENTS

Nausea severity was collected through self-report and adherence was biologically assessed using varenicline concentrations (Quit2Live, plasma sample at week 4; PNAT, saliva sample at week 2). In Quit2Live, the end-points were cotinine-verified abstinence at weeks 4, 12 and 26. In PNAT, the end-points were carbon monoxide-verified abstinence at weeks 2, 12 and 26.

FINDINGS

Early nausea was not directly associated with abstinence [odds ratio (OR) ranging from 0.73-1.28; P ≥ 0.26]. However early nausea was indirectly associated with lower cessation rates at multiple timepoints (ORs ranging from 0.92-0.94; 95% CI between 0.83-0.99) in a relationship mediated by reduced varenicline adherence (assessed by plasma varenicline concentrations) in the primary trial (Quit2Live). This relationship between nausea, adherence and cessation was similar in direction but weaker in effect size (ORs ranging from 0.98-0.99; 95% CI between 0.90-1.03) in a secondary trial (PNAT), where adherence was assessed using salivary varenicline concentrations.

CONCLUSIONS

These data suggest that early nausea during varenicline treatment may be indirectly associated with lower likelihood of smoking cessation through reducing varenicline adherence. Differences in robustness between the trials may be due to the different biological matrices (plasma vs. saliva) and/or timing used to assess varenicline adherence. The results of the first study suggest that improved management of early nausea during varenicline treatment may positively impact smoking cessation success through increasing varenicline adherence.

Longitudinal associations between smoking and affect among cancer patients using varenicline to quit smoking

During a quit attempt, high negative affect predicts relapse to smoking. In this study, we evaluated bidirectional longitudinal associations between smoking and negative affect among cancer patients treated with varenicline. Participants (N = 119, 50% female, Mage = 59 years) were smokers (≥5 cigarettes/week) who were diagnosed with cancer and were recruited for a 24-week trial of extended duration varenicline plus behavioral counseling; data for this secondary analyses were drawn from the 12-week open-label phase of the trial. Smoking was assessed via self-reported number of cigarettes in the past 24 h. Negative affect was assessed using the Positive and Negative Affect Scale (PANAS). Data were collected at pre-quit (week 0), target quit day (week 1), week 4, and week 12. We evaluated cross-lagged panel models for negative affect and smoking using PROC CALIS in SAS. Models were run separately for participants who were adherent (≥80% of medication taken) or nonadherent to varenicline. Among adherent participants (n = 96), smoking accounted for up to 22% of variance in subsequent negative affect throughout treatment. Cross-lagged associations were not observed between smoking and negative affect among non-adherent participants (n = 23). Negative affect did not predict subsequent smoking among either adherent or nonadherent participants. These results suggest that varenicline may attenuate abstinence-induced negative affect among cancer patients treated for nicotine dependence.

Placebo-controlled randomized clinical trial testing the efficacy and safety of varenicline for smokers with HIV

BACKGROUND

People living with HIV/AIDS (PLWH) smoke tobacco at higher rates and have more difficulty quitting than the general population, which contributes to significant life-years lost. The effectiveness of varenicline, one of the most effective tobacco dependence treatments, is understudied in HIV. We evaluated the safety and efficacy of varenicline for smoking cessation among PLWH.

METHODS

This was a single-site randomized, double-blind, placebo-controlled, phase 3 clinical trial (NCT01710137). PLWH on antiretroviral therapy (ART) who were treatment-seeking daily smokers were randomized (1:1) to 12 weeks of varenicline (n = 89) or placebo (n = 90). All participants were offered six smoking cessation behavioral counseling sessions. The primary outcome was 7-day point prevalence abstinence, confirmed with breath carbon monoxide, at Weeks 12 and 24. Continuous abstinence and time to relapse were secondary outcomes. Safety measures were treatment-related side effects, adverse events, blood pressure, viral load, and ART adherence.

RESULTS

Of the 179 smokers, 81% were African American, and 68% were male. Varenicline increased cessation at Week 12 (28.1% vs. 12.1%; OR = 4.54, 95% CI:1.83-11.25, P = .001). Continuous abstinence from Week 9 to 12 was higher for varenicline vs. placebo (23.6% vs. 10%; OR = 4.65, 95% CI:1.71-12.67, P = .003); at Week 24, there was no effect of varenicline for point prevalence (14.6% vs. 10%), continuous abstinence (10.1% vs. 6.7%), or time to relapse (Ps > .05). There were no differences between varenicline and placebo on safety measures (Ps > .05).

CONCLUSIONS

Varenicline is safe and efficacious for short-term smoking cessation among PLWH and should be used to reduce tobacco-related life-years lost in this population.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further.

OBJECTIVES

To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy).

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer.

DATA COLLECTION AND ANALYSIS

For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model.

MAIN RESULTS

Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.

Combining Real-Time Ratings With Qualitative Interviews to Develop a Smoking Cessation Text Messaging Program for Primary Care Patients

Background

Text messaging (short message service, SMS) interventions show promise as a way to help cigarette smokers quit. Few studies have examined the effectiveness of text messaging (SMS) programs targeting smokers associated with primary care or hospital settings.

Objective

This study aimed to develop a text messaging (SMS) program targeting primary care smokers.

Methods

Adult smokers in primary care were recruited from February 2017 to April 2017. We sent patients 10 to 11 draft text messages (SMS) over 2 days and asked them to rate each message in real time. Patients were interviewed daily by telephone to discuss ratings, message preferences, and previous experiences with nicotine replacement therapy (NRT). Content analysis of interviews was directed by a step-wise text messaging (SMS) intervention development process and the Information-Motivation-Behavioral Skills model of medication adherence.

Results

We sent 149 text messages (SMS) to 15 patients. They replied with ratings for 93% (139/149) of the messages: 134 (96%, 134/139) were rated as clear or useful and 5 (4%, 5/139) as unclear or not useful. Patients’ preferences included the addition of graphics, electronic cigarette (e-cigarette) content, and use of first names. Regarding NRT, patients identified informational gaps around safety and effectiveness, preferred positively framed motivational messages, and needed behavioral skills to dose and dispose of NRT.

Conclusions

Patients recommended text message (SMS) personalization, inclusion of e-cigarette information and graphics, and identified barriers to NRT use.

Combining real-time ratings with telephone interviews is a feasible method for incorporating primary care patients’ preferences into a behavioral text messaging (SMS) program.

Proactive text messaging (GetReady2Quit) and nicotine replacement therapy to promote smoking cessation among smokers in primary care: A pilot randomized trial protocol

INTRODUCTION

Most smokers see a physician each year, but few use any assistance when they try to quit. Text messaging programs improve smoking cessation in community and school settings; however, their efficacy in a primary care setting is unclear. The current trial assesses the feasibility and preliminary clinical outcomes of text messaging and mailed nicotine replacement therapy (NRT) among smokers in primary care.

METHODS

In this single-center pilot randomized trial, eligible smokers in primary care are offered brief advice by phone and randomly assigned to one of four interventions: (1) Brief advice only, (2) text messages targeted to primary care patients and tailored to quit readiness, (3) a 2-week supply of nicotine patches and/or lozenges (NRT), and (4) both text messaging and NRT. Randomization is stratified by practice and intention to quit. The text messages (up to 5/day) encourage those not ready to quit to practice a quit attempt, assist those with a quit date through a quit attempt, and promote NRT use. The 2-week supply of NRT is mailed to patients' homes.

RESULTS

Feasibility outcomes include recruitment rates, study retention, and treatment adherence. Clinical outcomes are assessed at 1, 2, 6, and 12-weeks post-enrollment. The primary outcome is ≥1self-reported quit attempt(s). Secondary clinical outcomes include self-reported past 7- and 30-day abstinence, days not smoked, NRT adherence, and exhaled carbon monoxide.

CONCLUSIONS

This pilot assesses text messaging plus NRT, as a proactively offered intervention for smoking cessation support in smokers receiving primary care and will inform full-scale randomized trial planning.

TRIAL REGISTRATION

ClinicalTrials.govNCT03174158.

Adherence to Pharmacological Smoking Cessation Interventions: A Literature Review and Synthesis of Correlates and Barriers

Introduction

Efficacious pharmacological interventions for smoking cessation are available, but poor adherence to these treatments may limit these interventions overall impact. To improve adherence to smoking cessation interventions, it is first necessary to identify and understand smoker-level characteristics that drive nonadherence (ie, nonconformance with a provider's recommendation of timing, dosage, or frequency of medication-taking during the prescribed length of time).

Methods

We present a literature review of studies examining correlates of, or self-reported reasons for, nonadherence to smoking cessation pharmacotherapies. Studies were identified through PubMed-using MeSH terms, Embase-using Emtree terms, and ISI Web of Science.

Results and Conclusions

This literature review included 50 studies that examined nonpreventable (eg, sociodemographics) and preventable (eg, forgetfulness) factors associated with adherence to smoking cessation medication and suggestions for overcoming some of the identified barriers. Systematic study of this topic would be facilitated by consistent reporting of adherence and correlates thereof in the literature, development of consistent definitions of medication adherence across studies, utilization of more objective measures of adherence (eg, blood plasma levels vs. self-report) in addition to reliance on self-reported adherence.

Implications

This article provides the most comprehensive review to date on correlates of adherence to pharmacological smoking cessation interventions. Challenges and specific gaps in the literature that should be a priority for future research are discussed. Future priorities include additional research, particularly among vulnerable populations of smokers, developing standardized definitions of adherence and methods for measuring adherence, regular assessment of cessation pharmacotherapy adherence in the context of research and clinical practice, and development of novel treatments aimed at preventable barriers to medication adherence.

Predicting smoking abstinence with biological and self-report measures of adherence to varenicline: Impact on pharmacogenetic trial outcomes

INTRODUCTION

Adherence to pharmacotherapies for tobacco dependence, such as varenicline, is necessary for effective treatment. The relationship between varenicline adherence, determined by commonly used indirect (i.e., self-reported pill counts) and infrequently used direct (i.e., varenicline levels) methods, and abstinence outcomes have not been previously examined, nor has their impact on the outcomes of a genetically randomized clinical trial been assessed.

METHODS

At Week 1 following target quit date, self-reported pill count and salivary varenicline levels were obtained from participants (N = 376) in a smoking cessation clinical trial (NCT01314001). Point-prevalence abstinence was biochemically-verified by salivary cotinine at Week 1 and by exhaled carbon monoxide at Week 1, end-of-treatment, 6 and 12 months following treatment. Blood nicotine metabolite ratio (NMR) was obtained at baseline.

RESULTS

Adherent individuals based on varenicline levels were significantly more likely to be abstinent than non-adherent individuals at Week 1 (odds ratios [ORs] 1.92-3.16, p's≤0.006), end-of-treatment (OR = 2.53, p = .004), and six months following treatment (OR = 2.30, p = .03). In contrast, pill counts did not consistently predict abstinence. Including direct measures of adherence enhanced the association between rate of nicotine metabolism (NMR) and end-of-treatment abstinence; normal metabolizers (NMR ≥ 0.31) were significantly more likely than slow metabolizers (NMR < 0.31) to be abstinent at end-of-treatment (OR = 2.00, p = .005).

CONCLUSION

Adherence based on salivary varenicline, rather than on pill counts, is predictive of Week 1 abstinence, irrespective of the biomarker of abstinence assessed, and of long-term abstinence. Direct measures of adherence enhance the ability to assess the impact of a biomarker or genetic marker on abstinence outcomes.

Algorithm for resolving discrepancies between claims for smoking cessation pharmacotherapies during pregnancy and smoking status in delivery records: The impact on estimates of utilisation

BACKGROUND

The linkage of routine data collections are valuable for population-based evaluation of smoking cessation pharmacotherapy in pregnancy where little is known about the utilisation or safety of these pharmacotherapies antenatally. The use of routine data collections to study smoking cessation pharmacotherapy is limited by disparities among data sources. This study developed an algorithm to resolve disparity between the evidence of pharmacotherapy utilisation for smoking cessation and the recording of smoking in pregnancy, examined its face validity and assessed the implications on estimates of smoking cessation pharmacotherapy utilisation.

METHODS

Perinatal records (n = 1,098,203) of women who gave birth in the Australian States of Western Australia and New South Wales (2004-2012) were linked to hospital admissions and pharmaceutical dispensing data. An algorithm, based on dispensing information about the type of smoking therapy, timing and quantity of supply reclassified certain groups of women as smoking during pregnancy. Face validity of the algorithm was tested by examining the distribution of factors associated with inaccurate recording of smoking status among women that the algorithm classified as misreporting smoking in pregnancy. Rate of utilisation among smokers, according to original and reclassified smoking status, was measured, to demonstrate the utility of the algorithm.

RESULTS

Smoking cessation pharmacotherapy were dispensed to 2184 women during pregnancy, of those 1013 women were originally recorded as non-smoking as per perinatal and hospital data. Application of the algorithm reclassified 730 women as smoking during pregnancy. The algorithm satisfied the test of face validity-the expected demographic factors of marriage, private hospital delivery and higher socioeconomic status, were more common in women whom the algorithm identified as misreporting their smoking status. Application of the algorithm resulted in smoking cessation pharmacotherapy utilisation estimates ranging from 2.3-3.6% of all pregnancies.

CONCLUSION

Researchers can use the algorithm presented herein to improve the identification of smoking among women who use cessation pharmacotherapies during pregnancy. Improved identification can improve the validity of safety analyses of smoking cessation pharmacotherapy-providing clinicians with valuable evidence to use when counselling women on the role of pharmacotherapy for smoking cessation during pregnancy.

Can we increase smokers' adherence to nicotine replacement therapy and does this help them quit?

OBJECTIVE

To examine the effects of five intervention components on smokers' adherence to combined nicotine patch and nicotine gum during a quit attempt and assess whether adherence is related to cessation.

METHOD

Smokers interested in quitting (N = 513; 59% female; 87% White) received nicotine patch plus nicotine gum and participated in a 2x2x2x2x2 randomized factorial experiment (i.e., 32 treatment conditions) evaluating five intervention components: (1) medication adherence counseling versus none; (2) automated medication adherence calls versus none; (3) electronic medication monitoring with feedback and counseling versus e-monitoring alone; (4) 26 versus 8 weeks of nicotine patch plus nicotine gum; and (5) maintenance counseling versus none. Adherence was assessed over the first 6 weeks post-target quit day via timeline follow-back (nicotine patch) and electronic medication dispenser (gum).

RESULTS

In the first 6 weeks post-quit day, 12% of participants used no patches or gum, and 40% used the patch every day. Only 1.4% used both patch and gum adherently every day in the 6 weeks post-target quit day. E-monitoring counseling increased gum use (from 1.9 to 2.6 pieces/day; p < .001) but did not increase abstinence. More adherent patch and gum use in the first 6 weeks were each associated with higher point-prevalence abstinence rates through 1 year.

CONCLUSIONS

This large experiment with electronic monitoring of nicotine gum adherence showed that e-monitoring counseling increased gum use but not abstinence. Adherence to nicotine patch and to gum were each strongly related to abstinence, but it is unclear whether adherence increases abstinence, or relapse causes medication discontinuation.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT01120704.

The association between nicotine dependence and physical health among people receiving injectable diacetylmorphine or hydromorphone for the treatment of chronic opioid use disorder

INTRODUCTION

People with chronic opioid use disorder often present to treatment with individual and structural vulnerabilities and remain at risk of reporting adverse health outcomes. This risk is greatly compounded by tobacco smoking, which is highly prevalent among people with chronic opioid use disorder. Despite the known burden of tobacco smoking on health, the relationship between nicotine dependence and health has not been studied among those receiving injectable opioid agonist treatment. As such, the present study aims to explore the association between nicotine dependence and physical health among participants of the Study to Assess Longer-Term Opioid Medication Effectiveness (SALOME) at baseline and six-months.

METHODS

SALOME was a double-blind phase III clinical trial testing the non-inferiority of injectable hydromorphone to injectable diacetylmorphine for chronic opioid use disorder. Participants reporting tobacco smoking were included in a linear regression analysis of physical health at baseline (before receiving treatment) and at six-months.

RESULTS

At baseline, nicotine dependence score, lifetime history of emotional, physical, or sexual abuse and prior month safe injection site access were independently and significantly associated with physical health. At six-months nicotine dependence score was the only variable that maintained this significant and independent association with physical health.

CONCLUSIONS

Findings indicate that after six-months, the injectable treatment effectively brought equity to patients' physical health status, yet the association with nicotine dependence remained. Findings could inform whether the provision of treatment for nicotine dependence should be made a priority in settings where injectable opioid agonist treatment is delivered to achieve improvements in overall physical health in this population.

Factors associated with smoking cessation success in Lebanon

Objective:

The objective is to assess factors associated with the success rate of smoking cessation among Lebanese smokers in a smoking cessation center.

Methods:

A cross-sectional data study, conducted between March 2014 and March 2016 in an outpatient smoking cessation center with 156 enrolled patients. The patient’s nicotine dependence and motivation to quit smoking were evaluated according to the Fagerstrom Test for Nicotine Dependence and Richmond tests respectively.

Results:

The number of packs smoked per year decreased the odds of smoking cessation success (p=0.004, ORa=0.982, CI 0.97-0.994), while the compliance with the offered treatment increased the odds of success by 7.68 times (p<0.001, ORa=7.68, CI 3.438-17.187). Highly dependent and highly motivated smokers had more success in the quitting process compared to those with a lower dependence and motivation respectively.

Conclusion:

Our findings showed that many factors can influence smoking cessation, an experience described as difficult, most significantly the number of packs per year and compliance with the smoking cessation treatment. Moreover, although these outcomes are not representative of the entire Lebanese population, we believe that health authorities could utilize these results when implementing upcoming smoking cessations programs. All attempts at cessation should have a goal of reducing the number of packs smoked per year to improve the chances of ceasing into the future.

Factors Associated with Adherence to Transdermal Nicotine Patches within a Smoking Cessation Effectiveness Trial

BACKGROUND

Adherence to transdermal nicotine patches, one of the most popular and effective treatment for nicotine dependence, remains very low and is a strong predictor of cessation rates. This study examined individual factors related to adherence as well as differences over time between adherent (≥ 80% of daily patch use) and non-adherent participants (< 80% of daily patch use).

METHODS

We analyzed data from 440 participants who received 8 weeks of 21mg transdermal nicotine and 4 behavioral counseling sessions within an effectiveness trial that examined the effects of long-term treatment. Multiple logistical regression assessed baseline variables associated with patch adherence and generalized estimating equations (GEE) were used to evaluate changes in craving and withdrawal, depressive and anxiety symptoms, substitute and complementary reinforcers, and side effects between participants who were or were not adherent.

RESULTS

In a logistic regression model, being female, living with a child or children, and higher self-reported anxiety symptoms were predictive of lower patch adherence (p < .05). In the GEE analysis, adherence was significantly associated with: a greater reduction in craving, a greater engagement in substitute reinforcers, and a greater decrease in complementary reinforcers over time (p < .05).

CONCLUSIONS

Difficulties adhering to transdermal nicotine patches may be related to psychiatric comorbidity, difficulty managing nicotine craving, and challenges with engaging in substitute reinforcers and reducing exposure to complementary reinforcers. These constructs may serve as targets for interventions designed to increase treatment adherence.

Cancer-related disease factors and smoking cessation treatment: Analysis of an ongoing clinical trial

OBJECTIVE

Smoking cessation treatment should be an important aspect of cancer care. In this study, we evaluated whether cancer-related disease factors adversely influence smoking cessation treatment.

METHODS

Smokers with cancer (within 5 years of diagnosis, any tumor site) were recruited for an ongoing trial of varenicline for smoking cessation. Disease factors, assessed at baseline, included tumor site, cancer treatment, time since diagnosis, and health-related quality of life. Medication adherence was defined by 132 of 165 pills taken and counseling adherence was defined by 4 of 4 behavioral counseling sessions attended. Abstinence was bioverified at Week 12. Using logistic regression analysis, we assessed the relationship between disease factors and 12-week medication adherence, counseling adherence, and abstinence.

RESULTS

Of 144 participants, 56% were medication adherent, 74% were counseling adherent, and 39% were abstinent. Health-related quality of life predicted medication adherence (OR: 1.08, 95% CI, 1.01-1.16, P = .019, d = 0.20) but not counseling adherence or 12-week abstinence. Tumor site, cancer treatment, and time since diagnosis did not predict any smoking cessation treatment outcomes.

CONCLUSIONS

Cancer-related disease factors did not predict cancer survivors' engagement or success in smoking cessation treatment. Findings support National Comprehensive Cancer Network Clinical Practice guidelines that recommend smoking cessation treatment for all smokers with cancer, regardless of time since diagnosis.

Addressing varenicline adherence through repackaging in a dose administration aid

Background

Ensuring adherence to prescribed smoking cessation medications, such as Champix^® (varenicline), is essential during a quit attempt as non-adherence can significantly reduce the likelihood of achieving prolonged smoking abstinence. The use of dose administration aids may improve adherence, though medication stability on repackaging is not guaranteed, due to a lack of available data from manufacturers supporting this practice.

Objective

To determine the suitability for repackaging varenicline tartrate tablets into a dose administration aid, by assessing its physical and chemical stability after being repackaged and stored at ambient conditions for 6 weeks.

Methods

Varenicline tartrate (1.0 mg) tablets were repackaged into commercially available Webster-pak^® blister compartments and stored for 42 days at ambient conditions characteristic of a Zone IVB climate (30 ± 2°C and 75 ± 5% relative humidity) according to the World Health Organization (WHO) guidelines on pharmaceutical stability testing. Physical and chemical tests were performed on the repackaged and control tablets, including an assessment of: tablet thickness, hardness, weight uniformity, friability, dissolution, disintegration, and content uniformity after exposure to ambient conditions and light according to International Council on Harmonisation of Technical Requirements of Pharmaceuticals for Human Use guideline Q1B.

Results

Weight, friability, and thickness of the tablets complied with compendial standards. A validated high performance liquid chromatography method was used to confirm that after exposure to light, and repackaging at 30°C/75% relative humidity, the tablets remained within the required 95%–105% of the stated drug content. However, tablet hardness and disintegration decreased over time, with tablets becoming softer and undergoing more rapid disintegration in water.

Conclusion

Repackaging 1.0 mg varenicline tartrate tablets into a dose administration aid can be undertaken to improve adherence rates and therefore smoking abstinence rates. This can be performed without compromising either the physical or chemical stability of the tablets.

Measures and predictors of varenicline adherence in the treatment of nicotine dependence

INTRODUCTION

While adherence to medication in smoking cessation clinical trials is strongly associated with clinical outcome, very few studies have evaluated the validity of pill count as a measure of adherence relative to a biological assay, and evaluated a broad range of correlates of adherence.

METHODS

In a smoking cessation clinical trial of varenicline, we compared pill counts collected over 4 different time periods to varenicline salivary levels taken after 2weeks of treatment, as well as evaluated predictors of adherence to varenicline.

RESULTS

Using a binary measure of adherence based on salivary varenicline levels, adherence was higher among older, white, and more educated participants. Relative to 3, 7, and 14-day pill count, 12-week pill count was the only significant measure able to discriminate adherence as defined by salivary varenicline levels (assessed by area under the receiver operating characteristic curve; AUC=0.59, p=0.004). Seventy-two percent of participants who indicated adherence on 12-week pill count were classified as adherent based on varenicline saliva levels (sensitivity=0.80; specificity=0.40). There was modest variability in the relationship between 12-week pill count and varenicline levels across race and rate of nicotine metabolism. Lastly, General Estimating Equation models demonstrated that longitudinal changes in withdrawal, craving, negative and positive affect, and side effect count and severity were not related to adherence based on salivary varenicline levels.

CONCLUSIONS

These results indicate that 12-week pill count was the best, albeit a relatively weak, measure of varenicline adherence; additional factors associated with treatment adherence need to be identified.

Effectiveness of intensive practice nurse counselling versus brief general practitioner advice, both combined with varenicline, for smoking cessation: a randomized pragmatic trial in primary care

AIMS

To study the effectiveness of intensive counselling by a practice nurse (PN) versus brief advice by a general practitioner (GP), each combined with pharmacotherapy, for 6 months' tobacco abstinence (primary outcome). Secondary outcomes included 12-month abstinence, medication adherence and incremental costs per life-year gained.

DESIGN

A multi-site (n = 10), two-group, parallel, pragmatic randomized controlled trial.

SETTING

A network of primary health-care centres in the Netherlands.

PARTICIPANTS

A total of 295 adult daily smokers (mean age = 48 years; mean cigarettes/day = 19).

INTERVENTION AND COMPARATOR

Patients were randomized to receive individual counselling by a practice nurse (PN) (n = 149) or brief advice by a general practitioner (GP) (146). All patients received 12 weeks of open-label varenicline.

MEASUREMENTS

The primary outcome was prolonged biochemically validated abstinence from weeks 9 to 26 after treatment initiation. Secondary outcomes included abstinence from weeks 9 to 52, good dosing adherence (> 80% days taken) and incremental costs per life-year gained.

FINDINGS

Abstinence rates in the PN versus GP groups were 32.2% (n = 48) versus 39.0% [n = 57; odds ratio (OR) = 0.71; 95% confidence interval (CI) = 0.44-1.16] from weeks 9 to 26 and 25.5% (n = 38) versus 28.8% (n = 42; OR = 0.84, 95% CI = 0.50-1.43) from weeks 9 to 52, respectively. Values of the Bayes factor indicated that the PN and GP were equally effective. Good dosing adherence was significantly lower in the PN (45.5%, n = 56/123) than in the GP group (62.0%, n = 75/121; OR = 0.45, 95% CI = 0.26-0.77), and the incremental costs per life-year gained were -€416.10.

CONCLUSIONS

Among people seeking help to stop smoking from their general practice, one-off brief advice from a general practitioner appears to be as effective as several sessions of behavioural support from a practice nurse when smoking cessation medication is provided.

Moderators of smoking cessation outcomes in a randomized-controlled trial of varenicline versus placebo

RATIONALE AND OBJECTIVE

Varenicline has gained a reputation as the optimal intervention for treatment resistant smokers, yet more than half of those who try it do not succeed. To better understand individual differences in the effectiveness of varenicline, this study evaluates the effectiveness of varenicline for smoking cessation in a double-blind, placebo-controlled, randomized clinical trial and examines the influence of psychological factors on treatment outcome.

METHOD

Two hundred five cigarette smokers interested in quitting were randomly assigned to 12 weeks of varenicline or placebo. Outcomes examined were CO-confirmed continuous abstinence for the past month, average number of cigarettes smoked per day, and 7-day point prevalence.

RESULTS

Varenicline-treated participants were more likely than placebo to achieve continuous abstinence at the end of treatment (OR = 3.29; RR = 2.62), and 7-day point prevalence rates showed an effect of medication at each time point. Participants in both groups significantly reduced their smoking during the course of treatment and follow-up, and the medication by visit interaction was significant in the expected direction. Impulsivity and personality style emerged as moderators of the relationship between medication condition and treatment outcome.

CONCLUSIONS

In addition to replicating efficacy results for varenicline versus placebo, the present study shows that the efficacy of pharmacotherapy is influenced by psychological factors. In an era where pharmacotherapy is often perceived as the "silver bullet," we are reminded that smoking cessation is a dynamic process and intervention must be adaptable to address individual differences.

A Randomised Controlled Trial Evaluating the Effectiveness and Tolerability of Step-up and Step-down Varenicline Therapy for Smoking Cessation: A Study Protocol

Background: Varenicline remains the most effective medication for smoking cessation; however, discontinuation as a result of adverse events negatively impacts medication adherence, and the likelihood of a quit attempt being successful. Post-treatment cravings and withdrawal symptoms may also occur, increasing the likelihood of treatment failure, due to lapse and relapse after achieving initial abstinence. This protocol details a trial investigating changes in the effectiveness and tolerability of varenicline, when an extended step-up and step-down regimen are used.

Methods: A phase four, randomised, double-blinded, placebo-controlled single-centre study with a treatment period of 16 weeks, and follow-up period of 12 weeks will be conducted. Up to 201 participants will be enrolled and allocated in a 1:1:1 ratio to a placebo-matching control group, step-up, or step-down intervention group, all receiving behavioural counselling and quitting advice. Participants will be contacted weekly during treatment and fortnightly during follow-up. Eligible participants are smokers over 18 years old, willing to quit smoking, are able to attend clinic visits, and have no uncontrolled or serious medical issues. Primary outcome measures are comparisons of biochemically confirmed continuous abstinence rates, 7-day point prevalence abstinence rates, and the frequency, severity and duration of adverse events, cravings and withdrawal symptoms. Secondary outcome measures are participant adherence to the study medication throughout treatment, and comparisons of changes in smoking satisfaction and reward. Effects of each regimen on smoking cessation will be assessed by logistic regression, with survival analyses used for a more precise estimate of when cessation occurs. Primary endpoints will then be compared using a general linear model. Australian New Zealand Clinical Trials Registry: ACTRN12616000802404p

Effect of 0.5 mg versus 1 mg varenicline for smoking cessation: a randomized controlled trial

AIMS

Varenicline is used in smoking cessation. The aims of the trial were to test for differences between standard 1- and 0.5-mg doses (both twice daily during 8 weeks) in (1) abstinence, (2) adherence and (3) side effects.

DESIGN

Open-label randomized parallel-group controlled trial with 1-year follow-up. All those randomized were included in the final sample using an intention-to-treat (ITT) approach.

SETTING

Stop-Smoking Clinic of the Virgen Macarena University Hospital in Seville, Spain.

PARTICIPANTS

The study comprised smokers (n = 484), 59.5% of whom were men with a mean age of 50.67 years and a smoking history of 37.5 pack-years.

INTERVENTION AND COMPARATOR

Participants were randomized to 1 mg (n = 245) versus 0.5 mg (n = 239) and received behavioural support, which consisted of a baseline visit and six follow-ups during 1 year.

MEASUREMENTS

The primary outcome was continuous self-reported abstinence during 1 year, with biochemical verification. The secondary outcomes were adherence and side effects. Also measured were baseline demographics, medical history and smoking characteristics.

FINDINGS

Abstinence rates at 1 year were 46.5% with 1 mg versus 46.4% with 0.5 mg [odds ratio (OR) = 0.997; 95% confidence interval (CI) = 0.7-1.43; P = 1.0]; Bayes factor in favour of H0 = 238.507, Bayes factor against H0 = 0.004. Treatment adherence was similar in both regimens (OR = 1.16; 95% CI = 0.8-1.7; P = 0.44). Side effects were reported in 19.3% of cases with 1 mg versus 12.1% with 0.5 mg, although with no significant differences between regimens (OR = 1.73; 95% CI = 0.94-3.18; P = 0.093).

CONCLUSIONS

There appears to be no difference in smoking cessation effectiveness between 1 mg and 0.5 mg varenicline, both administered twice daily for 8 weeks, with similar rates of abstinence (46.5% versus 46.4%), adherence and side effects.

Combining Text Messaging and Telephone Counseling to Increase Varenicline Adherence and Smoking Abstinence Among Cigarette Smokers Living with HIV: A Randomized Controlled Study

Smoking represents an important health risk for people living with HIV (PLHIV). Low adherence to smoking cessation pharmacotherapy may limit treatment effectiveness. In this study, 158 participants recruited from three HIV care centers in New York City were randomized to receive 12-weeks of varenicline (Chantix) either alone as standard care (SC) or in combination with text message (TM) support or TM plus cell phone-delivered adherence-focused motivational and behavioral therapy (ABT). Generalized linear mixed-effect models found a significant decline in varenicline adherence from week 1-12 across treatment groups. At 12-weeks, the probability of smoking abstinence was significantly higher in SC+TM+ABT than in SC. The study demonstrates the feasibility of delivering adherence-focused interventions to PLHIV who smoke. Findings suggest intensive behavioral support is an important component of an effective smoking cessation intervention for this population, and a focus on improving adherence self-efficacy may lead to more consistent adherence and higher smoking abstinence.

The clinical utility of the Medication Adherence Questionnaire (MAQ) in an alcohol pharmacotherapy trial

BACKGROUND

Medication nonadherence is a ubiquitous problem in pharmacology treatment for alcohol use disorders. Unintentional and purposeful nonadherence as measured by the Medication Adherence Questionnaire (MAQ) has been shown to predict problems with medication adherence; however, feedback from the MAQ has never been incorporated into a behavioral intervention to facilitate medication adherence. We assessed the integration of the MAQ into medical management (MM), a counseling approach frequently employed in conjunction with alcohol pharmacotherapy, to determine whether prior patterns of nonadherence could be addressed effectively to promote medication adherence.

METHODS

We conducted a post-hoc analysis of data from 131 alcohol dependent smokers who participated in a double blind, placebo controlled study of varenicline for the treatment of alcohol dependence. At baseline, participants completed a single administration of the MAQ, which asks 2 questions about unintentional nonadherence (e.g., forgetting) and 2 questions about purposeful nonadherence (e.g., stopping because feeling good or feeling bad). Based on these responses, participants were divided into 1 of 3 three categories. Adherent (n=60), Unintentional or Purposeful Nonadherent (n=50) and Unintentional and Purposeful Nonadherent (n=21). Over the course of the 16-week treatment period, patients were expected to participate in 12 medical management (MM) sessions; a brief psychosocial treatment. Feedback based on the MAQ responses was integrated into the MM sessions to facilitate medication and treatment adherence.

RESULTS

The 3 adherence groups were compared on baseline characteristics, medication adherence, treatment attendance and end-of-treatment patient ratings of treatment helpfulness. Baseline demographics and characteristics were not significantly different among the three categories. We found no statistically significant differences among the three groups with respect to pill adherence, treatment attendance, and treatment satisfaction ratings.

CONCLUSIONS

The findings suggest that the incorporation of MAQ feedback into the MM approach could be effective in mitigating risks associated with prior patterns of nonadherence suggesting that further testing of the integrated behavioral approach is warranted.

Lessons learned in the development and evaluation of RxCoach™, an mHealth app to increase tobacco cessation medication adherence

OBJECTIVE

In this project we developed and evaluated a mobile health app to improve adherence to tobacco cessation medication.

METHODS

The study was conducted in three phases: (1) Create app with input from our consultant, focus groups and user testing; (2) Test feasibility of the app; and (3) Develop and user-test the barcode scanner.

RESULTS

Focus group feedback was instrumental in developing content and creating the user interface. User testing helped to identify problems and refine the app. The feasibility trial provided "real world" testing. We experienced challenges in recruitment due to the inclusion criteria. We had high attrition due to technical issues, medication side effects, enrollment procedures, and lack of personal contact. Among the five retained participants, use of the app was associated with good medication adherence and high consumer satisfaction.

CONCLUSION

The small sample size limits the generalizability of the findings and the conclusions that can be drawn from the study. However, the feasibility trial enabled the team to identify ways to improve the conduct of this and other mHealth studies.

PRACTICAL IMPLICATIONS

We should expand RxCoach to include all prescription and over-the-counter tobacco cessation medications, and re-test for feasibility using lessons learned to improve recruitment and retention.